Histogram Equalization (HE) has been an essential addition to the Image Enhancement world.
Enhancement techniques like Classical Histogram Equalization(CHE),Adaptive Histogram Equalization
(AHE), Bi-Histogram Equalization (BHE) and Recursive Mean Separate Histogram Equalization (RMSHE)
methods enhance contrast, brightness is not well preserved, which gives an unpleasant look to the final
image obtained. Thus, we introduce a novel technique Multi-Decomposition Histogram Equalization
(MDHE) to eliminate the drawbacks of the earlier methods. In MDHE, we have decomposed the input
image using a unique logic, applied CHE in each of the sub-images and then finally interpolated them in
correct order. The final image after MDHE gives us the best results based on contrast enhancement and
brightness preservation aspect compared to all other techniques mentioned above. We have calculated the
various parameters like PSNR, SNR, RMSE, MSE, etc. for every technique. Our results are well supported
by bar graphs, histograms and the parameter calculations at the end.
CONTRAST ENHANCEMENT TECHNIQUES USING HISTOGRAM EQUALIZATION METHODS ON COLOR...IJCSEA Journal
Ā
Histogram equalization (HE) is a simple and widely used image contrast enhancement technique. The basic disadvantage of HE is it changes the brightness of the image. In order to overcome this drawback, various HE methods have been proposed. These methods preserves the brightness on the output image but, does not have a natural look. In order to overcome this problem the, present paper uses Multi-HE methods, which decompose the image into several sub images, and classical HE method is applied to each sub image. The algorithm is applied on various images and has been analysed using both objective and subjective assessment.
7 ijaems sept-2015-8-design and implementation of fuzzy logic based image fus...INFOGAIN PUBLICATION
Ā
The quality of image holds importance for both humans and machines. To fulfill the requirement of good quality images, image enhancement is needed. Application of a single contrast enhancement technique often does not produce desirable result and may lead to over enhanced images. To overcome this problem image fusion is performed so that better results with desired enhancement can be achieved. In the present paper an amalgamation of image enhancement, fusion and sharpening have been carried out in the candidate algorithm. The algorithm makes use of fuzzy logic for weight calculation. The results are compared with DACE/LIF approach and it is observed that the proposed algorithm improves the result in terms of quality parameters like PSNR (Peak Signal to Noise Ratio), AMBE (Absolute Mean Brightness Error) and SSIM (Structural Similarity Index) by 0.5 dB, 3 and 0.1 respectively from the existing technique.
Review on Image Enhancement in Spatial Domainidescitation
Ā
With the proliferation in electronic imaging devices
like in mobiles, computer vision, medical field and space field;
image enhancement field has become the quite interesting
and important area of research. These imaging devices are
viewed under a diverse range of viewing conditions and a huge
loss in contrast under bright outdoor viewing conditions; thus
viewing condition parameters such as surround effects,
correlated color temperature and ambient lighting have
become of significant importance. Therefore, Principle
objective of Image enhancement is to adjust the quality of an
image for better human visual perception. Appropriate choice
of enhancement techniques is greatly influenced by the
imaging modality, task at hand and viewing conditions.
Basically, image enhancement techniques have been classified
into two broad categories: Spatial domain image enhancement
and Frequency domain image enhancement. This survey report
gives an overview of different methodologies have been used
for enhancement under the spatial domain category. It is noted
that in this field still more research is to be done.
Modified Contrast Enhancement using Laplacian and Gaussians Fusion Techniqueiosrjce
Ā
The aim of image fusion is to mix images of a scene captured below totally different illumination. One
image contains most of information from the whole supply images automatically. Contrast enhancement is employed
to enhance the standard of visible image with none introducing unrealistic visual appearances. Fusion technique is
employed for the important applications like medical imaging, microscopic imaging, remote sensing, and laptop
vision and robotics. Contrast enhancement improves the brightness differences within the dark, gray or bright regions
at the expense of the brightness differences within the alternative regions. During this paper methodology of the
contrast enhancement for images that improves the local image contrast by controlling the local image gradient. The
proposed methodology improves the improvement drawback and maximizes the local contrast and global contrast of
an image.
MODIFIED HISTOGRAM EQUALIZATION FOR IMAGE CONTRAST ENHANCEMENT USING PARTICLE...ijcseit
Ā
A novel Modified Histogram Equalization (MHE) technique for contrast enhancement is proposed in this
paper. This technique modifies the probability density function of an image by introducing constraints prior
to the process of histogram equalization (HE). These constraints are formulated using two parameters
which are optimized using swarm intelligence. This technique of contrast enhancement takes control over
the effect of HE so that it enhances the image without causing any loss to its details. A median adjustment
factor is then added to the result to normalize the change in the luminance level after enhancement. This
factor suppresses the effect of luminance change due to the presence of outlier pixels. The outlier pixels of
highly deviated intensities have greater impact in changing the contrast of an image. This approach
provides a convenient and effective way to control the enhancement process, while being adaptive to
various types of images. Experimental results show that the proposed technique gives better results in
terms of Discrete Entropy and SSIM values than the existing histogram-based equalization methods.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
CONTRAST ENHANCEMENT TECHNIQUES USING HISTOGRAM EQUALIZATION METHODS ON COLOR...IJCSEA Journal
Ā
Histogram equalization (HE) is a simple and widely used image contrast enhancement technique. The basic disadvantage of HE is it changes the brightness of the image. In order to overcome this drawback, various HE methods have been proposed. These methods preserves the brightness on the output image but, does not have a natural look. In order to overcome this problem the, present paper uses Multi-HE methods, which decompose the image into several sub images, and classical HE method is applied to each sub image. The algorithm is applied on various images and has been analysed using both objective and subjective assessment.
7 ijaems sept-2015-8-design and implementation of fuzzy logic based image fus...INFOGAIN PUBLICATION
Ā
The quality of image holds importance for both humans and machines. To fulfill the requirement of good quality images, image enhancement is needed. Application of a single contrast enhancement technique often does not produce desirable result and may lead to over enhanced images. To overcome this problem image fusion is performed so that better results with desired enhancement can be achieved. In the present paper an amalgamation of image enhancement, fusion and sharpening have been carried out in the candidate algorithm. The algorithm makes use of fuzzy logic for weight calculation. The results are compared with DACE/LIF approach and it is observed that the proposed algorithm improves the result in terms of quality parameters like PSNR (Peak Signal to Noise Ratio), AMBE (Absolute Mean Brightness Error) and SSIM (Structural Similarity Index) by 0.5 dB, 3 and 0.1 respectively from the existing technique.
Review on Image Enhancement in Spatial Domainidescitation
Ā
With the proliferation in electronic imaging devices
like in mobiles, computer vision, medical field and space field;
image enhancement field has become the quite interesting
and important area of research. These imaging devices are
viewed under a diverse range of viewing conditions and a huge
loss in contrast under bright outdoor viewing conditions; thus
viewing condition parameters such as surround effects,
correlated color temperature and ambient lighting have
become of significant importance. Therefore, Principle
objective of Image enhancement is to adjust the quality of an
image for better human visual perception. Appropriate choice
of enhancement techniques is greatly influenced by the
imaging modality, task at hand and viewing conditions.
Basically, image enhancement techniques have been classified
into two broad categories: Spatial domain image enhancement
and Frequency domain image enhancement. This survey report
gives an overview of different methodologies have been used
for enhancement under the spatial domain category. It is noted
that in this field still more research is to be done.
Modified Contrast Enhancement using Laplacian and Gaussians Fusion Techniqueiosrjce
Ā
The aim of image fusion is to mix images of a scene captured below totally different illumination. One
image contains most of information from the whole supply images automatically. Contrast enhancement is employed
to enhance the standard of visible image with none introducing unrealistic visual appearances. Fusion technique is
employed for the important applications like medical imaging, microscopic imaging, remote sensing, and laptop
vision and robotics. Contrast enhancement improves the brightness differences within the dark, gray or bright regions
at the expense of the brightness differences within the alternative regions. During this paper methodology of the
contrast enhancement for images that improves the local image contrast by controlling the local image gradient. The
proposed methodology improves the improvement drawback and maximizes the local contrast and global contrast of
an image.
MODIFIED HISTOGRAM EQUALIZATION FOR IMAGE CONTRAST ENHANCEMENT USING PARTICLE...ijcseit
Ā
A novel Modified Histogram Equalization (MHE) technique for contrast enhancement is proposed in this
paper. This technique modifies the probability density function of an image by introducing constraints prior
to the process of histogram equalization (HE). These constraints are formulated using two parameters
which are optimized using swarm intelligence. This technique of contrast enhancement takes control over
the effect of HE so that it enhances the image without causing any loss to its details. A median adjustment
factor is then added to the result to normalize the change in the luminance level after enhancement. This
factor suppresses the effect of luminance change due to the presence of outlier pixels. The outlier pixels of
highly deviated intensities have greater impact in changing the contrast of an image. This approach
provides a convenient and effective way to control the enhancement process, while being adaptive to
various types of images. Experimental results show that the proposed technique gives better results in
terms of Discrete Entropy and SSIM values than the existing histogram-based equalization methods.
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Efficient contrast enhancement using gamma correction with multilevel thresho...eSAT Publishing House
Ā
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.
Feature Extraction of an Image by Using Adaptive Filtering and Morpological S...IOSR Journals
Ā
Abstract: For enhancing an image various enhancement schemes are used which includes gray scale manipulation, filtering and Histogram Equalization, Where Histogram equalization is one of the well known image enhancement technique. It became a popular technique for contrast enhancement because it is simple and effective. The basic idea of Histogram Equalization method is to remap the gray levels of an image. Here using morphological segmentation we can get the segmented image. Morphological reconstruction is used to segment the image. Comparative analysis of different enhancement and segmentation will be carried out. This comparison will be done on the basis of subjective and objective parameters. Subjective parameter is visual quality and objective parameters are Area, Perimeter, Min and Max intensity, Avg Voxel Intensity, Std Dev of Intensity, Eccentricity, Coefficient of skewness, Coefficient of Kurtosis, Median intensity, Mode intensity. Keywords: Histogram Equalization, Segmentation, Morphological Reconstruction .
Image Enhancement using Guided Filter for under Exposed ImagesDr. Amarjeet Singh
Ā
Image enhancement becomes an important step to
improve the quality of image and change in the appearance of
the image in such a way that either a human or a machine can
fetch certain information from the image after a change. Due
to low contrast images it becomes very difficult to get any
information out of it. In todayās digital world of imaging
image enhancement is a very useful in various applications
ranging from electronics printing to recognition. For highly
underexposed region, intensity bin are present in darken
region thatās by such images lacks in saturation and suffers
from low intensity. Power law transformation provides
solution to this problem. It enhances the brightness so as
image at least becomes visible. To modify the intensity level
histogram equalization can be used. In this we can apply
cumulative density function and probabilistic density function
so as to divide the image into sub images.
In proposed approach to provide betterment in
results guided filter has been applied to images after
equalization so that we can get better Entropy rate and
Coefficient of correlation can be improved with previously
available techniques. The guided filter is derived from local
linear model. The guided filter computes the filtering output
by considering the content of guidance image, which can be
the image itself or other targeted image.
Image enhancement is a method of improving the quality of an image and contrast is a major aspect. Traditional methods of contrast enhancement like histogram equalization results in over/under enhancement of the image especially a lower resolution one. This paper aims at developing a new Fuzzy Inference System to enhance the contrast of the low resolution images overcoming the shortcomings of the traditional methods. Results obtained using both the approaches are compared.
Hierarchical Approach for Total Variation Digital Image InpaintingIJCSEA Journal
Ā
The art of recovering an image from damage in an undetectable form is known as inpainting. The manual work of inpainting is most often a very time consum ing process. Due to digitalization of this technique, it is automatic and faster. In this paper, after the user selects the regions to be reconstructed, the algorithm automatically reconstruct the lost regions with the help of the information surrounding them. The existing methods perform very well when the region to be reconstructed is very small, but fails in proper reconstruction as the area increases. This paper describes a Hierarchical method by which the area to be inpainted is reduced in multiple levels and Total Variation(TV) method is used to inpaint in each level. This algorithm gives better performance when compared with other existing algorithms such as nearest neighbor interpolation, Inpainting through Blurring and Sobolev Inpainting.
Image enhancement is one of the challenging issues in image processing. The objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a lot of choices for improving the visual quality of images. Appropriate choice of such techniques is very important. This paper will provide an overview and analysis of different techniques commonly used for image enhancement. Image enhancement plays a fundamental role in vision applications. Recently much work is completed in the field of images enhancement. Many techniques have previously been proposed up to now for enhancing the digital images. In this paper, a survey on various image enhancement techniques has been done.
Interpolation Technique using Non Linear Partial Differential Equation with E...CSCJournals
Ā
With the large use of images for the communication, image zooming plays an important role.
Image zooming is the process of enlarging the image with some factor of magnification, where
the factor can be integer or non-integer. Applying zooming algorithm to an image generally results
in aliasing; edge blurring and other artifacts. The main focus of the work presented in this paper is
on the reduction of these artifacts. This paper focuses on reduction of these artifacts and
presents an image zooming algorithm using non-linear fourth order PDE method combined with
edge directed bi-cubic algorithm. The proposed method uses high resolution image obtained from
edge directed bi-cubic interpolation algorithm to construct the zoomed image. This technique
preserves edges and minimizes blurring and staircase effects in the zoomed image. In order to
evaluate image quality obtained after zooming, the objective assessment is performed.
Image enhancement technique plays vital role in improving the quality of the image. Enhancement
technique basically enhances the foreground information and retains the background and improve the
overall contrast of an image. In some case the background of an image hides the structural information of
an image. This paper proposes an algorithm which enhances the foreground image and the background
part separately and stretch the contrast of an image at inter-object level and intra-object level and then
combines it to an enhanced image. The results are compared with various classical methods using image
quality measures
A Novel Color Image Fusion for Multi Sensor Night Vision ImagesEditor IJCATR
Ā
In this paper presents a simple and fast color fusion approach for night vision images. Image fusion involves merging of two
or more images in such a way, to get the most advantageous characteristics of each image. Here the Visible image is fused with the
InfraRed (IR) image, so the desired result will be single, highly informative image providing full information. This paper focuses on
color constancy and color contrast problem.
Firstly the contrast of the infrared and visible image is enhanced using Local Histogram Equation. Then the two enhanced
images are fused in three compounds of a LAB image using aDWT image fusion. This paper adopts an approach which transfer color
from the reference image to the fused image using Color Transfer Technology. To enhance the contrast between the target and the
background, a scaling factor is introduced in the transferring equation in the b channel. Finally our approach gives the Multiband
Fused image with the natural day-time color appearance and the hot targets are popped out with intense colors while the background
details present with the natural color appearance.
A MODIFIED HISTOGRAM BASED FAST ENHANCEMENT ALGORITHMcsandit
Ā
The contrast enhancement of medical images has an important role in diseases diagnostic,
specially, cancer cases. Histogram equalization is considered as the most popular algorithm for
contrast enhancement according to its effectiveness and simplicity. In this paper, we present a
modified version of the Histogram Based Fast Enhancement Algorithm. This algorithm
enhances the areas of interest with less complexity. It is applied only to CT head images and its
idea based on treating with the soft tissues and ignoring other details in the image. The
proposed modification make the algorithm is valid for most CT image types with enhanced
results.
COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATIONecij
Ā
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its
histogram. It increases the brightness of a gray scale image which is different from the mean brightness of
the original image. There are various types of Histogram equalization techniques like Histogram
Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram
Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi
Histogram Equalization, Recursive Mean Separate Histogram Equalization and Recursive Sub Image
Histogram Equalization. In this paper, the histogram equalization approach of gray-level images is
extended for colour images. The acquired image is converted into HSV (Hue, Saturation, Value). The
image is then decomposed into two parts by using exposure threshold and then equalized them
independently Over enhancement is also controlled in this method by using clipping threshold. For
measuring the performance of the enhanced image, entropy and contrast are calculated.
SENSORLESS VECTOR CONTROL OF BLDC USING EXTENDED KALMAN FILTER sipij
Ā
This Paper mainly deals with the implementation of vector control technique using the brushless DC motor
(BLDC). Generally tachogenerators, resolvers or incremental encoders are used to detect the speed. These
sensors require careful mounting and alignment, and special attention is required with electrical noises. A
speed sensor need additional space for mounting and maintenance and hence increases the cost and size of
the drive system. These problems are eliminated by speed sensor less vector control by using Extended
Kalman Filter and Back EMF method for position sensing. By using the EKF method and Back EMFmethod, the sensor less vector control of BLDC is implemented and its simulation using MATLAB/SIMULINK and hardware kit is implemented.
C OMPARISON OF M ODERN D ESCRIPTION M ETHODS F OR T HE R ECOGNITION OF ...sipij
Ā
Plants are one kingdom of living things. They are e
ssential to the balance of nature and peopleās live
s.
Plants are not just important to human environment,
they form the basis for the sustainability and lon
g-
term health of environmental systems. Beside these
important facts, they have many useful applications
such as medical application and agricultural applic
ation. Also plants are the origin of coal and petro
leum.
In order to plant recognition, one part of it has u
nique characteristic for recognition process. This
desired
part is leaf. The present paper introduces bag of w
ords (BoW) and support vector machine (SVM)
procedure to recognize and identify plants through
leaves. Visual contents of images are applied and t
hree
usual phases in computer vision are done: (i) featu
re detection, (ii) feature description, (iii) image
description. Three different methods are used on Fl
avia dataset. The proposed approach is done by scal
e
invariant feature transform (SIFT) method and two c
ombined method, HARRIS-SIFT and features from
accelerated segment test-SIFT (FAST-SIFT). The accu
racy of SIFT method is higher than other methods
which is 89.3519 %. Vision comparison is investigat
ed for four different species. Some quantitative re
sults
are measured and compared.
Image processing based girth monitoring and recording system for rubber plant...sipij
Ā
Measuring the girth and continuous monitoring of the increase in girth is one of the most important processes in rubber plantations since identification of girth deficiencies would enable planters to take corrective actions to ensure a good yield from the plantation.
This research paper presents an image processing based girth measurement & recording system that can replace existing manual process in an efficient and economical manner.
The system uses a digital image of the tree which uses the current number drawn on the tree to identify the tree number & its width. The image is threshold first & then filtered out using several filtering criterion to identify possible candidates for numbers. Identified blobs are then fed to the Tesseract OCR for number recognition. Threshold image is then filtered again with different criterion to segment out the black strip drawn on the tree which is then used to calculate the width of the tree using calibration parameters. Once the tree number is identified & width is calculated the girth the measured girth of the tree is stored in the data base under the identified tree number.
The results obtained from the system indicated significant improvement in efficiency & economy for main plantations. As future developments we are proposing a standard commercial system for girth measurement using standardized 2D Bar Codes as tree identifiers
Development and Hardware Implementation of an Efficient Algorithm for Cloud D...sipij
Ā
Detecting clouds in satellite imagery is becoming more important with increasing data availability which
are generated by earth observing satellites. Hence, intellectual processing of the enormous amount of data
received by hundreds of earth receiving stations, with specific satellite image oriented approaches,
presents itself as a pressing need. One of the most important steps in previous stages of satellite image
processing is cloud detection. While there are many approaches that compact with different semantic
meaning, there are rarely approaches that compact specifically with cloud and cloud cover detection. In
this paper, the technique presented is the scene based adaptive cloud, cloud cover detection and find the
position with assumption of sun reflection, background varying and scattering are constant. The capability
of the developed system was tested using dedicated satellite images and assessed in terms of cloud
percentage coverage. The system used for this process comprises of Intel(R) Xenon(R) CPU E31245 @
3.30GHz processor along with MATLAB 13 software and DSPC6713 processor along with Code Compose
Studio 3.1.
A NOVEL PROBABILISTIC BASED IMAGE SEGMENTATION MODEL FOR REALTIME HUMAN ACTIV...sipij
Ā
Automatic human activity detection is one of the difficult tasks in image segmentation application due to
variations in size, type, shape and location of objects. In the traditional probabilistic graphical
segmentation models, intra and inter region segments may affect the overall segmentation accuracy. Also,
both directed and undirected graphical models such as Markov model, conditional random field have
limitations towards the human activity prediction and heterogeneous relationships. In this paper, we have
studied and proposed a natural solution for automatic human activity segmentation using the enhanced
probabilistic chain graphical model. This system has three main phases, namely activity pre-processing,
iterative threshold based image enhancement and chain graph segmentation algorithm. Experimental
results show that proposed system efficiently detects the human activities at different levels of the action
datasets.
A study of a modified histogram based fast enhancement algorithm (mhbfe)sipij
Ā
Image enhancement is one of the most important issues in low-level image processing. The goal of image
enhancement is to improve the quality of an image such that enhanced image is better than the original
image. Conventional Histogram equalization (HE) is one of the most algorithms used in the contrast
enhancement of medical images, this due to its simplicity and effectiveness. However, it causes the
unnatural look and visual artefacts, where it tends to change the brightness of an images. The Histogram
Based Fast Enhancement Algorithm (HBFE) tries to enhance the CT head images, where it improves the
water-washed effect caused by conventional histogram equalization algorithms with less complexity. It
depends on using full gray levels to enhance the soft tissues ignoring other image details. We present a
modification of this algorithm to be valid for most CT image types with keeping the degree of simplicity.
Experimental results show that The Modified Histogram Based Fast Enhancement Algorithm (MHBFE)
enhances the results in term of PSNR, AMBE and entropy. We use also the Statistical analysis to ensure
the improvement of the proposed modification that can be generalized. ANalysis Of VAriance (ANOVA) is
used as first to test whether or not all the results have the same average. Then we find the significant
improvement of the modification.
Efficient contrast enhancement using gamma correction with multilevel thresho...eSAT Publishing House
Ā
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.
Feature Extraction of an Image by Using Adaptive Filtering and Morpological S...IOSR Journals
Ā
Abstract: For enhancing an image various enhancement schemes are used which includes gray scale manipulation, filtering and Histogram Equalization, Where Histogram equalization is one of the well known image enhancement technique. It became a popular technique for contrast enhancement because it is simple and effective. The basic idea of Histogram Equalization method is to remap the gray levels of an image. Here using morphological segmentation we can get the segmented image. Morphological reconstruction is used to segment the image. Comparative analysis of different enhancement and segmentation will be carried out. This comparison will be done on the basis of subjective and objective parameters. Subjective parameter is visual quality and objective parameters are Area, Perimeter, Min and Max intensity, Avg Voxel Intensity, Std Dev of Intensity, Eccentricity, Coefficient of skewness, Coefficient of Kurtosis, Median intensity, Mode intensity. Keywords: Histogram Equalization, Segmentation, Morphological Reconstruction .
Image Enhancement using Guided Filter for under Exposed ImagesDr. Amarjeet Singh
Ā
Image enhancement becomes an important step to
improve the quality of image and change in the appearance of
the image in such a way that either a human or a machine can
fetch certain information from the image after a change. Due
to low contrast images it becomes very difficult to get any
information out of it. In todayās digital world of imaging
image enhancement is a very useful in various applications
ranging from electronics printing to recognition. For highly
underexposed region, intensity bin are present in darken
region thatās by such images lacks in saturation and suffers
from low intensity. Power law transformation provides
solution to this problem. It enhances the brightness so as
image at least becomes visible. To modify the intensity level
histogram equalization can be used. In this we can apply
cumulative density function and probabilistic density function
so as to divide the image into sub images.
In proposed approach to provide betterment in
results guided filter has been applied to images after
equalization so that we can get better Entropy rate and
Coefficient of correlation can be improved with previously
available techniques. The guided filter is derived from local
linear model. The guided filter computes the filtering output
by considering the content of guidance image, which can be
the image itself or other targeted image.
Image enhancement is a method of improving the quality of an image and contrast is a major aspect. Traditional methods of contrast enhancement like histogram equalization results in over/under enhancement of the image especially a lower resolution one. This paper aims at developing a new Fuzzy Inference System to enhance the contrast of the low resolution images overcoming the shortcomings of the traditional methods. Results obtained using both the approaches are compared.
Hierarchical Approach for Total Variation Digital Image InpaintingIJCSEA Journal
Ā
The art of recovering an image from damage in an undetectable form is known as inpainting. The manual work of inpainting is most often a very time consum ing process. Due to digitalization of this technique, it is automatic and faster. In this paper, after the user selects the regions to be reconstructed, the algorithm automatically reconstruct the lost regions with the help of the information surrounding them. The existing methods perform very well when the region to be reconstructed is very small, but fails in proper reconstruction as the area increases. This paper describes a Hierarchical method by which the area to be inpainted is reduced in multiple levels and Total Variation(TV) method is used to inpaint in each level. This algorithm gives better performance when compared with other existing algorithms such as nearest neighbor interpolation, Inpainting through Blurring and Sobolev Inpainting.
Image enhancement is one of the challenging issues in image processing. The objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a lot of choices for improving the visual quality of images. Appropriate choice of such techniques is very important. This paper will provide an overview and analysis of different techniques commonly used for image enhancement. Image enhancement plays a fundamental role in vision applications. Recently much work is completed in the field of images enhancement. Many techniques have previously been proposed up to now for enhancing the digital images. In this paper, a survey on various image enhancement techniques has been done.
Interpolation Technique using Non Linear Partial Differential Equation with E...CSCJournals
Ā
With the large use of images for the communication, image zooming plays an important role.
Image zooming is the process of enlarging the image with some factor of magnification, where
the factor can be integer or non-integer. Applying zooming algorithm to an image generally results
in aliasing; edge blurring and other artifacts. The main focus of the work presented in this paper is
on the reduction of these artifacts. This paper focuses on reduction of these artifacts and
presents an image zooming algorithm using non-linear fourth order PDE method combined with
edge directed bi-cubic algorithm. The proposed method uses high resolution image obtained from
edge directed bi-cubic interpolation algorithm to construct the zoomed image. This technique
preserves edges and minimizes blurring and staircase effects in the zoomed image. In order to
evaluate image quality obtained after zooming, the objective assessment is performed.
Image enhancement technique plays vital role in improving the quality of the image. Enhancement
technique basically enhances the foreground information and retains the background and improve the
overall contrast of an image. In some case the background of an image hides the structural information of
an image. This paper proposes an algorithm which enhances the foreground image and the background
part separately and stretch the contrast of an image at inter-object level and intra-object level and then
combines it to an enhanced image. The results are compared with various classical methods using image
quality measures
A Novel Color Image Fusion for Multi Sensor Night Vision ImagesEditor IJCATR
Ā
In this paper presents a simple and fast color fusion approach for night vision images. Image fusion involves merging of two
or more images in such a way, to get the most advantageous characteristics of each image. Here the Visible image is fused with the
InfraRed (IR) image, so the desired result will be single, highly informative image providing full information. This paper focuses on
color constancy and color contrast problem.
Firstly the contrast of the infrared and visible image is enhanced using Local Histogram Equation. Then the two enhanced
images are fused in three compounds of a LAB image using aDWT image fusion. This paper adopts an approach which transfer color
from the reference image to the fused image using Color Transfer Technology. To enhance the contrast between the target and the
background, a scaling factor is introduced in the transferring equation in the b channel. Finally our approach gives the Multiband
Fused image with the natural day-time color appearance and the hot targets are popped out with intense colors while the background
details present with the natural color appearance.
A MODIFIED HISTOGRAM BASED FAST ENHANCEMENT ALGORITHMcsandit
Ā
The contrast enhancement of medical images has an important role in diseases diagnostic,
specially, cancer cases. Histogram equalization is considered as the most popular algorithm for
contrast enhancement according to its effectiveness and simplicity. In this paper, we present a
modified version of the Histogram Based Fast Enhancement Algorithm. This algorithm
enhances the areas of interest with less complexity. It is applied only to CT head images and its
idea based on treating with the soft tissues and ignoring other details in the image. The
proposed modification make the algorithm is valid for most CT image types with enhanced
results.
COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATIONecij
Ā
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its
histogram. It increases the brightness of a gray scale image which is different from the mean brightness of
the original image. There are various types of Histogram equalization techniques like Histogram
Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram
Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi
Histogram Equalization, Recursive Mean Separate Histogram Equalization and Recursive Sub Image
Histogram Equalization. In this paper, the histogram equalization approach of gray-level images is
extended for colour images. The acquired image is converted into HSV (Hue, Saturation, Value). The
image is then decomposed into two parts by using exposure threshold and then equalized them
independently Over enhancement is also controlled in this method by using clipping threshold. For
measuring the performance of the enhanced image, entropy and contrast are calculated.
SENSORLESS VECTOR CONTROL OF BLDC USING EXTENDED KALMAN FILTER sipij
Ā
This Paper mainly deals with the implementation of vector control technique using the brushless DC motor
(BLDC). Generally tachogenerators, resolvers or incremental encoders are used to detect the speed. These
sensors require careful mounting and alignment, and special attention is required with electrical noises. A
speed sensor need additional space for mounting and maintenance and hence increases the cost and size of
the drive system. These problems are eliminated by speed sensor less vector control by using Extended
Kalman Filter and Back EMF method for position sensing. By using the EKF method and Back EMFmethod, the sensor less vector control of BLDC is implemented and its simulation using MATLAB/SIMULINK and hardware kit is implemented.
C OMPARISON OF M ODERN D ESCRIPTION M ETHODS F OR T HE R ECOGNITION OF ...sipij
Ā
Plants are one kingdom of living things. They are e
ssential to the balance of nature and peopleās live
s.
Plants are not just important to human environment,
they form the basis for the sustainability and lon
g-
term health of environmental systems. Beside these
important facts, they have many useful applications
such as medical application and agricultural applic
ation. Also plants are the origin of coal and petro
leum.
In order to plant recognition, one part of it has u
nique characteristic for recognition process. This
desired
part is leaf. The present paper introduces bag of w
ords (BoW) and support vector machine (SVM)
procedure to recognize and identify plants through
leaves. Visual contents of images are applied and t
hree
usual phases in computer vision are done: (i) featu
re detection, (ii) feature description, (iii) image
description. Three different methods are used on Fl
avia dataset. The proposed approach is done by scal
e
invariant feature transform (SIFT) method and two c
ombined method, HARRIS-SIFT and features from
accelerated segment test-SIFT (FAST-SIFT). The accu
racy of SIFT method is higher than other methods
which is 89.3519 %. Vision comparison is investigat
ed for four different species. Some quantitative re
sults
are measured and compared.
Image processing based girth monitoring and recording system for rubber plant...sipij
Ā
Measuring the girth and continuous monitoring of the increase in girth is one of the most important processes in rubber plantations since identification of girth deficiencies would enable planters to take corrective actions to ensure a good yield from the plantation.
This research paper presents an image processing based girth measurement & recording system that can replace existing manual process in an efficient and economical manner.
The system uses a digital image of the tree which uses the current number drawn on the tree to identify the tree number & its width. The image is threshold first & then filtered out using several filtering criterion to identify possible candidates for numbers. Identified blobs are then fed to the Tesseract OCR for number recognition. Threshold image is then filtered again with different criterion to segment out the black strip drawn on the tree which is then used to calculate the width of the tree using calibration parameters. Once the tree number is identified & width is calculated the girth the measured girth of the tree is stored in the data base under the identified tree number.
The results obtained from the system indicated significant improvement in efficiency & economy for main plantations. As future developments we are proposing a standard commercial system for girth measurement using standardized 2D Bar Codes as tree identifiers
Development and Hardware Implementation of an Efficient Algorithm for Cloud D...sipij
Ā
Detecting clouds in satellite imagery is becoming more important with increasing data availability which
are generated by earth observing satellites. Hence, intellectual processing of the enormous amount of data
received by hundreds of earth receiving stations, with specific satellite image oriented approaches,
presents itself as a pressing need. One of the most important steps in previous stages of satellite image
processing is cloud detection. While there are many approaches that compact with different semantic
meaning, there are rarely approaches that compact specifically with cloud and cloud cover detection. In
this paper, the technique presented is the scene based adaptive cloud, cloud cover detection and find the
position with assumption of sun reflection, background varying and scattering are constant. The capability
of the developed system was tested using dedicated satellite images and assessed in terms of cloud
percentage coverage. The system used for this process comprises of Intel(R) Xenon(R) CPU E31245 @
3.30GHz processor along with MATLAB 13 software and DSPC6713 processor along with Code Compose
Studio 3.1.
A NOVEL PROBABILISTIC BASED IMAGE SEGMENTATION MODEL FOR REALTIME HUMAN ACTIV...sipij
Ā
Automatic human activity detection is one of the difficult tasks in image segmentation application due to
variations in size, type, shape and location of objects. In the traditional probabilistic graphical
segmentation models, intra and inter region segments may affect the overall segmentation accuracy. Also,
both directed and undirected graphical models such as Markov model, conditional random field have
limitations towards the human activity prediction and heterogeneous relationships. In this paper, we have
studied and proposed a natural solution for automatic human activity segmentation using the enhanced
probabilistic chain graphical model. This system has three main phases, namely activity pre-processing,
iterative threshold based image enhancement and chain graph segmentation algorithm. Experimental
results show that proposed system efficiently detects the human activities at different levels of the action
datasets.
A study of a modified histogram based fast enhancement algorithm (mhbfe)sipij
Ā
Image enhancement is one of the most important issues in low-level image processing. The goal of image
enhancement is to improve the quality of an image such that enhanced image is better than the original
image. Conventional Histogram equalization (HE) is one of the most algorithms used in the contrast
enhancement of medical images, this due to its simplicity and effectiveness. However, it causes the
unnatural look and visual artefacts, where it tends to change the brightness of an images. The Histogram
Based Fast Enhancement Algorithm (HBFE) tries to enhance the CT head images, where it improves the
water-washed effect caused by conventional histogram equalization algorithms with less complexity. It
depends on using full gray levels to enhance the soft tissues ignoring other image details. We present a
modification of this algorithm to be valid for most CT image types with keeping the degree of simplicity.
Experimental results show that The Modified Histogram Based Fast Enhancement Algorithm (MHBFE)
enhances the results in term of PSNR, AMBE and entropy. We use also the Statistical analysis to ensure
the improvement of the proposed modification that can be generalized. ANalysis Of VAriance (ANOVA) is
used as first to test whether or not all the results have the same average. Then we find the significant
improvement of the modification.
Enhancement performance of road recognition system of autonomous robots in sh...sipij
Ā
Road region recognition is a main feature that is gaining increasing attention from intellectuals because it
helps autonomous vehicle to achieve a successful navigation without accident. However, different
techniques based on camera sensor have been used by various researchers and outstanding results have
been achieved. Despite their success, environmental noise like shadow leads to inaccurate recognition of
road region which eventually leads to accident for autonomous vehicle. In this research, we conducted an
investigation on shadow and its effects, optimized the road region recognition system of autonomous
vehicle by introducing an algorithm capable of detecting and eliminating the effects of shadow. The
experimental performance of our system was tested and compared using the following schemes: Total
Positive Rate (TPR), False Negative Rate (FNR), Total Negative Rate (TNR), Error Rate (ERR) and False
Positive Rate (FPR). The performance result of the system improved on road recognition in shadow
scenario and this advancement has added tremendously to successful navigation approaches for
autonomous vehicle.
Holistic privacy impact assessment framework for video privacy filtering tech...sipij
Ā
In this paper, we present a novel Holistic Framework for Privacy Protection Level Performance Evaluation
and Impact Assessment (H-PIA) to support the design and deployment of privacy-preserving filtering
techniques as may be co-evolved for video surveillance through user-centred participative engagement and
collectively negotiated solution seeking for privacy protection. The proposed framework is based on the
UI-REF normative ethno-methodological framework for Privacy-by-Co-Design which is based on
collective-interpretivist and socio-psycho-cognitively rooted Human Judgment and Decision Making (JDM)
theory including Pleasure-Pain-Recall (PPR)-theoretic opinion elicitation and analysis. This supports not
only the socio-ethically reflective conflicts resolution, prioritisation and traceability of privacy-preserving
requirements evolving through user-centred co-design but also the integration of Key Holistic
Performance Indicators (KPIs) comprising a number of objective and subjective evaluation metrics for the
design and operational deployment of surveillance data/-video-analytics from a system-of-system-scale
context-aware accountability engineering perspective. For the objective tests, we have proposed five
crucial criteria to be evaluated to assess the optimality of the balance of privacy protection and security
assurance as may be negotiated with end-users through co-design of a privacy filtering solution. This
evaluation is supported by a process of quantitative assessment of some of the KPIs through an automated
objective measurement of the functional performance of the given filter. Additionally, a subjective
qualitative user study has been conducted to correlate with, and cross-validate, the results obtained from
the objective assessment of the KPIs. The simulation results have confirmed the sufficiency, necessity and
efficacy of the UI-REF-based methodologically-guided framework for Privacy Protection evaluation to
enable optimally balanced Privacy Filtering of the video frame whilst retaining the minimum of the
information as negotiated per agreed process logic. Insights from this study have served the co-design and
deployment optimisation of privacy-preserving video filtering solutions. This UI-REF-based framework
has been successfully applied to the evaluation of MediaEval 2012-2013 Privacy Filtering and as such has
served to motivates further innovation in co-design and multi-level, multi-modal impact assessment of
multimedia privacy-security-balancing risk mitigation technologies.
A Comparative Study of DOA Estimation Algorithms with Application to Tracking...sipij
Ā
Tracking the Direction of Arrival (DOA) Estimation of a moving source is an important and challenging
task in the field of navigation, RADAR, SONAR, Wireless Sensor Networks (WSNs) etc. Tracking is carried
out starting from the estimation of DOA, considering the estimated DOA as an initial value, the Kalman
Filter (KF) algorithm is used to track the moving source based on the motion model which governs the
motion of the source. This comparative study deals with analysis, significance of Non-coherent,
Narrowband DOA (Direction of Arrival) Estimation Algorithms in perception to tracking. The DOA
estimation algorithms Multiple Signal Classification (MUSIC), Root-MUSIC& Estimation of Signal
Parameters via Rotational Invariance Technique (ESPRIT) are considered for the purpose of the study, a
comparison in terms of optimality with respect to Signal to Noise Ratio (SNR), number of snapshots and
number of Antenna elements used and Computational complexity is drawn between the chosen algorithms
resulting in an optimum DOA estimate. The optimum DOA Estimate is taken as an initial value for the
Kalman filter tracking algorithm. The Kalman filter algorithm is used to track the optimum DOA Estimate.
Implementation of features dynamic tracking filter to tracing pupilssipij
Ā
The objective of this paper is to show the implementation of an artificial vision filter capable of tracking the
pupils of a person in a video sequence. There are several algorithms that can achieve this objective, for this
case, features dynamic tracking selected, which is a method that traces patterns between each frame that
form a video scene, this type of processing offers the advantage of eliminating the problems of occlusion
patterns of interest. The implementation was tested on a base of videos of people with different physical
characteristics of the eyes. An additional goal is to obtain information of the eye movements that are
captured and pupil coordinates for each of these movements. These data could help some studies related to
eye health.
āFIELD PROGRAMMABLE DSP ARRAYSā - A NOVEL RECONFIGURABLE ARCHITECTURE FOR EFF...sipij
Ā
Digital Signal Processing functions are widely used in real time high speed applications. Those functions
are generally implemented either on ASICs with inflexibility, or on FPGAs with bottlenecks of relatively
smaller utilization factor or lower speed compared to ASIC. The proposed reconfigurable DSP processor is
redolent to FPGA, but with basic fixed Common Modules (CMs) (like adders, subtractors, multipliers,
scaling units, shifters) instead of CLBs. This paper introduces the development of a reconfigurable DSP
processor that integrates different filter and transform functions. The switching between DSP functions is
occurred by reconfiguring the interconnection between CMs. Validation of the proposed reconfigurable
architecture has been achieved on Virtex5 FPGA. The architecture provides sufficient amount of flexibility,
parallelism and scalability.
A ROBUST CHAOTIC AND FAST WALSH TRANSFORM ENCRYPTION FOR GRAY SCALE BIOMEDICA...sipij
Ā
In this work, a new scheme of image encryption based on chaos and Fast Walsh Transform (FWT) has been proposed.
We used two chaotic logistic maps and combined chaotic encryption methods to the two-dimensional FWT of images.
The encryption process involves two steps: firstly, chaotic sequences generated by the chaotic logistic maps are used to
permute and mask the intermediate results or array of FWT, the next step consist in changing the chaotic sequences or
the initial conditions of chaotic logistic maps among two intermediate results of the same row or column. Changing the
encryption key several times on the same row or column makes the cipher more robust against any attack. We tested
our algorithms on many biomedical images. We also used images from data bases to compare our algorithm to those
in literature. It comes out from statistical analysis and key sensitivity tests that our proposed image encryption schemeprovides an efficient and secure way for real-time encryption and transmission biomedical images.
E FFECTIVE P ROCESSING A ND A NALYSIS OF R ADIOTHERAPY I MAGESsipij
Ā
a-Si Electronic Portal Imaging Device (EPID) is an
important tool to verify the location of the radiat
ion
therapy beam with respect to the patient anatomy. B
ut, Electronic Portal Images (EPI) suffer from low
contrast. In order to have better in-treatment imag
es to extract relevant features of the anatomy, ima
ge
processing tools need to be integrated in the Radio
logy systems. The goal of this research work is to
inspect
several image processing techniques for contrast en
hancement of electronic portal images and gauge
parameters like mean, variance, standard deviation,
MSE, RMSE, entropy, PSNR, AMBE, normalised cross
correlation, average difference, structural content
(SC), maximum difference and normalised absolute
error (NAE) to study their visual quality improvem
ent. In addition, by adding salt and pepper noise,
Gaussian noise and motion blur, we calculate error
measurement parameters like Universal Image Quality
(UIQ) index, Enhancement Measurement Error (EME), P
earson Correlation Coefficient, SNR and Mean
Absolute error (MAE). The improved results point ou
t that image processing tools need to be incorporat
ed
into radiology for accurate delivery of dose
A STUDY FOR THE EFFECT OF THE EMPHATICNESS AND LANGUAGE AND DIALECT FOR VOIC...sipij
Ā
The signal sound contains many different features, including Voice Onset Time (VOT), which is a very
important feature of stop sounds in many languages. The only application of VOT values is stopping
phoneme subsets. This subset of consonant sounds is stop phonemes exist in the Arabic language, and in
fact, all languages. Very important subsets of Semitic languageās consonants are the Emphatic sounds. The
pronunciation of these sounds is hard and unique especially for less-educated Arabs and non-native Arabic
speakers. In the Arabic language, all emphatic sounds have their own non-emphatic counterparts that
differ only in the āemphaticnessā based on written letters. VOT can be utilized by the human auditory
system to distinguish between voiced and unvoiced stops such as /p/ and /b/ in English. Similarly, VOT can
be adopted by digital systems to classify and recognize stop sounds and their carried syllables for words of
any language. In addition, an analysis of any languageās phoneme set is very important in order to identify
the features of digital speech and language for automatic recognition, synthesis, processing, and
communication.
Analog signal processing approach for coarse and fine depth estimationsipij
Ā
Imaging and Image sensors is a field that is continuously evolving. There are new products coming into the
market every day. Some of these have very severe Size, Weight and Power constraints whereas other
devices have to handle very high computational loads. Some require both these conditions to be met
simultaneously. Current imaging architectures and digital image processing solutions will not be able to
meet these ever increasing demands. There is a need to develop novel imaging architectures and image
processing solutions to address these requirements. In this work we propose analog signal processing as a
solution to this problem. The analog processor is not suggested as a replacement to a digital processor but
it will be used as an augmentation device which works in parallel with the digital processor, making the
system faster and more efficient. In order to show the merits of analog processing two stereo
correspondence algorithms are implemented. We propose novel modifications to the algorithms and new
imaging architectures which, significantly reduces the computation time
Modified approach to transform arc from text to linear form text a preproces...sipij
Ā
Arc-form-text is an artistic-text which is quite common in several documents such as certificates,
advertisements and history documents. OCRs fail to read such arc-form-text and it is necessary to
transform the same to linear-form-text at preprocessing stage. In this paper, we present a modification to
an existing transformation model for better readability by OCRs. The method takes the segmented arcform-
text as input. Initially two concentric ellipses are approximated to enclose the arc-form-text and later
the modified transformation model transforms the text in arc-form to linear-form. The proposed method is
implemented on several upper semi-circular arc-form-text inputs and the readability of the transformed text
is analyzed with an OCR.
Enhancement of Medical Images using Histogram Based Hybrid TechniqueINFOGAIN PUBLICATION
Ā
Digital Image Processing is very important area of research. A number of techniques are available for image enhancement of gray scale images as well as color images. They work very efficiently for enhancement of the gray scale as well as color images. Important techniques namely Histogram Equalization, BBHE, RSWHE, RSWHE (recursion=2, gamma=No), AGCWD (Recursion=0, gamma=0) have been used quite frequently for image enhancement. But there are some shortcomings of the present techniques. The major shortcoming is that while enhancement, the brightness of the image deteriorates quite a lot. So there was need for some technique for image enhancement so that while enhancement was done, the brightness of the images does not go down. To remove this shortcoming, a new hybrid technique namely RESWHE+AGCWD (recursion=2, gamma=0 or 1) was proposed. The results of the proposed technique were compared with the existing techniques. In the present methodology, the brightness did not decrease during image enhancement. So the results and the technique was validated and accepted. The parameters via PSNR, MSE, AMBE etc. are taken for performance evaluation and validation of the proposed technique against the existing techniques which results in better outperform.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
Ā
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
MODIFIED HISTOGRAM EQUALIZATION FOR IMAGE CONTRAST ENHANCEMENT USING PARTICLE...ijcseit
Ā
A novel Modified Histogram Equalization (MHE) technique for contrast enhancement is proposed in this paper. This technique modifies the probability density function of an image by introducing constraints prior to the process of histogram equalization (HE). These constraints are formulated using two parameters which are optimized using swarm intelligence. This technique of contrast enhancement takes control over
the effect of HE so that it enhances the image without causing any loss to its details. A median adjustment factor is then added to the result to normalize the change in the luminance level after enhancement. This factor suppresses the effect of luminance change due to the presence of outlier pixels. The outlier pixels of highly deviated intensities have greater impact in changing the contrast of an image. This approach provides a convenient and effective way to control the enhancement process, while being adaptive to various types of images. Experimental results show that the proposed technique gives better results in
terms of Discrete Entropy and SSIM values than the existing histogram-based equalization methods.
Engineering Research Publication
Best International Journals, High Impact Journals,
International Journal of Engineering & Technical Research
ISSN : 2321-0869 (O) 2454-4698 (P)
www.erpublication.org
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IJETR, IJMCTR,
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An image enhancement method based on gabor filtering in wavelet domain and ad...nooriasukmaningtyas
Ā
The images are not always good enough to convey the proper information.
The image may be very bright or very dark sometime or it may be low
contrast or high contrast. Because of these reasons image enhancement plays
important role in digital image processing. In this paper we proposed an
image enhancement technique in which gabor and median filtering is
performed in wavelet domain and adaptive histogram equalization is
performed in spatial domain. Brightness and contrast are the two parameters
Keywords: used for analyzing the performance of the proposed method.
Contrast enhancement using various statistical operations and neighborhood pr...sipij
Ā
Histogram Equalization is a simple and effective contrast enhancement technique. In spite of its popularity
Histogram Equalization still have some limitations āproduces artifacts, unnatural images and the local
details are not considered, therefore due to these limitations many other Equalization techniques have been
derived from it with some up gradation. In this proposed method statistics play an important role in image
processing, where statistical operations is applied to the image to get the desired result such as
manipulation of brightness and contrast. Thus, a novel algorithm using statistical operations and
neighborhood processing has been proposed in this paper where the algorithm has proven to be effective in
contrast enhancement based on the theory and experiment.
COLOUR IMAGE ENHANCEMENT BASED ON HISTOGRAM EQUALIZATIONecij
Ā
Histogram equalization is a nonlinear technique for adjusting the contrast of an image using its histogram. It increases the brightness of a gray scale image which is different from the mean brightness of the original image. There are various types of Histogram equalization techniques like Histogram Equalization, Contrast Limited Adaptive Histogram Equalization, Brightness Preserving Bi Histogram Equalization, Dualistic Sub Image Histogram Equalization, Minimum Mean Brightness Error Bi Histogram Equalization, Recursive Mean Separate Histogram Equalization and Recursive Sub Image Histogram Equalization. In this paper, the histogram equalization approach of gray-level images is extended for colour images. The acquired image is converted into HSV (Hue, Saturation, Value). The image is then decomposed into two parts by using exposure threshold and then equalized them independently Over enhancement is also controlled in this method by using clipping threshold. For
measuring the performance of the enhanced image, entropy and contrast are calculated.
Optimized Histogram Based Contrast Limited Enhancement for Mammogram ImagesIDES Editor
Ā
Detection of breast cancer in its early stage is very
important in the field of medicine. Optimal Contrast
Enhancement is essential for the detection of mass and micro
calcification in mammogram images. The standard histogram
equalization is effective and simple method for contrast
enhancement but for medical images most of the time it
produces excessive contrast enhancement due to lack of control
for the level of enhancement. In this paper image
enhancement is considered as an optimization problem and
an optimization technique based on entropy and edge
information of the image is presented. The enhancement
function used in the paper is Contrast Limited Adaptive
Histogram Equalization (CLAHE) based on local contrast
modification (LCM). Its enhancement potential is tested by
sobel operator for the detection of microcalcification. Results
are compared with other enhancement techniques such as
Histogram Equalization, Unsharp Masking and CLAHE.
Developing 3D Viewing Model from 2D Stereo Pair with its Occlusion RatioCSCJournals
Ā
We intend to make a 3D model using a stereo pair of images by using a novel method of local matching in pixel domain for calculating horizontal disparities. We also find the occlusion ratio using the stereo pair followed by the use of The Edge Detection and Image SegmentatiON (EDISON) system, on one the images, which provides a complete toolbox for discontinuity preserving filtering, segmentation and edge detection. Instead of assigning a disparity value to each pixel, a disparity plane is assigned to each segment. We then warp the segment disparities to the original image to get our final 3D viewing Model.
Image Contrast Enhancement for Brightness Preservation Based on Dynamic Stret...CSCJournals
Ā
Histogram equalization is an efficient process often employed in consumer electronic systems for image contrast enhancement. In addition to an increase in contrast, it is also required to preserve the mean brightness of an image in order to convey the true scene information to the viewer. A conventional approach is to separate the image into sub-images and then process independently by histogram equalization towards a modified profile. However, due to the variations in image contents, the histogram separation threshold greatly influences the level of shift in mean brightness with respect to the uniform histogram in the equalization process. Therefore, the choice of a proper threshold, to separate the input image into sub-images, is very critical in order to preserve the mean brightness of the output image. In this research work, a dynamic range stretching approach is adopted to reduce the shift in output image mean brightness. Moreover, the computationally efficient golden section search algorithm is applied to obtain a proper separation into sub-images to preserve the mean brightness. Experiments were carried out on a large number of color images of natural scenes. Results, as compared to current available approaches, showed that the proposed method performed satisfactorily in terms of mean brightness preservation and enhancement in image contrast.
Comparison of Histogram Equalization Techniques for Image Enhancement of Gray...IJMER
Ā
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessmentā¦. And many more.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Ā
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
Ā
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
Ā
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Ā
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
Ā
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
ā¢ The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
ā¢ Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
ā¢ Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
ā¢ Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
Ā
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Ā
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Ā
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as āpredictable inferenceā.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
DevOps and Testing slides at DASA ConnectKari Kakkonen
Ā
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
CONTRAST ENHANCEMENT AND BRIGHTNESS PRESERVATION USING MULTIDECOMPOSITION HISTOGRAM EQUALIZATION
1. Signal & Image Processing : An International Journal (SIPIJ) Vol.4, No.3, June 2013
DOI : 10.5121/sipij.2013.4308 83
CONTRAST ENHANCEMENT AND
BRIGHTNESS PRESERVATION USING MULTI-
DECOMPOSITION HISTOGRAM EQUALIZATION
Sayali Nimkar, Sucheta Shrivastava and Sanal Varghese
Department of Electronics and Telecommunication Engineering,
Atharva college of Engineering, Maharashtra, India.
nimkar.sayali@gmail.com
suchetashrivastava@yahoo.co.in
sanalalice@gmail.com
ABSTRACT
Histogram Equalization (HE) has been an essential addition to the Image Enhancement world.
Enhancement techniques like Classical Histogram Equalization(CHE),Adaptive Histogram Equalization
(AHE), Bi-Histogram Equalization (BHE) and Recursive Mean Separate Histogram Equalization (RMSHE)
methods enhance contrast, brightness is not well preserved, which gives an unpleasant look to the final
image obtained. Thus, we introduce a novel technique Multi-Decomposition Histogram Equalization
(MDHE) to eliminate the drawbacks of the earlier methods. In MDHE, we have decomposed the input
image using a unique logic, applied CHE in each of the sub-images and then finally interpolated them in
correct order. The final image after MDHE gives us the best results based on contrast enhancement and
brightness preservation aspect compared to all other techniques mentioned above. We have calculated the
various parameters like PSNR, SNR, RMSE, MSE, etc. for every technique. Our results are well supported
by bar graphs, histograms and the parameter calculations at the end.
KEYWORDS
Classical histogram equalization, Histogram Equalization, Image Enhancement, Multi-decomposition
histogram equalization & Recursive mean separate histogram equalization
1. INTRODUCTION.
Image processing is avast and challenging domain with its applications in fields like medical,
aerial and satellite images, industrial applications, law enforcement, and science. Often the
quality of an image is more often linked to its contrast and brightness levels enhancing these
parameters will certainly give us the best result. Our main area of research is MDHE for
Histogram Equalization (HE).Here, HE is an image enhancement method that allocates the pixel
values evenly, thus developing a better picture. Image Enhancement majorly involves four key
parameters ā [1] brightness āBrightness can be modified by increasing āgammaā. Gamma is a
non-linear form of increase in brightness. [2] contrast- It is the separation between the dark and
bright areas of an image. Thus, increasing contrast increases darkness in dark areas and brightness
in bright areas. [3] Saturation- Saturation is increasing the separation between the shadows and
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highlights. [4] Sharpnessā It is related to edges, the contrast along the edges of a photo. Using
histogram equalization contrast can be enhanced. It is a straightforward and Invertible operator.
There are various histogram equalization techniques with their own advantages and
disadvantages. Our method Multide composition histogram equalization however is a unique
combination of CHE and types of Histogram Equalization.
2. HISTOGRAM EQUALIZATION TECHNIQUES
There are numerous methods by which Histogram of an image can be equalized. Depending upon
the area of Application, we can choose the different histogram equalization techniques. We will
see the following four types of Histogram Equalization methods in detail:
2.1 Classical Histogram Equalization (CHE)
2.2 Adaptive Histogram Equalization (AHE)
2.3 Bi- Histogram Equalization (BHE)
2.4 Recursive Mean Separate Histogram Equalization (RMSHE)
2.5 Multi-Decomposition Histogram Equalization (MDHE)
2.1 Classical Histogram Equalization
CHE is the fundamental technique for image processing, especially when gray level images are
considered. The aim of this method is to distribute the given number of gray levels over a range
uniformly, thus enhancing its contrast. The cumulative density function (CDF) is formulated by
the below mentioned expression:
The CHE tries to produce an output image with a flattened histogram, means a uniform
distribution. An image is formed by the dynamic range of values of gray levels. Basically, the
entire gray levels are denoted as 0 to L ā1.
Figure 1.Histogram after CHE Figure 2. Image after CHE
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2.1.1 Disadvantage
1. A disadvantage of this method is that it is undifferentiating between the various pixels,
that is, while increasing the contrast of its background, the signal gets distorted.
2. Histogram equalization often produces unrealistic and unlikely effects in photographs.
2.2 Adaptive Histogram Equalization
Adaptive Histogram Equalization (AHE) is used to improve contrast in images. It computes many
ordinary histograms, each one analogous with a section of the image. Thus, the output results in
each to redistributing the lightness values. It is appropriate to adjust the local contrast and to fetch
clear details.
On the other hand, AHE is responsible for over-amplifying noise in some homogeneous regions
of an image. To avoid this drawback, an advanced version of AHE, called Contrast Limited
Adaptive Histogram Equalization (CLAHE) is introduced.
Figure 3.Histogram after AHE Figure 4.Image after AHE
2.2.1 Disadvantage
ā¢ AHE has a behavior of amplifying noise, thus limiting its use for homogeneous figures.
ā¢ Its advanced form is contrast limited adaptive histogram equalization (CLAHE) that
eliminated the above problem.
ā¢ It also fails to retain the brightness with respect to the input image.
2.3 Bi-Histogram Equalization
The major basis of origination of this method is to overcome the drawback introduced by CHE.
Here, the original image is segmented twice i.e. into two sub-sections. This is done by dividing
the meangray level and then applying CHE method on each of the two sub-sectioned image. Its
objective is to produce method suitable for real-time applications. But again this method has the
same disadvantage as CHE by inputting unwanted signals.
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Figure 5. Histogram for BHE Figure 6.Image after BHE
2.4 Recursive Mean Separate Histogram Decomposition
An extended version of the BHE method proposed before, and named as recursive mean-separate
HE(RMSHE), proposes the following. Instead of decomposing the image only once, the RMSHE
method offers to perform image decomposition recursively, up to a scale r, generating 2r sub-
images. After, each one of these sub-images is independently enhanced using the CHE method.
Note that, computationally speaking, this method presents a problem: the number of decomposed
sub-histograms is a power of two.
Figure 7.Histogram of RMSHE Figure 8.Image of RMSHE
2.5 Multi-Decomposition Histogram Equalization
All the HE methods that we have covered prior to this, enhances the contrast of an image but are
unable to preserve its brightness. As a result, these methods can generate unnatural and non-
existing objects in the processed image. To eliminate these limitations, MDHE comes up with a
novel technique by decomposing the image into various small images. Then the image contrast
enhancement provided by CHE in each sub-image is less concentrated, leading the output image
to have a more likely and acceptable look.
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We have followed a four step process to carry out our technique effectively:
2.5.1 Multi-Decomposition of the image
An image is taken as input and divided into as many as 64 sub-images (it is flexible according to
application field). This is implemented using the spatial domain techniques. Functions are called
and the decomposition of the image is done.
2.5.2 Applying histogram based techniques
Now after dividing the image into 64 sub-images we apply Adaptive Histogram Equalization
method on each of the 64 sub-images to obtain enhanced sub-images. This is implemented by
using nested for loop.
2.5.3 Interpolating the image
The next part that is to be done is to interpolate all the sub-images in the right sequence, carefully
at the right place to get our Interpolated image. Though contrast enhancement has been achieved,
the image still lacks brightness preservation.
2.5.4 Brightness Preservation
To preserve the brightness we now apply a code according to which we can set a limit which
preserve brightness. Therefore, at the end of the entire process, we have obtained an image which
is contrast enhanced, brightness preserved as well as there is a natural look to the image. This
distinguishes our method from the others.
Thus the output images obtained by applying MDHE give amazing results, thus satisfying our
need to select this method. The images, bar graphs and histograms of the entire project are
attached in the conclusion. This will help the reader to understand the results in a much better and
effective way.
Figure 9.Equalized Histogram of MDHE Figure 10. Image of MDHE
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2.5.5 MDHE Flowchart:
Figure11. MDHE flowchart
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3. DISCUSSION
The performance of Multi-Decomposition Histogram Equalization (MDHE) is measured using
Image Enhancement Parameters such as Mean Absolute error (MAE), Pearson correlation
Coefficient (PCC), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Mean
Squared Error (MSE) and Root Mean squared error (RMSE). They help in evaluating the
effectiveness of the Image enhancement technique thus used.
3.1 Image Enhancement Parameters
3.1.1 Signal to Noise Ratio (SNR) is
It gives us the relation betweenrequired signal levelandsurrounding noise level. It is defined as
the ratio of signal power to noise power. A ratio of higher than 1:1 is regarded as a well signaled
ratio. It is measured in Decibels. Represented as:
3.1.2 Peak Signal to Noise Ratio (PSNR) is
It is the fraction of the optimum power level to a desired signal and the optimized power
of disturbance noise that affects the reliability of its representation expressed in logarithmic
decibel scale. It is generally used in measuring the quality of reconstruction done onlossy
compression codecs.
3.1.3 Mean Squared Error (MSE) is
It deals with the values obtained by an estimator thus calculating the divergence between
estimator values and optimum values of estimated quantity. MSE quantifies the average of
squares of the āerrorsā .The higher value of MSE the better.
3.1.4 Root Mean Square Error (RMSE) is
It calculates the root of power two for Standard Deviation. It measures the average magnitude of
the error. It is most useful when large errors are specifically undesirable. Given by:
3.1.5 Pearson Correlation Coefficient(PPMCC or PCC) is
In statistics, the Pearson product-moment correlation co-efficient is denoted by r and it measures
the correlation i.e. the strength of linear dependence between two variables X and Y, giving a
value between +1 and -1 inclusive.
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3.1.6 Universal Quality index for images (UIQ) is
It is calculated by structuring any image abnormality as an amalgamation of parameters such as
correlation loss, luminance distortion and contrast distortion. It performs considerably better than
the widely used distortion metric mean squared error. And it exhibits consistency with subjective
quality measurement on various models and experiments employed.
3.1.7 Mean Absolute Error (MAE) is
It is used to measure how close forecasts or our predictions are to the eventual outcomes. Mean
Absolute error is given by:
It amounts for the accuracy for continuous variables.
4. RESULT
The improvement in the quality and clarity in image is clearly seen in the figure of the Tree as
can be made out from above examples. Clearly, The Tree in MDHE looks well contrasted and
brightened. Another comparison of āSunset.jpgā with Table- I values highest in Pearson Co-
efficient and PSNR value for MDHE that give it the edge over others. For MSE and RMSHE, the
values of CHE are 125.2 and 11.89 respectively nearing to it is MDHE. With the other MAE,
SNR and UIQ values averaging to the finest. Rounding off to precision is the MDHE amongst the
other methods.
Figure 12. Comparison of āSunset.jpgā using various methods(a) CHE (b) AHE (c) BHE
(d) RMSHE (e) MDHE
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Figure 13. Graphical representation for the image āSunset.jpgā using various image enhancement
parameters.
TABLE 1: Comparison of parameters for āSunset.jpgā using various methods
5. CONCLUSIONS AND FUTURE APPLICATIONS
HE works on the four main elements of images: saturation, contrast, sharpness and brightness.
We focus on these four parameters and thus, enhance the quality of images. We obtain the desired
contrast levels, along with preservation of brightness and not only this, the natural look of the
input image is maintained. Future applications include photos obtained from satellite
communications ā since we obtain images from satellite that are distorted due to space
interference and dispersion losses. Other application fields are Medical field- X-Rays, Meteor
descriptions, Discoveries of Geo-stationary bodies, weather information, law enforcement that
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includes finger processing, surveillance camera processing. Science- enhancing electron
microscope image for readability.
REFERENCES
[1] Introduction-to-Matlab-Image-Processing-By-Dhananjay-K-Theckedath
[2] Digital Image Processing, Second Edition, Rafael C. Gonzalez, University of Tennessee, Richard E.
[3] http://homes.di.unimi.it/ferrari/ElabImm2011_12/EI2011_12_06_histo_eq_double.pdf
[4] http://www.mathworks.in/help/images/ref/histeq.html
[5] http://sebastien.hillaire.free.fr/index.php?option=com_content&view=article&id=59&Itemid=70
[6] http://grads.ece.mcmaster.ca/~shux/4tn4/sol_1.pdf
[7] http://stackoverflow.com/questions/15798742/histogram-equalization-method-without-use-of-histeq
[8] Vinay Kumar (Sept 2011), āContrast Enhancement using Sub- Regions Histogram Equalizationā
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[9] http://www.asee.org/documents/sections/middle-atlantic/spring-2010/Implementing-a-Histogram-
Equalization-Algorithm.pdf
[10] Ikpe1101.ikp.kfa-juelich.de/briefbook_data_analysis/node127.html
[11] S. D. Chen, and A. R. Ramli,(1997) āMinimum mean brightness error bihistogram equalization in
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[12] Y. T. Kim, āContrast enhancement using brightness preserving bihistogram equalization,ā IEEE
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[13] http.//fourier.eng.hmc.edu/e161/lectures/contrast_transform/node2.html
[14] http://www.mathworks.in/help/images/ref/histeq.html
[15] Soong-Der Chen, Abd. RahmanRamli, (2004) :āPreserving Brightness in Histogram Equalization
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[16] Yaara David, RaāananDekell, YonathanDekell (2009): āHistogram Equalization For SIPERā ,
sipl.technion.ac.il/Info/Teaching_Projects_Histogram-Equal_e.shtml
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AUTHORS
Sanal Varghese : Completed bachelors at Atharva College Of Engineering. Working at
Infosys Ltd, Mysore. Areas of research comprise of Image processing, Wireless networks
and Data communication.
Sayali Nimkar : Pursuing MS in Electrical Engineering at University of North Carolina,
Charlotte.Interests include Signal processing and Wireless sensor networks.
Sucheta Shrivastava : Student at Atharva college of engineering. Pursuing masters.
Interests include Signal & Image processing, semiconductors, wired and wireless
networking and optics .