Abstract—Single sensor digital cameras capture only one color value for every pixel location. The process of reconstructing a full color image from these incomplete color samples output from an image sensor overlaid with a color filter array (CFA) is called demosaicing or Color Filter Array (CFA) interpolation. The most commonly used CFA configuration is the Bayer filter. The proposed demosaicing method makes use of multiscale color gradients to adaptively combine color difference estimates from horizontal and vertical directions and determine the contribution of each direction to the green channel interpolation. This method does not require any thresholds and is non iterative. The red and blue channels are then refined using structural approximation.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Similarity and Variance of Color Difference Based DemosaicingRadita Apriana
The aim of the project is to find the missing color samples at each pixel location by the
combination of similarity algorithm and the variance of colour difference algorithm. Many demosaicing
algorithms find edges in horizontal and vertical directions, which are not suitable for other directions.
Hence using the similarity algorithm the edges are found in different directions. But in this similarity
algorithm sometimes the horizontal and vertical directions are mislead. Hence this problem can be rectified
using the variance of colour difference algorithm. It is proved experimentally that this new demosaicing
algorithm based on similarity and variance of colouyr difference has better colour peak signal to noise ratio
(CPSNR). It has better o0bjective and subjective performance. It is an analysis study of both similarity and
colour variance algorithms.
PREDICTION BASED LOSSLESS COMPRESSION SCHEME FOR BAYER COLOUR FILTER ARRAY IM...ijiert bestjournal
This paper presents an experimental evaluation of t he effectiveness of various techniques for lossless compression of CFA images. A colour image requires at least three colour samples at each pixel location. A digital camera would need th ree separate sensors to completely measure the image. In a three chip colour camera,the light entering the camera is split and projected onto each spectral sensor. Each sensor requires its prop er driving electronics,and the sensors have to be registered precisely. These additional requireme nts add a large expense to the system. Thus most commercial digital cameras use colour filterar rays to sample red,green,and blue colours according to a specificpattern. At the location of each pixel only one colour sample istaken and the values of the other colours must be interpolate d usingneighbouring samples. This colour plane interpolation is knownas demosaicing.Demosaic ing is generally carried out before compression.Recently,it was found that compression first schemes outperform the conventional demosaicing first schemes in terms of output image quality.An efficient prediction based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels w hen predicting a pixel,an adaptive colour difference estimation scheme to remove the colour s pectral redundancy when handling red and blue samples,and an adaptive code word generation technique. Simulation results show the comparison of different coding scheme in terms of compression ratio.
This document discusses color image processing and different color models. It begins with an introduction and then covers color fundamentals such as brightness, hue, and saturation. It describes common color models like RGB, CMY, HSI, and YIQ. Pseudo color processing and full color image processing are explained. Color transformations between color models are also discussed. Implementation tips for interpolation methods in color processing are provided. The document concludes with thanks to the head of the computer science department.
AN IMPLEMENTATION OF ADAPTIVE PROPAGATION-BASED COLOR SAMPLING FOR IMAGE MATT...ijiert bestjournal
Natural image matting refers to the problem of an e xtracting the region of interest such as foreground object from an image based on the user i nputs like scribbles or trimap. The proposed algorithm combines propagation and color s ampling methods. Unlike previous propagation-based approaches that used either local or non local propagation method,the proposed framework adaptively uses both local and n on local processes according to the detection result of the different region in the ima ge. The proposed color sampling strategy,which is based on the characteristic of super pixel uses a simple sample selection criterion and requires significantly less computational cost. Proposed method used another method to convert original image to trimap image,which is ba sed on selection process. That use roipoly tool to select a polygonal region of interest withi n the image,it can use as a mask for masked filtering. In which used the Chan-Vese algorithm fo r image segmentation
This document contains information about a lecture on digital image processing given by Dr. Moe Moe Myint at Technological University in Kyaukse, Myanmar. It provides the lecture schedule and contact information for Dr. Myint, as well as an outline of topics to be covered in Chapter 6, including color fundamentals, color models, color transformations, smoothing and sharpening of color images, and color image compression. The document discusses concepts such as the RGB, CMYK, and HSI color models and how they represent color, as well as methods for processing and manipulating colors in digital images.
In image processing colour segmentation is used to extract features of an object in both special and frequency domains. The objective of this paper is to use colour segmentation technique to identify the defected region of fruits and corresponding percentage of frequency components from its Spectrogram. Here we separate the defective portion of fruit using colour segmentation technique taking four images from four directions to get the appropriate result of 3D images. The percentage of the defective portion is determined using scatterplot of the colours of the image. Next, we apply the similar concept to spectrogram of an image (even applicable in speech signal) to extract the percentages of frequency components of the signal.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Similarity and Variance of Color Difference Based DemosaicingRadita Apriana
The aim of the project is to find the missing color samples at each pixel location by the
combination of similarity algorithm and the variance of colour difference algorithm. Many demosaicing
algorithms find edges in horizontal and vertical directions, which are not suitable for other directions.
Hence using the similarity algorithm the edges are found in different directions. But in this similarity
algorithm sometimes the horizontal and vertical directions are mislead. Hence this problem can be rectified
using the variance of colour difference algorithm. It is proved experimentally that this new demosaicing
algorithm based on similarity and variance of colouyr difference has better colour peak signal to noise ratio
(CPSNR). It has better o0bjective and subjective performance. It is an analysis study of both similarity and
colour variance algorithms.
PREDICTION BASED LOSSLESS COMPRESSION SCHEME FOR BAYER COLOUR FILTER ARRAY IM...ijiert bestjournal
This paper presents an experimental evaluation of t he effectiveness of various techniques for lossless compression of CFA images. A colour image requires at least three colour samples at each pixel location. A digital camera would need th ree separate sensors to completely measure the image. In a three chip colour camera,the light entering the camera is split and projected onto each spectral sensor. Each sensor requires its prop er driving electronics,and the sensors have to be registered precisely. These additional requireme nts add a large expense to the system. Thus most commercial digital cameras use colour filterar rays to sample red,green,and blue colours according to a specificpattern. At the location of each pixel only one colour sample istaken and the values of the other colours must be interpolate d usingneighbouring samples. This colour plane interpolation is knownas demosaicing.Demosaic ing is generally carried out before compression.Recently,it was found that compression first schemes outperform the conventional demosaicing first schemes in terms of output image quality.An efficient prediction based lossless compression scheme for Bayer CFA images is proposed in this paper. It exploits a context matching technique to rank the neighboring pixels w hen predicting a pixel,an adaptive colour difference estimation scheme to remove the colour s pectral redundancy when handling red and blue samples,and an adaptive code word generation technique. Simulation results show the comparison of different coding scheme in terms of compression ratio.
This document discusses color image processing and different color models. It begins with an introduction and then covers color fundamentals such as brightness, hue, and saturation. It describes common color models like RGB, CMY, HSI, and YIQ. Pseudo color processing and full color image processing are explained. Color transformations between color models are also discussed. Implementation tips for interpolation methods in color processing are provided. The document concludes with thanks to the head of the computer science department.
AN IMPLEMENTATION OF ADAPTIVE PROPAGATION-BASED COLOR SAMPLING FOR IMAGE MATT...ijiert bestjournal
Natural image matting refers to the problem of an e xtracting the region of interest such as foreground object from an image based on the user i nputs like scribbles or trimap. The proposed algorithm combines propagation and color s ampling methods. Unlike previous propagation-based approaches that used either local or non local propagation method,the proposed framework adaptively uses both local and n on local processes according to the detection result of the different region in the ima ge. The proposed color sampling strategy,which is based on the characteristic of super pixel uses a simple sample selection criterion and requires significantly less computational cost. Proposed method used another method to convert original image to trimap image,which is ba sed on selection process. That use roipoly tool to select a polygonal region of interest withi n the image,it can use as a mask for masked filtering. In which used the Chan-Vese algorithm fo r image segmentation
This document contains information about a lecture on digital image processing given by Dr. Moe Moe Myint at Technological University in Kyaukse, Myanmar. It provides the lecture schedule and contact information for Dr. Myint, as well as an outline of topics to be covered in Chapter 6, including color fundamentals, color models, color transformations, smoothing and sharpening of color images, and color image compression. The document discusses concepts such as the RGB, CMYK, and HSI color models and how they represent color, as well as methods for processing and manipulating colors in digital images.
In image processing colour segmentation is used to extract features of an object in both special and frequency domains. The objective of this paper is to use colour segmentation technique to identify the defected region of fruits and corresponding percentage of frequency components from its Spectrogram. Here we separate the defective portion of fruit using colour segmentation technique taking four images from four directions to get the appropriate result of 3D images. The percentage of the defective portion is determined using scatterplot of the colours of the image. Next, we apply the similar concept to spectrogram of an image (even applicable in speech signal) to extract the percentages of frequency components of the signal.
Object Elimination and Reconstruction Using an Effective Inpainting MethodIOSR Journals
Abstract: Three major problems have been found in the existing algorithms of image inpainting:
Reconstruction of large regions, Preference of filling-in and Choice of best exemplars to synthesize the missing
region. The proposed algorithm introduces two ideas that deal with these problems preserving edge continuity
along with decrease in error propagation. The proposed algorithm introduces a modified priority computation
in order to generate better edges in the omitted region and to reduce the transmission of errors in the resultant
image a novel way to find optimal exemplar has been proposed. This proposal optimizes the reconstruction
process and increases the accuracy. The proposed algorithm removes blurness and builds edges efficiently
while reconstructing large target region.
Keywords: Image inpainting, texture synthesis, Image Completion, exemplar-based method
Segmentation of Color Image using Adaptive Thresholding and Masking with Wate...Habibur Rahman
The document proposes a modified watershed algorithm for image segmentation. It applies adaptive masking and thresholding to each color channel before combining the results. The modified algorithm is compared to FCM, RG, and HKM using metrics like PSNR, MSE, PSNRRGB, and CQM on 10 images. Results show the proposed method ensures accuracy and quality while being faster than other algorithms, making it suitable for real-time use. It performs better than the other algorithms according to visual and quantitative analysis.
The document discusses an automatic process to extract contour lines from topographical maps by:
1) Extracting contour lines from maps based on color and thinning the lines.
2) Reconnecting any broken contour lines.
3) Tracing the contours using an algorithm and extracting altitude data.
4) Storing the extracted contour lines and their attribute data in a database.
Contour Line Tracing Algorithm for Digital Topographic MapsCSCJournals
Topographic maps contain information related to roads, contours, landmarks land covers and rivers etc. For any Remote sensing and GIS based project, creating a database using digitization techniques is a tedious and time consuming process especially for contour tracing. Contour line is very important information that these maps provide. They are mainly used for determining slope of the landforms or rivers. These contour lines are also used for generating Digital Elevation Model (DEM) for 3D surface generation from any satellite imagery or aerial photographs. This paper suggests an algorithm that can be used for tracing contour lines automatically from contour maps extracted from the topographical sheets and creating a database. In our approach, we have proposed a modified Moore's Neighbor contour tracing algorithm to trace all contours in the given topographic maps. The proposed approach is tested on several topographic maps and provides satisfactory results and takes less time to trace the contour lines compared with other existing algorithms.
Reduced-reference Video Quality Metric Using Spatial Information in Salient R...TELKOMNIKA JOURNAL
In multimedia transmission, it is important to rely on an objective quality metric which accurately
represents the subjective quality of processed images and video sequences. Maintaining acceptable
Quality of Experience in video transmission requires the ability to measure the quality of the video seen at
the receiver end. Reduced-reference metrics make use of side-information that is transmitted to the
receiver for estimating the quality of the received sequence with low complexity. This attribute enables
real-time assessment and visual degradation detection caused by transmission and compression errors. A
novel reduced-reference video quality known as the Spatial Information in Salient Regions Reduced
Reference Metric is proposed. The approach proposed makes use of spatial activity to estimate the
received sequence distortion after concealment. The statistical elements analysed in this work are based
on extracted edges and their luminance distributions. Results highlight that the proposed edge dissimilarit y
measure has a good correlation with DMOS scores from the LIVE Video Database.
This document compares the accuracy of determining volumes using close range photogrammetry versus traditional methods. It presents a case study where the volume of a test field was calculated using both approaches. Using traditional methods with 425 control points, the volume was calculated as 221475.14 m3 using trapezoidal rules, 221424.52 m3 using Simpson's rule, and 221484.05 m3 using Simpson's 3/8 rule. Using close range photogrammetry with 42 control points and 574 generated points, the volume was calculated as 215310.60 m3 using trapezoidal rules, 215300.43 m3 using Simpson's rule, and 215304.12 m3 using Simpson's 3
Towards better performance: phase congruency based face recognitionTELKOMNIKA JOURNAL
Phase congruency is an edge detector and measurement of the significant feature in the image. It is a robust method against contrast and illumination variation. In this paper, two novel techniques are introduced for developing alow-cost human identification system based on face recognition. Firstly, the valuable phase congruency features, the gradient-edges and their associate dangles are utilized separately for classifying 130 subjects taken from three face databases with the motivation of eliminating the feature extraction phase. By doing this, the complexity can be significantly reduced. Secondly, the training process is modified when a new technique, called averaging-vectors is developed to accelerate the training process and minimizes the matching time to the lowest value. However, for more comparison and accurate evaluation,three competitive classifiers: Euclidean distance (ED),cosine distance (CD), and Manhattan distance (MD) are considered in this work. The system performance is very competitive and acceptable, where the experimental results show promising recognition rates with a reasonable matching time.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IRJET-A Review on Implementation of High Dimension Colour Transform in Domain...IRJET Journal
This document reviews algorithms for detecting salient regions in images using high dimensional color transforms. It summarizes several existing methods that use color contrast, frequency analysis, and superpixel segmentation. A key method discussed creates a saliency map by finding the optimal linear combination of color coefficients in a high dimensional color space. This allows more accurate detection of salient objects versus methods using only RGB color. The performance of this high dimensional color transform method is improved by also utilizing relative location and color contrast between superpixels as learned features.
The document describes a new image scaling algorithm based on an area pixel model that aims to achieve low complexity suitable for VLSI implementation. It presents an edge-oriented area-pixel scaling processor that uses an approximate technique to calculate pixel areas with 6-bit integers rather than floating point values. It also employs a simple edge catching technique to better preserve edges. The proposed 7-stage VLSI architecture was implemented using Verilog HDL and synthesized using a 0.18-micron process, achieving a processing rate of 200MHz with 10.4K gate counts. Experimental results showed it performs better than other lower complexity methods in terms of quality and speed.
SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHINGijma
This document summarizes a research paper that aimed to improve 3D point cloud segmentation through a hybrid approach using both object space and image space segmentation. The researchers used surface growing segmentation on 3D point clouds combined with spectral information from RGB and grayscale images to extract buildings, streets, and vegetation. Experiments on case studies showed that updating plane parameters and robust plane fitting improved building extraction, especially for low accuracy point clouds. Region growing in grayscale images also resulted in more realistic building roofs than using RGB images.
Extended hybrid region growing segmentation of point clouds with different re...csandit
In the recent years, 3D city reconstruction is one of the active researches in the field of
photogrammetry. The goal of this work is to improve and extend region growing based
segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral
information of RGB and grayscale image to extract building roofs, streets and vegetation. In
order to process 3D point clouds, hybrid segmentation is carried out in both object space and
image space. Our experiments on two case studies verify that updating plane parameters and
robust least squares plane fitting improves the results of building extraction especially in case
of low accurate point clouds. In addition, region growing in image space has been derived to
the fact that grayscale image is more flexible than RGB image and results in more realistic
building roofs.
Edge detection is one of the most powerful image analysis tools for enhancing and detecting edges. Indeed, identifying and localizing edges are a low level task in a variety of applications such as 3-D reconstruction, shape recognition, image compression, enhancement, and restoration. This paper introduces a new algorithm for detecting edges based on color space models. In this RGB image is taken as an input image and transforming the RGB image to color models such as YUV, YCbCr and XYZ. The edges have been detected for each component in color models separately and compared with the original image of that particular model. In order to measure the quality assessment between images, SSIM (Structural Similarity Index Method) and VIF (Visual Information Fidelity) has been calculated. The results have shown that XYZ color model is having high SSIM value and VIF value. In the previous papers, edge detection based on RGB color model has low SSIM and VIF values. So by converting the images into different color models shows a significant improvement in detection of edges. Keywords: Edge detection, Color models, SSIM, VIF.
Higher Order Feature Set For Underwater Noise ClassificationCSCJournals
The development of intelligent systems for classification of underwater noise sources has been a field of research interest for decades. Such systems include the extraction of features from the received signals, followed by the application of suitable classification algorithms. Most of the existing feature extraction methods rely on the classical power spectral methods, which may fail to provide information pertaining to the deviations from linearity and Gaussianity of stochastic processes. Hence, many recent research efforts focus on higher order spectral methods in order to prevail over such limitations. This paper makes use of bispectrum, which is a higher order spectrum of order three, in order to extract a set of robust features for the classification of underwater noise sources. An SVM classifier is used for evaluating the performance of the feature set.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper that proposes a new image interpolation technique to reconstruct high-resolution images from low-resolution counterparts while preserving edge structures. The technique estimates each pixel to be interpolated in two orthogonal directions and fuses the estimates using linear minimum mean square error estimation. This adaptive fusion approach can better discriminate edge directions in the local window compared to interpolating in a single direction. The technique aims to improve on traditional linear interpolation methods by adapting to local image gradients to reduce artifacts while preserving sharp edges. A simplified version is also presented to reduce computational costs with minimal impact on performance. Experiments showed the new technique can better preserve edges and reduce artifacts compared to other methods.
A Solution to Land Area Calculation for Android Phone using GPS-Luwei YangLuwei Yang
This document proposes an Android application to calculate land area using GPS. It records a user's path using GPS as they walk around a land area. It then calculates the total land area using the trapezoid method, which breaks the irregular shape into smaller trapezoids. The Kalman filter is used to improve GPS accuracy and reduce errors, achieving an average error of 3.64% in tests. Key aspects include using Gauss-Kruger projection to convert GPS coordinates to plane coordinates before area calculation, and employing the trapezoid method and Kalman filtering to accurately calculate irregular land shapes and compensate for GPS errors, respectively.
This paper presents a geometric approach to the coordinatization of a measured space called the Map
Maker’s algorithm. The measured space is defined by a distance matrix for sites which are reordered and
mapped to points in a two-dimensional Euclidean space. The algorithm is tested on distance matrices
created from 2D random point sets and the resulting coordinatizations compared with the original point
sets for confirmation. Tolerance levels are set to deal with the cumulative numerical errors in the
processing of the algorithm. The final point sets are found to be the same apart from translations,
reflections and rotations as expected. The algorithm also serves as a method for projecting higher
dimensional data to 2D.
Node Failure Prevention by Using Energy Efficient Routing In Wireless Sensor ...IJTET Journal
The most necessary issue that has to be solved in coming up with an information transmission rule for
wireless unplanned networks is a way to save unplanned node energy whereas meeting the wants of applications
users because the unplanned nodes are battery restricted. Whereas satisfying the energy saving demand, it’s
conjointly necessary to realize the standard of service. Just in case of emergency work, it's necessary to deliver the
information on time. Achieving quality of service in is additionally necessary. So as to realize this demand, Power -
efficient Energy-Aware routing protocol for wireless unplanned networks is planned that saves the energy by
expeditiously choosing the energy economical path within the routing method. When supply finds route to
destination, it calculates α for every route. The worth α is predicated on largest minimum residual energy of the trail
and hop count of the trail. If a route has higher α, then that path is chosen for routing the information. The worth of α
are higher, if the most important of minimum residual energy of the trail is higher and also the range of hop count is
lower. Once the trail is chosen, knowledge is transferred on the trail. So as to extend the energy potency any
transmission power of the nodes is additionally adjusted supported the situation of their neighbour. If the neighbours
of a node are closely placed thereto node, then transmission vary of the node is diminished. Thus it's enough for the
node to own the transmission power to achieve the neighbour at intervals that vary. As a result transmission power
of the node is cut back that later on reduces the energy consumption of the node. Our planned work is simulated
through Network machine (NS-2). Existing AODV and Man-Min energy routing protocol conjointly simulated
through NS-2 for performance comparison. Packet Delivery quantitative relation, Energy Consumption and end-toend
delay.
Mitigating The Power Fluctuation Of PMSG Wind Turbine In A Microgrid By Optim...IJTET Journal
Abstract— The major problem of PMSG wind turbine are power fluctuation. And this problem is overcome by new optimization technique and circuit model of the Superconducting Magnetic Energy Storage (SMES) with Fault Current Limiter (FCL) in a micro grid. Normally, SMES-FCL circuit which contain superconducting coil. In case of without fault condition, SMES-FCL act as the SMES unit to mitigate the power fluctuation of PMSG. Under fault condition, the SC is automatically connected to the system and it can be used as FCL to reduce the fault current. Then, the voltage drop of PMSG and fault current unit will be mitigated. By the energy function method is used to determine the optimal problem. Finally, this MATLAB result shows the superior control effect compare to the conventional method.
Activity Recognition From IR Images Using Fuzzy Clustering TechniquesIJTET Journal
Infrared sensors ensures that activity recognition is possible in the day and night times. It is used especially for activity monitoring of older adults as falls are more prevalent at night than the day. This paper focus on an application of fuzzy set techniques and it is capable of accurately detecting several different activity states related to fall detection and fall risk assessment and it also includes sitting, standing and being on the floor to ensure that elderly residents gets the help they need quickly in case of emergencies. Fall detection and fall risk assessment is used for an aging in place facility for the elderly people. It describes the silhouette extraction process, the image features , and the fuzzy clustering technique.
Joint Optimization of The two Tier Femto cells and Macro cell Users OFDMA Net...IJTET Journal
We proposed a novel joint sub channel and resource allocation for the two-tier OFDMA network. The multi-cell OFDMA network not only has to control the interference to the users, but also has to coordinate the cross-tier interference. A resource allocation scheme for cross-channel Femto and Macro is proposed, aiming to maximize the capacity. We formulate this joint optimization for both uplink and downlink in OFDMA network will be considered. To efficiently solve this problem using dual decomposition and low complexity methods. The resulting schemes efficiently allocate the resource and data sharing in a distributed way. The simulation results show that the less interference and provide significant throughput.
Object Elimination and Reconstruction Using an Effective Inpainting MethodIOSR Journals
Abstract: Three major problems have been found in the existing algorithms of image inpainting:
Reconstruction of large regions, Preference of filling-in and Choice of best exemplars to synthesize the missing
region. The proposed algorithm introduces two ideas that deal with these problems preserving edge continuity
along with decrease in error propagation. The proposed algorithm introduces a modified priority computation
in order to generate better edges in the omitted region and to reduce the transmission of errors in the resultant
image a novel way to find optimal exemplar has been proposed. This proposal optimizes the reconstruction
process and increases the accuracy. The proposed algorithm removes blurness and builds edges efficiently
while reconstructing large target region.
Keywords: Image inpainting, texture synthesis, Image Completion, exemplar-based method
Segmentation of Color Image using Adaptive Thresholding and Masking with Wate...Habibur Rahman
The document proposes a modified watershed algorithm for image segmentation. It applies adaptive masking and thresholding to each color channel before combining the results. The modified algorithm is compared to FCM, RG, and HKM using metrics like PSNR, MSE, PSNRRGB, and CQM on 10 images. Results show the proposed method ensures accuracy and quality while being faster than other algorithms, making it suitable for real-time use. It performs better than the other algorithms according to visual and quantitative analysis.
The document discusses an automatic process to extract contour lines from topographical maps by:
1) Extracting contour lines from maps based on color and thinning the lines.
2) Reconnecting any broken contour lines.
3) Tracing the contours using an algorithm and extracting altitude data.
4) Storing the extracted contour lines and their attribute data in a database.
Contour Line Tracing Algorithm for Digital Topographic MapsCSCJournals
Topographic maps contain information related to roads, contours, landmarks land covers and rivers etc. For any Remote sensing and GIS based project, creating a database using digitization techniques is a tedious and time consuming process especially for contour tracing. Contour line is very important information that these maps provide. They are mainly used for determining slope of the landforms or rivers. These contour lines are also used for generating Digital Elevation Model (DEM) for 3D surface generation from any satellite imagery or aerial photographs. This paper suggests an algorithm that can be used for tracing contour lines automatically from contour maps extracted from the topographical sheets and creating a database. In our approach, we have proposed a modified Moore's Neighbor contour tracing algorithm to trace all contours in the given topographic maps. The proposed approach is tested on several topographic maps and provides satisfactory results and takes less time to trace the contour lines compared with other existing algorithms.
Reduced-reference Video Quality Metric Using Spatial Information in Salient R...TELKOMNIKA JOURNAL
In multimedia transmission, it is important to rely on an objective quality metric which accurately
represents the subjective quality of processed images and video sequences. Maintaining acceptable
Quality of Experience in video transmission requires the ability to measure the quality of the video seen at
the receiver end. Reduced-reference metrics make use of side-information that is transmitted to the
receiver for estimating the quality of the received sequence with low complexity. This attribute enables
real-time assessment and visual degradation detection caused by transmission and compression errors. A
novel reduced-reference video quality known as the Spatial Information in Salient Regions Reduced
Reference Metric is proposed. The approach proposed makes use of spatial activity to estimate the
received sequence distortion after concealment. The statistical elements analysed in this work are based
on extracted edges and their luminance distributions. Results highlight that the proposed edge dissimilarit y
measure has a good correlation with DMOS scores from the LIVE Video Database.
This document compares the accuracy of determining volumes using close range photogrammetry versus traditional methods. It presents a case study where the volume of a test field was calculated using both approaches. Using traditional methods with 425 control points, the volume was calculated as 221475.14 m3 using trapezoidal rules, 221424.52 m3 using Simpson's rule, and 221484.05 m3 using Simpson's 3/8 rule. Using close range photogrammetry with 42 control points and 574 generated points, the volume was calculated as 215310.60 m3 using trapezoidal rules, 215300.43 m3 using Simpson's rule, and 215304.12 m3 using Simpson's 3
Towards better performance: phase congruency based face recognitionTELKOMNIKA JOURNAL
Phase congruency is an edge detector and measurement of the significant feature in the image. It is a robust method against contrast and illumination variation. In this paper, two novel techniques are introduced for developing alow-cost human identification system based on face recognition. Firstly, the valuable phase congruency features, the gradient-edges and their associate dangles are utilized separately for classifying 130 subjects taken from three face databases with the motivation of eliminating the feature extraction phase. By doing this, the complexity can be significantly reduced. Secondly, the training process is modified when a new technique, called averaging-vectors is developed to accelerate the training process and minimizes the matching time to the lowest value. However, for more comparison and accurate evaluation,three competitive classifiers: Euclidean distance (ED),cosine distance (CD), and Manhattan distance (MD) are considered in this work. The system performance is very competitive and acceptable, where the experimental results show promising recognition rates with a reasonable matching time.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
IRJET-A Review on Implementation of High Dimension Colour Transform in Domain...IRJET Journal
This document reviews algorithms for detecting salient regions in images using high dimensional color transforms. It summarizes several existing methods that use color contrast, frequency analysis, and superpixel segmentation. A key method discussed creates a saliency map by finding the optimal linear combination of color coefficients in a high dimensional color space. This allows more accurate detection of salient objects versus methods using only RGB color. The performance of this high dimensional color transform method is improved by also utilizing relative location and color contrast between superpixels as learned features.
The document describes a new image scaling algorithm based on an area pixel model that aims to achieve low complexity suitable for VLSI implementation. It presents an edge-oriented area-pixel scaling processor that uses an approximate technique to calculate pixel areas with 6-bit integers rather than floating point values. It also employs a simple edge catching technique to better preserve edges. The proposed 7-stage VLSI architecture was implemented using Verilog HDL and synthesized using a 0.18-micron process, achieving a processing rate of 200MHz with 10.4K gate counts. Experimental results showed it performs better than other lower complexity methods in terms of quality and speed.
SEGMENTATION AND CLASSIFICATION OF POINT CLOUDS FROM DENSE AERIAL IMAGE MATCHINGijma
This document summarizes a research paper that aimed to improve 3D point cloud segmentation through a hybrid approach using both object space and image space segmentation. The researchers used surface growing segmentation on 3D point clouds combined with spectral information from RGB and grayscale images to extract buildings, streets, and vegetation. Experiments on case studies showed that updating plane parameters and robust plane fitting improved building extraction, especially for low accuracy point clouds. Region growing in grayscale images also resulted in more realistic building roofs than using RGB images.
Extended hybrid region growing segmentation of point clouds with different re...csandit
In the recent years, 3D city reconstruction is one of the active researches in the field of
photogrammetry. The goal of this work is to improve and extend region growing based
segmentation in the X-Y-Z image in the form of 3D structured data with combination of spectral
information of RGB and grayscale image to extract building roofs, streets and vegetation. In
order to process 3D point clouds, hybrid segmentation is carried out in both object space and
image space. Our experiments on two case studies verify that updating plane parameters and
robust least squares plane fitting improves the results of building extraction especially in case
of low accurate point clouds. In addition, region growing in image space has been derived to
the fact that grayscale image is more flexible than RGB image and results in more realistic
building roofs.
Edge detection is one of the most powerful image analysis tools for enhancing and detecting edges. Indeed, identifying and localizing edges are a low level task in a variety of applications such as 3-D reconstruction, shape recognition, image compression, enhancement, and restoration. This paper introduces a new algorithm for detecting edges based on color space models. In this RGB image is taken as an input image and transforming the RGB image to color models such as YUV, YCbCr and XYZ. The edges have been detected for each component in color models separately and compared with the original image of that particular model. In order to measure the quality assessment between images, SSIM (Structural Similarity Index Method) and VIF (Visual Information Fidelity) has been calculated. The results have shown that XYZ color model is having high SSIM value and VIF value. In the previous papers, edge detection based on RGB color model has low SSIM and VIF values. So by converting the images into different color models shows a significant improvement in detection of edges. Keywords: Edge detection, Color models, SSIM, VIF.
Higher Order Feature Set For Underwater Noise ClassificationCSCJournals
The development of intelligent systems for classification of underwater noise sources has been a field of research interest for decades. Such systems include the extraction of features from the received signals, followed by the application of suitable classification algorithms. Most of the existing feature extraction methods rely on the classical power spectral methods, which may fail to provide information pertaining to the deviations from linearity and Gaussianity of stochastic processes. Hence, many recent research efforts focus on higher order spectral methods in order to prevail over such limitations. This paper makes use of bispectrum, which is a higher order spectrum of order three, in order to extract a set of robust features for the classification of underwater noise sources. An SVM classifier is used for evaluating the performance of the feature set.
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
This document summarizes a research paper that proposes a new image interpolation technique to reconstruct high-resolution images from low-resolution counterparts while preserving edge structures. The technique estimates each pixel to be interpolated in two orthogonal directions and fuses the estimates using linear minimum mean square error estimation. This adaptive fusion approach can better discriminate edge directions in the local window compared to interpolating in a single direction. The technique aims to improve on traditional linear interpolation methods by adapting to local image gradients to reduce artifacts while preserving sharp edges. A simplified version is also presented to reduce computational costs with minimal impact on performance. Experiments showed the new technique can better preserve edges and reduce artifacts compared to other methods.
A Solution to Land Area Calculation for Android Phone using GPS-Luwei YangLuwei Yang
This document proposes an Android application to calculate land area using GPS. It records a user's path using GPS as they walk around a land area. It then calculates the total land area using the trapezoid method, which breaks the irregular shape into smaller trapezoids. The Kalman filter is used to improve GPS accuracy and reduce errors, achieving an average error of 3.64% in tests. Key aspects include using Gauss-Kruger projection to convert GPS coordinates to plane coordinates before area calculation, and employing the trapezoid method and Kalman filtering to accurately calculate irregular land shapes and compensate for GPS errors, respectively.
This paper presents a geometric approach to the coordinatization of a measured space called the Map
Maker’s algorithm. The measured space is defined by a distance matrix for sites which are reordered and
mapped to points in a two-dimensional Euclidean space. The algorithm is tested on distance matrices
created from 2D random point sets and the resulting coordinatizations compared with the original point
sets for confirmation. Tolerance levels are set to deal with the cumulative numerical errors in the
processing of the algorithm. The final point sets are found to be the same apart from translations,
reflections and rotations as expected. The algorithm also serves as a method for projecting higher
dimensional data to 2D.
Node Failure Prevention by Using Energy Efficient Routing In Wireless Sensor ...IJTET Journal
The most necessary issue that has to be solved in coming up with an information transmission rule for
wireless unplanned networks is a way to save unplanned node energy whereas meeting the wants of applications
users because the unplanned nodes are battery restricted. Whereas satisfying the energy saving demand, it’s
conjointly necessary to realize the standard of service. Just in case of emergency work, it's necessary to deliver the
information on time. Achieving quality of service in is additionally necessary. So as to realize this demand, Power -
efficient Energy-Aware routing protocol for wireless unplanned networks is planned that saves the energy by
expeditiously choosing the energy economical path within the routing method. When supply finds route to
destination, it calculates α for every route. The worth α is predicated on largest minimum residual energy of the trail
and hop count of the trail. If a route has higher α, then that path is chosen for routing the information. The worth of α
are higher, if the most important of minimum residual energy of the trail is higher and also the range of hop count is
lower. Once the trail is chosen, knowledge is transferred on the trail. So as to extend the energy potency any
transmission power of the nodes is additionally adjusted supported the situation of their neighbour. If the neighbours
of a node are closely placed thereto node, then transmission vary of the node is diminished. Thus it's enough for the
node to own the transmission power to achieve the neighbour at intervals that vary. As a result transmission power
of the node is cut back that later on reduces the energy consumption of the node. Our planned work is simulated
through Network machine (NS-2). Existing AODV and Man-Min energy routing protocol conjointly simulated
through NS-2 for performance comparison. Packet Delivery quantitative relation, Energy Consumption and end-toend
delay.
Mitigating The Power Fluctuation Of PMSG Wind Turbine In A Microgrid By Optim...IJTET Journal
Abstract— The major problem of PMSG wind turbine are power fluctuation. And this problem is overcome by new optimization technique and circuit model of the Superconducting Magnetic Energy Storage (SMES) with Fault Current Limiter (FCL) in a micro grid. Normally, SMES-FCL circuit which contain superconducting coil. In case of without fault condition, SMES-FCL act as the SMES unit to mitigate the power fluctuation of PMSG. Under fault condition, the SC is automatically connected to the system and it can be used as FCL to reduce the fault current. Then, the voltage drop of PMSG and fault current unit will be mitigated. By the energy function method is used to determine the optimal problem. Finally, this MATLAB result shows the superior control effect compare to the conventional method.
Activity Recognition From IR Images Using Fuzzy Clustering TechniquesIJTET Journal
Infrared sensors ensures that activity recognition is possible in the day and night times. It is used especially for activity monitoring of older adults as falls are more prevalent at night than the day. This paper focus on an application of fuzzy set techniques and it is capable of accurately detecting several different activity states related to fall detection and fall risk assessment and it also includes sitting, standing and being on the floor to ensure that elderly residents gets the help they need quickly in case of emergencies. Fall detection and fall risk assessment is used for an aging in place facility for the elderly people. It describes the silhouette extraction process, the image features , and the fuzzy clustering technique.
Joint Optimization of The two Tier Femto cells and Macro cell Users OFDMA Net...IJTET Journal
We proposed a novel joint sub channel and resource allocation for the two-tier OFDMA network. The multi-cell OFDMA network not only has to control the interference to the users, but also has to coordinate the cross-tier interference. A resource allocation scheme for cross-channel Femto and Macro is proposed, aiming to maximize the capacity. We formulate this joint optimization for both uplink and downlink in OFDMA network will be considered. To efficiently solve this problem using dual decomposition and low complexity methods. The resulting schemes efficiently allocate the resource and data sharing in a distributed way. The simulation results show that the less interference and provide significant throughput.
Design of Real-time Self Establish Wireless Sensor For Dynamic NetworkIJTET Journal
Abstract— Wireless sensor network in the recent trend engaged with high speed responsive real time system. This type of real time system requires reliable and compatible sensor to work in an environment where the sensor is dynamic in nature. Sensor network is to design to perform a set of high level information processing tasks such as detection, tracking or classification. Application of sensor networks is wide ranging and can vary significantly in application requirements, modes of deployment, sensing modality, power supply. Dynamic configuring of wireless sensor involves timing constraints to configure the sensor or to switch an adaptive sensor when working node failure due to energy, data rate, packet loss and range of the sensor. So the network, with such dynamic nature needs a background sensor which is able to be switched when the active sensor has a problem and improper functioning due to the network deploy environment. The background sensor lies inactive inside the range of the active sensor; ensure that the sensor is about to die and make sure the last data transfer successful find delay time to switch. Fault tolerance is achieved by switching the background sensor with the active sensor, where the background sensor self establish themselves in the network and perform similar routing metrics and configure them self with the network as soon they are switched. Once, the actual sensor retained back to the active condition then the background sensor will go to inactive state during this switching process the sensor will not loss data packet.
Design of Rear wing for high performance cars and Simulation using Computatio...IJTET Journal
The performance of a sports car is not only limited to its engine power but also to aerodynamic properties of the car. By decreasing the drag force it is possible to reduce the engine power required to achieve same top speed thus decreasing the fuel requirement. The stability of a sports car is considerably important at high speed. The provision of a rear wing increases the downforce thus reducing the rear axle lift and provides increased traction. In this study an optimum rear wing is designed for the high performance car so as to decrease drag and increase downforce. The CAD designed baseline model with or without rear wing is being analyzed in computational fluid dynamics software. The lift and drag coefficient are calculated for all the design thus an optimum rear wing is designed for the considered baseline model.
Analysis of low pdp using SPST in bilateral filterIJTET Journal
A FPGA Implementation of a bilateral filter for image processing is given which does spatial averaging without smoothing edges. Kernel based processing is possible, which means that processing of the entire filter window at one pixel clock cycle. It is also supported by the arrangement of the input data into groups and applied a single clock cycle for a group of pixels. Based on these features, a technique called Spurious Power Suppression Technique (SPST) is implemented in Bilateral Filter to minimize Power Delay Product (PDP). SPST can also dramatically reduce the power by turn off its MSP (Most significant bit) without compromising the computational results to achieve the target parameters. Furthermore, an Original Glitch Diminishing technique is proposed to filter out useless switching power by asserting signals after the data transient period. The SPST can be expanded to a Fine-grain scheme in which the combinational circuits are divided into more than two parts. In Bilateral Filter a kernel of different size can be implemented using SPST which achieve good performance.
A Passive Lossless Soft-Switching Snubber for Telecom Power SuppliesIJTET Journal
At present the majority of power supplies or power converters use switch-mode technology. Higher switching frequencies allow reduction of the magnetic component sizes with PWM switching converters but cause higher switching losses and greater electro-magnetic interference. To reduce these switching losses active or passive soft-switching methods are used in various applications.This paper presents a passive lossless soft-switching snubber for telecom power supplies. Simulation results are given to demonstrate the validity and features of the snubber
ARM Based Climate Controlled Wearable JacketIJTET Journal
Thermo-electric (TE) technology is used in both electricity generation and air-conditioning. The Thermo-electric coolers(TEC) uses Peltier effect which converts the electrical energy applied from the ends of the Thermo-electric module into the temperature difference. The main objective of the work is to design a highly reliable and wearable jacket that controls extreme temperatures say working in thermal power plants, within the jacket. The extreme temperatures can be monitored using temperature sensors placed on both sides of the Thermo-electric cooler module and controlled using ARM LPC2148 Microcontroller. In Industries, this jacket provides a more practical and safer solutions for human working under extreme temperatures. Furthermore, this jacket can also be applied as a good warmer one for human beings working in cold regions(say Polar regions).
An Efficient System Of Electrocardiogram Data Acquisition And Analysis Using ...IJTET Journal
This document describes the development of a portable and cost-effective electrocardiogram (ECG) data acquisition and analysis system using LabVIEW. ECG signals are collected from patients using 3-lead ECG sensors and transmitted to a laptop via a National Instruments data acquisition card. LabVIEW software is used to monitor the ECG signal in real-time, record the data, and analyze it to diagnose cardiac issues like tachycardia, bradycardia, and myocardial infarction. The system aims to help diagnose heart-related emergencies in crowded areas and transmit patient data to hospitals prior to ambulance arrival to improve treatment.
Comparative Study of Ant Colony Optimization And Gang SchedulingIJTET Journal
Abstract— Ant Colony Optimization (ACO) is a well known and rapidly evolving meta-heuristic technique. All optimization problems have already taken advantage of the ACO technique while countless others are on their way. Ant Colony Optimization (ACO) has been used as an effective algorithm in solving the scheduling problem in grid computing. Whereas gang scheduling is a scheduling algorithm that is used to schedule the parallel systems and schedules related threads or processes to run simultaneously on different processors. The threads that are scheduled are belonging to the same process, but they from different processes in some cases, for example when the processes have a producer-consumer relationship, when all processes come from the same MPI program.
Classification of EEG Signal for Epileptic Seizure DetectionusingEMD and ELMIJTET Journal
Abstract—This paper proposes the classification of EEG signal for epilepsy diagnosis. Epilepsy is a neurological disorder which occurs due to synchronous neuronal activity in brain. Empirical Mode Decomposition (EMD), Extreme Learning Machine (ELM) are the techniquedelivered in the proposed method.Input EEG signal, which is available in online as Bonn Database is decomposed into five Intrinsic Mode Functions (IMFs) using EMD.Higher Order Statistical moments such as Variance, Skewness and Kurtosis are drawn out as features from the decomposed signals. Extreme Learning Machine is used as a classifier to classify the EEG signals with the taken features, under various categories that include healthy and ictal, interictal and ictal, Non seizure and seizure, healthy, interictal and ictal. The proposed method gives 100%accuracy, 100%sensitivity in discriminating interictal and ictal, non seizure and seizure, healthy and ictal, healthy, interictal and ictal, 100% specificity in classifying healthy and ictal, interictal and ictal and 100% and 99%accuracy in case of discriminating interictal and ictal, non seizure and seizure.
Auxetic materials are known for their peculiar behavior unlike conventional materials the thickness of these materials increase under the action of axial pull. In this paper we are going to study the properties of Auxetic materials , their occurrence in nature, methods of synthesis, applications. Our ideas of other possibilities to make use of these materials. The current status of research into auxetic (negative Poisson's ratio) materials is reviewed, with particular focus on those aspects of relevance to aerospace engineering. Developments in the modelling, design, manufacturing, testing, and potential applications of auxetic cellular solids, polymers, composites, and sensor/actuator devices are presented. Auxetic cellular solids in the forms of honeycombs and foams are reviewed in terms of their potential in a diverse range of applications, including as core materials in curved sandwich panel Composite components, random applications, directional pass band filters, adaptive and deployable structures,MEMS devices, filters and sieves, seat cushion material, energy absorption components, viscoelastic, damping materials and fastening devices. In this paper we are going to put forward our proposals of using auxetic materials in helmet, seat of a bike, car bumpers.
An Efficient Data Transmission for Cluster based Wireless Sensor Networks usi...IJTET Journal
In this paper Identity based digital Signature and Identity based online offline algorithm for the cluster based wireless sensor networks is used. Identity based digital signature computes the digital signature signing process. Identity based online offline algorithm reduces the complexity of computational overhead in cluster head. This project reduces the overhead of the cluster head for efficient transmission. The method for efficient data transmission using Identity based digital signature is also implemented for minimizing end-to-end delay using network simulator. The graphics analysis toolbox and awk scripts is used to process the data from trace files.
Surveillance Robot for Military Application Using ARMIJTET Journal
In the modern day robotics development in many field as too that enrich in military applications also as per that this robot SURVEILLANCE MONITORING ROBOT FOR MILITARY APPLCATION USING ARM monitor the defense area that is in our country borders. It is an forest area and every time commanders were not available in same area they move over different places at that time terrorist can easily enter into our nation. This robot perform main role there that PIR sensor in the robot will send the intimation and danger warning to the control room that unauthorized person entering that time we alert our soldiers to move to that place this operation were control using ARM7 controller. Another important component GPS exactly say which position the robot is now monitoring then it will be easy to soldiers to survey the area soon.And for communicating between control room and robot we are using ZIGBEE.Another one sensor TEMPERATURE SENSOR LM35 is used to monitor temperature in that area that is used to intimate us what is the temperature level in that area if any BOMB BLAST OR FIRE ACCIDENT in that area.
Raspberry Pi Based Client-Server Synchronization Using GPRSIJTET Journal
A low cost Internet-based attendance record embedded system for students which uses wireless technology to
transfer data between the client and server is designed. The proposed system consist of a Raspberry Pi which acts as a
client which stores the details of the students in the database by using user login system using web. When the user logs
into the database the data is sent through GPRS to the server machine which maintains the records of the employees and
the attendance is updated in the server database. The GPRS module provides a bidirectional real-time data transfer
between the client and server. This system can be implemented to any real time application so as to retrieve information
from a data source of the client system and send a file to the remote server through GPRS. The main aim is to avoid the
limitations in Ethernet connection and design a low cost and efficient attendance record system where the data is
transferred in a secure way from the client database and updated in the server database using GPRS technology
Space Vector of Three Phase Three level Neutral Point Clamped Quasi Z Source ...IJTET Journal
Space vector of three phase three level neutral point clamped quasi z source inverter is proposed in this paper. Space vector modulation is the pulse width modulation consists of number of switching states. Space vector pulse width modulation technique utilizes 15% more power from DC source. Harmonics are reduced by the presence of switching states. Quasi Z-source inverter is advanced topologies which performs both boost and buck operation of a converter. The proposed inverter obtains continuous input current and the boost converter is not needed. So, maximum voltage can be obtained in the load and system complexity is reduced. Maximum power can be obtained from the solar panel by using MPPT. The implementation of MPPT is to operate a PV array under constant voltage and power reference to modify the duty cycle of the inverter.The simulation of proposed topology is done in MATLAB/SIMULINK software.
Nowadays digital cameras are equipped with a
single sensor (CCD/CMOS), to reduce the size and cost of the
camera. The color filter array (CFA) is used to cover the sensor
and it consist of three primary colors such as red, green and blue
and it samples only one color component at each pixel location.
The process of estimating the other two missing color components
at each pixel location is known as demosaicing. The proposed
algorithm uses the directional color difference and multiscale
gradient method for green plane interpolation, this type of
interpolation method is used to reduce the artifacts and improve
the image quality. The red and blue plane are interpolated using
the estimated green plane, the bayer pattern is used for the
interpolation technique. The performance of the image is
measured using the CPSNR value
Novel algorithm for color image demosaikcing using laplacian maskeSAT Journals
Abstract Images in any digital camera is formed with the help of a monochrome sensor, which can be either a charge-coupled device(CCD) or complementary metal oxide semi-conductor(CMOS). Interpolation is the base for any demsoaicking process. The input for interpolation is the output of the Bayer Color Filter Array which is a mosaic like lattice structure. Bayer Color Filter Array samples the channel information of R,G and B values separately assigning only one channel component per pixel. To generate a complete color image, three channel values are required. In order to find those missing samples we use interpolation. It is a technique of estimating the missing values from the discrete observed samples scattered over the space. Thus Demosaicking or De-bayering is an algorithm of finding missing values from the mosaic patterned output of the Bayer CFA. Interpolation algorithm results in few artifacts such as zippering effect in the edges. This paper introduces an algorithm for demosaicking which outperforms the existing demosaciking algorithms. The main aim of this algorithm is to accurately estimate the Green component. The standard mechanism to compare the performance is PSNR(Peak Signal to Noise Ratio) and the image dataset for comparison was Kodak image dataset. The algorithm was implemented using Matlab2009B version. Keywords: Demosaicking, Interpolation, Bayer CFA, Laplacian Mask, Correlation.
This document summarizes several proposed optimized color transforms for improving the performance of image demosaicing algorithms. It begins with describing a basic sequential demosaicing algorithm that first interpolates the green color component and then reconstructs the red and blue components based on differences from green. The document then proposes alternative color transforms based on optimizing for: 1) energy compactness and non-singularity of the color components, 2) smoothness of the color components by minimizing their high-frequency energy in both the wavelet and Fourier domains, and 3) relative energy in the Fourier domain. Equations for calculating the optimal coefficients for these proposed color transforms are provided.
Effective Demosaicking for Bayer Color Filter Arrays with Directional Filteri...IRJET Journal
This document presents a novel approach for demosaicking, which is the process of reconstructing a full-color image from the raw data of a single-chip digital camera sensor covered with a color filter array (CFA). The proposed approach improves upon existing directional filtering and weighting techniques by analyzing their advantages and limitations. It introduces a new estimation scheme to reconstruct color components. Experimental results show the proposed method outperforms six state-of-the-art demosaicking methods in terms of subjective and objective quality measures.
IRJET- Effective Demosaicking for Bayer Color Filter Arrays with Direction...IRJET Journal
This document presents a novel demosaicking approach to restore full-color images from single-sensor digital camera data. The approach improves existing directional filtering and weighting techniques to reduce common demosaicking artifacts. It analyzes the advantages and limitations of prior methods and proposes a new estimation scheme. The method interpolates the green color plane using directional filtering or weighted averaging depending on edge strength. It then interpolates the red and blue planes using weighted averaging on color difference planes. Experimental results showed the proposed approach outperformed six state-of-the-art demosaicking methods in subjective and objective quality measures.
IRJET- A Review on Plant Disease Detection using Image ProcessingIRJET Journal
This document summarizes a research paper on detecting plant diseases from images using digital image processing techniques. The main steps discussed are: 1) Acquiring digital images of plant leaves, 2) Pre-processing the images by cropping, converting to grayscale, and enhancing, 3) Segmenting the images using k-means clustering to identify infected regions, 4) Extracting color, texture, and shape features from the segmented images, and 5) Classifying the images using a support vector machine to identify the type of disease. The proposed method was tested on images of citrus leaves to detect different diseases and future work aims to improve classification accuracy for other plant species.
An Efficient Filtering Technique for Denoising Colour Images IJECEIAES
This document presents an efficient filtering technique for denoising color images. The technique uses gradient-based color interpolation to estimate missing color values while also removing noise. It filters noise based on calculating first- and second-order gradients to identify noisy pixels versus edge pixels. The red color component is used for interpolation to optimize computations. Testing on a sample image shows the technique improves signal-to-noise ratio from 17.09 to 33.16 by effectively removing noise while retaining image details. The method has potential for applications in defense and civilian imaging systems by enhancing image quality.
ALPHA-ROOTING COLOR IMAGE ENHANCEMENT METHOD BY TWO-SIDE 2-D QUATERNION DISCR...ijaceeejournal
In this paper a quaternion approach of enhancement method is proposed in which color in the image is
considered as a single entity. This new method is referred as the alpha-rooting method of color image
enhancement by the two-dimensional quaternion discrete Fourier transform (2-D QDFT) followed by a
spatial transformation. The results of the proposed color image enhancement method are compared with its
counterpart channel-by-channel enhancement algorithm by the 2-D DFT. The image enhancements are
quantified to the enhancement measure that is based on visual perception referred as the color
enhancement measure estimation (CEME). The preliminary experiment results show t
Correction of Saturated Regions in RGB Color Space ijcga
In a digital image, color representation of a digital image sensor is limited to a narrow dynamic range. Especially, when extremely bright light is captured, the original color of a scene is saturated to the maximum value, up to which a digital image sensor can represent the color. This paper proposes an algorithm that corrects the color in a saturated region, where the original color is distorted and lost. For natural correction, i.e., to minimize the artifacts near the boundary of a saturated region, the proposed method uses the weighted sum of color value(s) in the saturated color channel(s) of neighborhood of saturated regions. In determining the weight of each pixel, saturation, hue, and color values are used with the certainty map. Using the certainty map, the proposed method can reliably distinguish the unsaturated and already desaturated neighboring pixels from the remaining pixels. Then, the proposed correction method computes the weight function using saturation, hue, and color values. Therefore, the proposed algorithm can get reliable corrected colors. Comparison of experimental results of the proposed and existing correction methods shows the effectiveness of the proposed saturated region correction method in the view of natural color restoration.
Correction of Saturated Regions in RGB Color Space ijcga
In a digital image, color representation of a digital image sensor is limited to a narrow dynamic range.
Especially, when extremely bright light is captured, the original color of a scene is saturated to the
maximum value, up to which a digital image sensor can represent the color. This paper proposes an
algorithm that corrects the color in a saturated region, where the original color is distorted and lost. For
natural correction, i.e., to minimize the artifacts near the boundary of a saturated region, the proposed
method uses the weighted sum of color value(s) in the saturated color channel(s) of neighborhood of
saturated regions. In determining the weight of each pixel, saturation, hue, and color values are used with
the certainty map. Using the certainty map, the proposed method can reliably distinguish the unsaturated
and already desaturated neighboring pixels from the remaining pixels. Then, the proposed correction
method computes the weight function using saturation, hue, and color values. Therefore, the proposed
algorithm can get reliable corrected colors. Comparison of experimental results of the proposed and
existing correction methods shows the effectiveness of the proposed saturated region correction method in
the view of natural color restoration.
A lossless color image compression using an improved reversible color transfo...eSAT Journals
Abstract In case of the conventional lossless color image compression methods, the pixels are interleaved from each color component, and they are predicted and finally encoded. In this paper, we propose a lossless color image compression method using hierarchical prediction of chrominance channel pixels and encoded with modified Huffman coding. An input image is chosen and the R, G and B color channel is transform into YCuCv color space using an improved reversible color transform. After that a conventional lossless image coder like CALIC is used to compress the luminance channel Y. The chrominance channel Cu and Cv are encoded with hierarchical decomposition and directional prediction. The effective context modeling for prediction residual is adopted finally. It is seen from the experimental result the proposed method improves the compression performance than the existing method. Keywords: Lossless color image compression, hierarchical prediction, reversible color transform, modified Huffman coding.
Colorization of Gray Scale Images in YCbCr Color Space Using Texture Extract...IOSR Journals
This document describes a technique for colorizing grayscale images by matching texture features between the grayscale image and windows in a color reference image. The technique works by first converting the images to the YCbCr color space, which has decorrelated color channels that allow color to be transferred without artifacts. Texture features like energy, entropy, homogeneity, contrast and correlation are then extracted from windows in the color image and compared to the grayscale image to find the best matching window. The mean and standard deviation of color values in the matching window are then imposed on pixels in the grayscale image to transfer color, while retaining the original luminance values. This process is repeated on small windows across the image to colorize the entire grayscale input.
This document discusses GPU-based implementations of bilateral filtering for images. Bilateral filtering smooths images while preserving edges by combining pixel values based on both geometric closeness and photometric similarity. It can be applied to color images in a way that is tuned to human color perception. A naïve bilateral filtering implementation iterates over all pixels, but it is well-suited for parallel GPU implementations due to its iterative and local nature. The document provides mathematical definitions of domain filtering, range filtering, and bilateral filtering, and notes that bilateral filtering combines the benefits of both by enforcing both geometric and photometric locality. It describes using Gaussian functions to implement the filters and discusses parameters for controlling the degree of blurring and edge preservation.
The document is a project report on image contrast enhancement using histogram equalization and cubic spline interpolation. It discusses image processing and contrast enhancement techniques. It provides details on color models like RGB, HSV, and LAB. It describes converting between color spaces like RGB to HSV and RGB to LAB. It outlines histogram equalization and cubic spline interpolation for contrast enhancement in the spatial domain. The report was conducted as a training project at the Defence Terrain Research Laboratory in India.
Modified Alpha-Rooting Color Image Enhancement Method on the Two Side 2-D Qua...mathsjournal
Color in an image is resolved to 3 or 4 color components and 2-Dimages of these components are stored in separate channels. Most of the color image enhancement algorithms are applied channel-by-channel on each image. But such a system of color image processing is not processing the original color. When a color image is represented as a quaternion image, processing is done in original colors. This paper proposes an implementation of the quaternion approach of enhancement algorithm for enhancing color images and is referred as the modified alpha-rooting by the two-dimensional quaternion discrete Fourier transform (2-D QDFT). Enhancement results of this proposed method are compared with the channel-by-channel image enhancement by the 2-D DFT. Enhancements in color images are quantitatively measured by the color enhancement measure estimation (CEME), which allows for selecting optimum parameters for processing by thegenetic algorithm. Enhancement of color images by the quaternion based method allows for obtaining images which are closer to the genuine representation of the real original color.
MODIFIED ALPHA-ROOTING COLOR IMAGE ENHANCEMENT METHOD ON THE TWO-SIDE 2-DQUAT...mathsjournal
Color in an image is resolved to 3 or 4 color components and 2-Dimages of these components are stored in
separate channels. Most of the color image enhancement algorithms are applied channel-by-channel on
each image. But such a system of color image processing is not processing the original color. When a color
image is represented as a quaternion image, processing is done in original colors. This paper proposes an
implementation of the quaternion approach of enhancement algorithm for enhancing color images and is
referred as the modified alpha-rooting by the two-dimensional quaternion discrete Fourier transform (2-D
QDFT). Enhancement results of this proposed method are compared with the channel-by-channel image
enhancement by the 2-D DFT. Enhancements in color images are quantitatively measured by the color
enhancement measure estimation (CEME), which allows for selecting optimum parameters for processing
by thegenetic algorithm. Enhancement of color images by the quaternion based method allows for
obtaining images which are closer to the genuine representation of the real original color.
MODIFIED ALPHA-ROOTING COLOR IMAGE ENHANCEMENT METHOD ON THE TWO-SIDE 2-DQUAT...mathsjournal
Color in an image is resolved to 3 or 4 color components and 2-Dimages of these components are stored in separate channels. Most of the color image enhancement algorithms are applied channel-by-channel on each image. But such a system of color image processing is not processing the original color. When a color image is represented as a quaternion image, processing is done in original colors. This paper proposes an implementation of the quaternion approach of enhancement algorithm for enhancing color images and is referred as the modified alpha-rooting by the two-dimensional quaternion discrete Fourier transform (2-D QDFT). Enhancement results of this proposed method are compared with the channel-by-channel image
enhancement by the 2-D DFT. Enhancements in color images are quantitatively measured by the color enhancement measure estimation (CEME), which allows for selecting optimum parameters for processing by thegenetic algorithm. Enhancement of color images by the quaternion based method allows for obtaining images which are closer to the genuine representation of the real original color.
MODIFIED ALPHA-ROOTING COLOR IMAGE ENHANCEMENT METHOD ON THE TWO-SIDE 2-DQUAT...mathsjournal
Color in an image is resolved to 3 or 4 color components and 2-Dimages of these components are stored in separate channels. Most of the color image enhancement algorithms are applied channel-by-channel on each image. But such a system of color image processing is not processing the original color. When a color image is represented as a quaternion image, processing is done in original colors. This paper proposes an implementation of the quaternion approach of enhancement algorithm for enhancing color images and is referred as the modified alpha-rooting by the two-dimensional quaternion discrete Fourier transform (2-D QDFT). Enhancement results of this proposed method are compared with the channel-by-channel image enhancement by the 2-D DFT. Enhancements in color images are quantitatively measured by the color enhancement measure estimation (CEME), which allows for selecting optimum parameters for processing by thegenetic algorithm. Enhancement of color images by the quaternion based method allows for obtaining images which are closer to the genuine representation of the real original color.
MODIFIED ALPHA-ROOTING COLOR IMAGE ENHANCEMENT METHOD ON THE TWO-SIDE 2-DQUAT...mathsjournal
Color in an image is resolved to 3 or 4 color components and 2-Dimages of these components are stored in
separate channels. Most of the color image enhancement algorithms are applied channel-by-channel on
each image. But such a system of color image processing is not processing the original color. When a color
image is represented as a quaternion image, processing is done in original colors. This paper proposes an
implementation of the quaternion approach of enhancement algorithm for enhancing color images and is
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image is represented as a quaternion image, processing is done in original colors. This paper proposes an
implementation of the quaternion approach of enhancement algorithm for enhancing color images and is
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QDFT). Enhancement results of this proposed method are compared with the channel-by-channel image
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enhancement measure estimation (CEME), which allows for selecting optimum parameters for processing
by thegenetic algorithm. Enhancement of color images by the quaternion based method allows for
obtaining images which are closer to the genuine representation of the real original color.
Similar to Multiscale Gradient Based – Directional CFA Interpolation with Refinement (20)
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2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
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Multiscale Gradient Based – Directional CFA Interpolation with Refinement
1. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 1 – APRIL 2015 - ISSN: 2349 - 9303
90
Multiscale Gradient Based – Directional CFA
Interpolation with Refinement
Aarthy Poornila.A1
1
Mepco Schlenk Engineering
College,
ECE Department
aarthypoornila@gmail.com
R. Mercy Kingsta2
Assistant Professor
3
Mepco Schlenk Engineering College,
ECE Department
m.kingsta@gmail.com
Abstract—Single sensor digital cameras capture only one color value for every pixel location. The process of
reconstructing a full color image from these incomplete color samples output from an image sensor overlaid with a color
filter array (CFA) is called demosaicing or Color Filter Array (CFA) interpolation. The most commonly used CFA
configuration is the Bayer filter. The proposed demosaicing method makes use of multiscale color gradients to adaptively
combine color difference estimates from horizontal and vertical directions and determine the contribution of each direction
to the green channel interpolation. This method does not require any thresholds and is non iterative. The red and blue
channels are then refined using structural approximation.
Index Terms — Multiscale color gradients, Color Filter Array (CFA) interpolation, demosaicing, directional interpolation.
—————————— ——————————
1. INTRODUCTION
emosaicing algorithm is a digital image process used to
reconstruct a full color image from the incomplete color
samples obtained from an image sensor overlaid with a color filter
array (CFA). Also known as CFA interpolation or color
reconstruction [21] .The reconstructed image is typically accurate in
uniform-colored areas, but has a loss of resolution and has edge
artifacts in non uniform-colored areas.
A color filter array is a mosaic of color filters in front of
the image sensor. The most commonly used CFA configuration is
the Bayer filter shown in Fig 1.1. This has alternating red (R) and
green (G) filters for odd rows and alternating green (G) and blue (B)
filters for even rows. There are twice as many green filters as red or
blue ones, exploiting the human eye's higher sensitivity to green
light.
Figure 1.1: Bayer mosaic of color image
1.1 Existing Algorithms
Nearest neighbor interpolation simply copies an adjacent pixel of
the same color channel (2x2 neighborhood). It is unsuitable for any
application where quality matters, but can be used for generating
previews with given limited computational resources [25].In
bilinear interpolation, the red value of a non-red pixel is computed
as the average of the two or four adjacent red pixels. The blue and
green values are also computed in a similar way. Bilinear
interpolation generates significant artifacts, especially across edges
and other high-frequency content, as it doesn`t take into account the
correlation between the RGB values [22].
Cubic interpolation takes into account more neighbors
than in algorithm no. [22] (e.g., 7x7 neighborhood). Lower weight is
given to pixels which are far from the current pixel.Gradient-
corrected bilinear interpolation assumes that in a
luminance/chrominance decomposition, the chrominance
components don`t vary much across pixels. It exploits the inter-
channel correlations between the different color channels and uses
the gradients among one color channel, to correct the bilinearly
interpolated value [23].
Smooth hue transition interpolation assumes that hue is
smoothly changing across an object’s surface; simple equations for
the missing colours can be obtained by using the ratios between the
known colours and the interpolated green values at each pixel [22].
Problem can occur when the green value is 0, so some simple
normalization methods are proposed [24].In order to prevent flaws
when estimating colours on or around edges, pattern recognition
interpolation [3] describes a way to classify and interpolate three
different patterns (edge, corner and strip) in the green color plane
that are shown in Fig 1.2. The first step in this procedure is to find
the average of the four neighboring green pixels, and classify the
neighbors as either high or low in comparison to this average.
.
D
2. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 1 – APRIL 2015 - ISSN: 2349 - 9303
91
Figure 1.2: (a) is a high edge pattern, (b) is a low edge pattern, (c) is a
corner pattern, and (d) is a stripe pattern.
Adaptive color plane interpolation assumes that the color
planes are perfectly correlated in small enough neighborhoods [25].
That is, in a small enough neighborhood, the equations.
G = B + k
G = R + j
are true for constants k, j.
In order to expand the edge detection power
of the adaptive color plane method, it is prudent to consider more
than two directions (i.e., not only the horizontal and vertical
directions). Thus directionally weighted gradient based
interpolation uses information from 4 directions (N, S, W, and E as
shown in Figure1.3)
Figure 1.3: Neighborhood of B pixel
A weight is assigned for each direction, using the known
information about the differences between B and G value [25].
2. PROPOSED SYSTEM DESIGN
2.1. System Description
The first step of the algorithm is to get initial directional
color channel estimates. The quality can be improved by applying
the interpolation over color differences using the advantages of
correlation between the color channels. Now every pixel location
has a true color channel value and two directional estimates. By
taking their difference, the directional color difference estimated.
The next step of the algorithm is to reconstruct the green
image along horizontal and vertical directions. Once the missing
green component is interpolated, the same process is performed for
estimating the next missing green component in a raster scan
manner. After interpolating all missing green components of the
image, the missing red and blue components at green CFA sampling
positions are estimated. Next, the directional color difference
estimates are combined from different directions.
The directional CFA interpolation method is based on
multi scale color gradients. Gradients are useful for extracting
directional data from digital images. In this method, the horizontal
and vertical color difference estimates are blended based on the
ratio of the total absolute values of vertical and horizontal color
difference gradients over a local window. For red & green rows and
columns in the input mosaic image, the directional estimates for the
missing red and green pixel values are estimated by initial
directional color channel estimates.
The color difference gradients calculated are used to find
weights for each direction. In order to avoid repetitive weight
calculations, the directional weights are reused.
Then the artifacts are removed and red and blue channels
are refined by the Structural Approximation method. The modules
of the proposed system framework are illustrated in Fig 2.1.
Fig 2.1 System Framework
2.1.1. Initial Directional Color Channel Estimation
To obtain a full color image, various demosaicing
algorithms can be used to interpolate a set of complete red, green,
and blue values for each point. The directional estimates for the
missing red and green pixel values, for red and green rows and
columns in the input mosaic image, are calculated.
The directional estimates for the missing blue and green
pixel values, for blue and green rows and columns in the input
mosaic image are calculated. Then horizontal and vertical color
channel estimates are calculated for finding directional color
channel estimates.
The directional color channel estimates for the missing
green pixel values are,
𝑔 𝐻
𝑖, 𝑗 =
𝐺 𝑖, 𝑗 − 1 + 𝐺 𝑖, 𝑗 + 1
2
+
2. 𝑅 𝑖, 𝑗 − 𝑅 𝑖, 𝑗 − 2 − 𝑅 𝑖, 𝑗 + 2
4
(1)
𝑔 𝑉
𝑖, 𝑗 =
𝐺 𝑖 − 1, 𝑗 + 𝐺(𝑖 + 1, 𝑗)
2
+
2. 𝑅 𝑖, 𝑗 − 𝑅 𝑖 − 2, 𝑗 − 𝑅(𝑖 + 2, 𝑗)
4
(2)
3. INTERNATIONAL JOURNAL FOR TRENDS IN ENGINEERING & TECHNOLOGY
VOLUME 4 ISSUE 1 – APRIL 2015 - ISSN: 2349 - 9303
92
Here,
𝑔 𝐻
𝑖, 𝑗 - Horizontal green color channel estimation at red
pixel
𝑔 𝑉
𝑖, 𝑗 - Vertical green color channel estimation at red
pixel
The color channel estimates are calculated from the Bayer
pattern. Here H and V denotes horizontal and vertical directions and
(i,j) denotes the pixel location.
2.1.2. Directional Color Difference Estimation
The quality can be improved by applying the interpolation
over color differences to take advantage of the correlation between
the color channels. This is an important technique employed in the
reconstruction of full color images, obtained by interpolation along
horizontal and vertical direction. Every pixel coordinate has a true
color channel value and two directional estimates. By taking their
difference directional color difference estimated.
Cg,r
H
i,j =
gH
i,j -R i,j , if G is interpolated
G i,j -rH
i,j , if R is interpolated
(3)
Cg,r
V
i,j =
gV
i,j -R i,j , if G is interpolated
G i,j -rV
i,j , if R is interpolated
(4)
𝐶𝑔,𝑟
𝐻
𝑖, 𝑗 , 𝐶𝑔,𝑟
𝑉
𝑖, 𝑗 are the horizontal and vertical difference
estimates between green and red channels.
2.1.3. Multiscale Gradient Calculation
A full-color image is usually composed of three color
planes. Three separate sensors are required for a camera to measure
an image. To reduce the cost, many cameras use a single sensor
overlaid with a color filter array. The most commonly used CFA
nowadays is the Bayer CFA. In a single sensor digital camera, only
one color is measured at each pixel and the other two missing color
values are estimated. This estimation process is known as color
demosaicing.
The Bayer pattern is comprised of blue and green and red
and green rows and columns as shown in Fig 2.2. To obtain a full-
color image, various demosaicing algorithms can be used to
interpolate a set of complete red, green, and blue values for each
point.For red and green rows and columns in the input mosaic
image, the directional estimates for the missing red and green pixel
values are calculated
.
Fig 2.2 Bayer pattern
The quality can be improved by applying the interpolation
over color differences to take advantage of the correlation between
the color channels. This is an important technique employs the
reconstruction of full color images, obtained by interpolation along
horizontal and vertical direction. For every pixel coordinate has a
true color channel value and two directional estimates.
The multi scale gradient equation determine the difference
between the available color channel values one pixel (instead of two
pixels) away from the target pixel, then do the same operation in
terms of the other channel by using its closest samples, and then
take the difference between these two as shown in Fig 2.3. Observe
that the first part of this equation is the green channel gradient, and
the second part is the red channel gradient at twice the scale
normalized by the distance between their operands.
Fig 2.3: Multiscale Gradient Equation
The Multiscale gradient equations for red and green rows and
column values are,
MH
i,j =
G i,j+1 -G i,j-1
2
-
R i,j+2 -R i,j-2
N1
+
G i,j+3 -G i,j-3
N2
-
R i,j+4 -R i,j-4
N3
(5)
MV
i,j =
G i+1,j -G i-1,j
2
-
R i+2,j -R i-2,j
N1
+
G i+3,j -G i-3,j
N2
-
R i+4,j -R i-4,j
N3
(6)
Where 𝑀 𝐻
𝑖, 𝑗 , 𝑀 𝑉
𝑖, 𝑗 denotes the multiscale gradient
equation at each pixel coordinates in horizontal and vertical
direction and N denotes Normalizers.The normalizer values are
N1=2, N2=4, N3=6
The color difference gradient is calculated by taking the
difference between the available color channel values that are two
pixels away from the target pixel. The same operation is done for
other color channels by using simple averaging, and then finding the
difference between these two operations
2.1.4. Initial Green Channel Interpolation
The next step of the algorithm is to reconstruct the green
image along horizontal and vertical directions. Initial green channel
interpolation section concentrates on estimating missing green
pixels from known green and red pixel values using the green-red
row of Bayer pattern. The same technique is used in estimating
missing green pixels from known green and blue pixels. For this,
directional color difference estimates around every green pixel to be
interpolated has to be estimated. Multiscale gradient a smaller scale
is more desirable because it allows the local color dynamics to be
captured at a better resolution. The available color channels are
replaced at this scale, but still performing the same operations. The
interpolated green channel is
δg,r i,j =
wV.f.Cg,r
V
i-1:i+1,j +wH.Cg,r
H
i,j-1:j+1 .f'
wC
(7)
Here
𝑤 𝐶 = 𝑤 𝑉 + 𝑤 𝐻
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f = [1/4 2/4 1/4]
Where 𝛿𝑔,𝑟 𝑖, 𝑗 indicates initial green channel interpolation at red
pixel locations.
2.1.5. Green Channel Update
After interpolating all missing green components of the
image, the missing red and blue components at green CFA sampling
positions are estimated. After the directional color difference
estimates are combined as explained in the previous section, the
green channel can be directly calculated and then the other channels
are completed. However, it is possible to improve the green channel
results by updating the initial color difference estimates. Consider
the closest four neighbors to the target pixel with each one having
its own weight.
𝛾𝑔,𝑟 𝑖, 𝑗 = 𝛿𝑔,𝑟 𝑖, 𝑗 . (1 − 𝑤
+ 𝑤 𝑁. 𝛿𝑔,𝑟 𝑖 − 2, 𝑗
+ 𝑤𝑆. 𝛿𝑔,𝑟 𝑖 + 2, 𝑗 +𝑤 𝐸. 𝛿𝑔,𝑟 𝑖, 𝑗 − 2
+ 𝑤 𝑁. 𝛿𝑔,𝑟 𝑖, 𝑗 + 2 . 𝑤
/𝑤 𝑇 (8)
Here the four neighbors of the target pixel calculated as
north, south, east and west directions. The weights (𝑤 𝑁, 𝑤𝑆, 𝑤 𝐸, 𝑤 𝑊)
are calculated by finding the total multiscale color gradients over a
local window. Once the missing green component is interpolated,
the same process is performed for estimating the next missing green
component in a raster scan manner. Once the color difference
estimate is finalized, we add it to the available target pixel to obtain
the estimated green channel value.
𝐺′ 𝑖,𝑗
= 𝛾𝑔,𝑟 𝑖, 𝑗 + 𝑅 𝑖, 𝑗 (9)
𝐺′ 𝑖, 𝑗 = 𝛾𝑔,𝑟 𝑖, 𝑗 + 𝐵(𝑖, 𝑗) (10)
2.1.6. Red and Blue Channel Interpolation
After the green channel has been reconstructed, interpolate
the red and blue components. The most common approach for red
and blue estimation consists of interpolation of the color differences
R-G, B-G instead of R and G directly. Finally, the missing blue
(red) components at the red (blue) sampling positions are
interpolated. For red and blue channel interpolation, first complete
the missing diagonal samples i.e. red pixel values at blue locations
and blue pixel values at red locations. These pixels are interpolated
using the 7 by 7 filter proposed.
Referring to the estimation of the red component (the same
strategy is applied for the blue one), thus all the green positions are
interpolated. Therefore, we choose to perform an interpolation using
the estimated red samples in the green location.
R'
i,j =G'
i,j -γg,r
i-3:i+3,j-3:j+3 X Prb (11)
B'
i,j =G'
i,j -γg,b
i-3:i+3,j-3:j+3 X Prb (12)
With the completion of red and blue pixel values at green
coordinates the full color image is to be generated.
2.1.7. Red and Blue Channel Refinement
The final step of the proposed method is to refine the
interpolated red and blue values. The equations for doing such
refinements by using Structural Approximation method [11] are
given below.
Let Q (k, l) be either red or blue sample as shown in Fig 2.4. Let
D (k, l) = G (k, l) – Q (k, l). (13)
Fig 2.4 Reference Bayer pattern
.
Here, G is a green sample, and P and Q represent either
red or blue sample respectively. If P is red, then Q is blue, and vice
versa.
𝑄 𝑖 − 1, 𝑗 = 𝐺 𝑖 − 1, 𝑗 −
𝐷 𝑖 − 1, 𝑗 − 1 + 𝐷 𝑖 − 1, 𝑗 + 1
2
𝑄 𝑖, 𝑗 − 1 = 𝐺 𝑖, 𝑗 − 1 −
𝐷 𝑖 − 1, 𝑗 − 1 + 𝐷 𝑖 + 1, 𝑗 − 1
2
𝑄 𝑖 + 1, 𝑗 = 𝐺 𝑖 + 1, 𝑗 −
𝐷 𝑖 + 1, 𝑗 − 1 + 𝐷 𝑖 + 1, 𝑗 + 1
2
𝑄 𝑖, 𝑗 + 1 = 𝐺 𝑖, 𝑗 + 1 −
𝐷 𝑖 + 1, 𝑗 − 1 + 𝐷 𝑖 + 1, 𝑗 + 1
2
The final interpolation after the above refinements is given by the
following equation,
Q i,j =G i,j -
D i-1,j +D i,j-1 +D i+1,j +D i,j+1
4
(14)
. The end of this equation can be seen that the proposed method
produce superior image quality than other demosaicing algorithms
2.2. Special Features
This method produces better results in terms of image
quality. It does not require any thresholds as it does not make any
hard decisions. It is non iterative. Features of gradients at different
scales are used. This is applied in digital camera.
3. RESULTS
A set of twenty four images from Kodak test set shown in
Fig 3.1 is used for the experimental verification of the proposed
algorithm. These images are captured using a single sensor digital
camera that uses a Color Filter Array (CFA) in which the color
filters are arranged in Bayer pattern. The sensor alignment of this
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94
single sensor digital camera is of the pattern GRBG as shown in Fig
2.2.
Fig: 3.1 Kodak Image Test Set
One of the 24 images of the Kodak image test set is taken as the
input for demosaicing process is shown in the Fig 3.2.
Fig: 3.2 Input Kodak Image
Mosaic Image is a picture that has been divided into
(usually equal sized) rectangular sections, each of which gives a
single color value red or green or blue based on the Bayer pattern as
shown in Fig 3.3.
Fig: 3.3 Mosaic Image
The horizontal estimate for the missing red and green pixel
values of the red and green rows and columns in the input mosaic
image and the horizontal estimate for the missing blue and green
pixel values of the blue and green rows and columns in the input
mosaic image are calculated.
Fig: 3.4 Horizontal color channel estimation
The vertical estimate for the missing red and green pixel
values of the red and green rows and columns in the input mosaic
image and the vertical estimate for the missing blue and green pixel
values of the blue and green rows and columns in the input mosaic
image are calculated.
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Fig: 3.5 Vertical color channel estimation
Fig: 3.6 Horizontal color difference
The image quality can be improved by applying the
interpolation over color differences. This is an important technique
employs the reconstruction of full color images, obtained by
interpolation along horizontal and vertical directions as in Fig 3.6
and Fig 3.7.
Fig: 3.7 Vertical color difference
Initial green channel interpolation concentrates on
estimating missing green pixels from known green and red pixel
values using the green and red row of Bayer pattern and missing
green pixels from known green and blue pixel values using the
green and blue row of Bayer pattern as shown in Fig 3.8.
Fig: 3.8 Initial Green channel Interpolation
Fig: 3.9 Green channel update
The green channel results are improved by updating the
initial color difference estimates as shown in Fig 3.9. Here the four
neighbors of the target pixel calculated as north, south, east and
west directions.
Fig: 3.10 Before Refinement
After the green channel has been reconstructed, the red and blue
components are interpolated. The most common approach for red
and blue estimation consists in interpolation of the color differences.
Now the image can be reconstructed with these interpolated color
channel values as shown in Fig 3.10.
.
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Fig: 3.11 Red plane Refinement
After interpolating the red and blue channels, the red channel is further
refined using structural approximation method as shown in Fig 3.11.
Fig: 3.12 Blue Plane Refinement
After interpolating the red and blue channels, the blue channel
is further refined using structural approximation method as shown in
Fig 3.12.
Fig: 3.13 Reconstructed image
The above fig 3.13 is the reconstruction of the whole
image. After the interpolation red and blue channel refinement takes
place by using structural approximation method. Here we conclude
that the proposed method out performs the other methods through
the tests in terms of PSNR.
4. Image Quality Metrics
Objective measures of quality require a reference image
that is distortion-free to be used for comparison with the image
whose quality is to be measured. The dimensions of the reference
image and the dimensions of the degraded image must be identical.
Quality of the images can be measured in terms of:
4.1. PSNR
The peak signal-to-noise ratio is a measure of quality that
is determined by first calculating the mean squared error (MSE) and
then dividing the maximum range of the data type by the MSE. This
measure is simple to calculate but sometimes doesn't align well with
perceived quality by humans. For example, the PSNR for a blurred
image compared to an unblurred image is quite high, even though
the perceived quality is low.
)(log.10)(log.20
log.10
1010
2
10
MSEMAXSNR
MSE
MAX
SNR
I
I
4.2. SSIM
The Structural Similarity (SSIM) Index measure of quality
works by measuring the structural similarity that compares local
patterns of pixel intensities that have been normalized for luminance
and contrast. This quality metric is based on the principle that the
human visual system is good for extracting information based on
structure.
covariance-crossanddeviationStandard
means,localtheareand,,,
22
,
2
22
1
22
21
xyyxyx
yxyx
xyyx
where
CC
CC
yxSSIM
4.1.1. Performance Comparison in terms of CPSNR
The performance of proposed method in terms of CPSNR
compared with the Local Polynomial Approximation (LPA),
Gradient Based Threshold Free demosaicing (GBTF) and Multiscale
Gradient Based Demosaicing (MGBD). Finally the proposed
method gives more performance than the existing methods.
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Table 4.1.1: Comparison of CPSNR Error Measure for Different
Demosaicing Methods on the BAYER PATTERN
Fig: 4.1.1. Performance comparisons after refinement
4.2.1. Performance Comparison in terms of SSIM
The performance of proposed method in terms of SSIM
compared with the Multiscale Gradient Based Demosaicing
(MGBD). Finally the proposed method gives more performance
than the existing method.
Table 4.2.1: Comparison of SSIM before and after refinement
Fig: 4.2.1. Performance comparisons after refinement
5. CONCLUSION AND FUTURE WORK
0
10
20
30
40
50
60
1
4
7
10
13
16
19
22
Avg
CPSNR
Image Number
Performance Measure in terms of CPSNR
LPA
GBTF
MGBD
Proposed
0.8
0.85
0.9
0.95
1
1
4
7
10
13
16
19
22
Avg
SSIM
Image Number
Performance in terms of SSIM
MGBD
Proposed
No LPA GBTF MGBD Proposed
1 40.46 36.19 39.87 40.61
2 41.33 41.99 41.77 46.18
3 43.47 43.66 43.72 47.86
4 40.86 42.38 41.13 45.86
5 37.54 37.86 39.05 42.47
6 40.93 37.74 41.38 42.87
7 43.02 43.16 43.51 47.89
8 37.13 34.94 37.56 39.99
9 43.49 42.01 43.96 47.89
10 42.67 42.67 43.20 47.72
11 40.53 39.09 41.36 43.62
12 43.98 42.43 44.45 48.26
13 36.09 35.22 36.00 37.72
14 36.97 39.19 37.97 42.29
15 40.09 41.86 40.30 45.00
16 43.99 40.12 44.86 46.33
17 41.80 42.43 42.32 46.76
18 37.42 38.97 38.22 41.97
19 41.51 38.42 42.17 44.71
20 41.44 41.86 42.16 45.96
21 39.63 38.76 40.31 42.44
22 38.49 40.15 39.05 43.68
23 43.89 44.08 44.02 47.46
24 35.37 38.32 35.69 41.38
Avg 40.50 40.15 41.00 44.46
No MGBD Proposed
1 0.9186 0.9523
2 0.9227 0.9711
3 0.9110 0.9595
4 0.9135 0.9616
5 0.9352 0.9621
6 0.8887 0.9586
7 0.9204 0.9615
8 0.9249 0.9540
9 0.9116 0.9488
10 0.9169 0.9529
11 0.8917 0.9526
12 0.8801 0.9600
13 0.9167 0.9473
14 0.9255 0.9579
15 0.9288 0.9668
16 0.9142 0.9544
17 0.9422 0.9589
18 0.9368 0.9638
19 0.9182 0.9553
20 0.9201 0.9523
21 0.9193 0.9561
22 0.9250 0.9571
23 0.9267 0.9635
24 0.9297 0.9550
Avg 0.9183 0.9576
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The proposed demosaicing method uses Multiscale color
gradients to adaptively combine color difference estimates from
different directions and then the red and blue channels are refined
using Structural Approximation method. The proposed solution
does not require any thresholds since it does not make any hard
decisions. It is non-iterative. The relationship between color
gradients at different scales can be used to develop a high quality
CFA interpolation. This method is easy to implement. Experimental
results show the effectiveness of proposed method as it clearly
outperforms the other available algorithms by a margin in terms of
CPSNR and SSIM. Further research efforts can focus on improving
the results and applying the multi scale gradients idea to other image
processing problems.
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