This presentation was made on a thesis paper for my M.Sc academic curriculum. Color Guided Thermal image Super Resolution Technic is declared here.This paper is collected from IEEE.Publish in 2016.
Image Denoising Using Earth Mover's Distance and Local HistogramsCSCJournals
In this paper an adaptive range and domain filtering is presented. In the proposed method local histograms are computed to tune the range and domain extensions of bilateral filter. Noise histogram is estimated to measure the noise level at each pixel in the noisy image. The extensions of range and domain filters are determined based on pixel noise level. Experimental results show that the proposed method effectively removes the noise while preserves the details. The proposed method performs better than bilateral filter and restored test images have higher PSNR than those obtained by applying popular Bayesshrink wavelet denoising method.
Fusion of Wavelet Coefficients from Visual and Thermal Face Images for Human ...CSCJournals
In this paper we present a comparative study on fusion of visual and thermal images using different wavelet transformations. Here, coefficients of discrete wavelet transforms from both visual and thermal images are computed separately and combined. Next, inverse discrete wavelet transformation is taken in order to obtain fused face image. Both Haar and Daubechies (db2) wavelet transforms have been used to compare recognition results. For experiments IRIS Thermal/Visual Face Database was used. Experimental results using Haar and Daubechies wavelets show that the performance of the approach presented here achieves maximum success rate of 100% in many cases.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
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Call us at : 08263069601
(Prefer mailing. Call in emergency )
Image Denoising Using Earth Mover's Distance and Local HistogramsCSCJournals
In this paper an adaptive range and domain filtering is presented. In the proposed method local histograms are computed to tune the range and domain extensions of bilateral filter. Noise histogram is estimated to measure the noise level at each pixel in the noisy image. The extensions of range and domain filters are determined based on pixel noise level. Experimental results show that the proposed method effectively removes the noise while preserves the details. The proposed method performs better than bilateral filter and restored test images have higher PSNR than those obtained by applying popular Bayesshrink wavelet denoising method.
Fusion of Wavelet Coefficients from Visual and Thermal Face Images for Human ...CSCJournals
In this paper we present a comparative study on fusion of visual and thermal images using different wavelet transformations. Here, coefficients of discrete wavelet transforms from both visual and thermal images are computed separately and combined. Next, inverse discrete wavelet transformation is taken in order to obtain fused face image. Both Haar and Daubechies (db2) wavelet transforms have been used to compare recognition results. For experiments IRIS Thermal/Visual Face Database was used. Experimental results using Haar and Daubechies wavelets show that the performance of the approach presented here achieves maximum success rate of 100% in many cases.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call us at : 08263069601
(Prefer mailing. Call in emergency )
The Effects of Segmentation Techniques in Digital Image Based Identification ...TELKOMNIKA JOURNAL
This paper presents the effects of segmentation techniques in the identification of Ethiopian
coffee variety. In Ethiopia, coffee varieties are classified based on their growing region. The most widely
coffee growing regions in Ethiopia are Bale, Harar, Jimma, Limu, Sidamo and Welega. Coffee beans of
these regions very in color shape and texture. We investigated various segmentation techniques for
efficient coffee beans variety identification system. Images of six different coffee beans varieties in Oromia
and Southern Ethiopia were acquired and analyzed. For this study Otsu, Fuzzy-C-Means (FCM) and Kmeans
segmentation techniques are considered. For classification of the varieties of Ethiopian coffee
beans back propagation neural network (BPNN) is used. From the experiment 94.54% accuracy is
achieved when BPNN is used on FCM segmentation technique.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
or
call us at : 08263069601
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSIONacijjournal
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more perceptible to human eye. Multispectral Image fusion is the process of combining
images optically acquired in more than one spectral band. In this paper, we present a pixel-level image
fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um),
mid infrared(1.55-1.75um),thermal- infrared(10.4-12.5um) and mid infrared(2.08-2.35um) to give a
composite colour image. The work coalesces a fusion technique that involves linear transformation based
on Cholesky decomposition of the covariance matrix of source data that converts multispectral source
images which are in grayscale into colour image. This work is composed of different segments that
includes estimation of covariance matrix of images, cholesky decomposition and transformation ones.
Finally, the fused colour image is compared with the fused image obtained by PCA transformation.
Comparison of Segmentation Algorithms and Estimation of Optimal Segmentation ...Pinaki Ranjan Sarkar
Recent advancement in sensor technology allows very high spatial resolution along with multiple spectral bands. There are many studies, which highlight that Object Based Image Analysis(OBIA) is more accurate than pixel-based classification for high resolution(< 2m) imagery. Image segmentation is a crucial step for OBIA and it is a very formidable task to estimate optimal parameters for segmentation as it does not have any unique solution. In this paper, we have studied different segmentation algorithms (both mono-scale and multi-scale) for different terrain categories and showed how the segmented output depends on upon various parameters. Later, we have introduced a novel method to estimate optimal segmentation parameters. The main objectives of this study are to highlight the effectiveness of presently available segmentation techniques on very high-resolution satellite data and to automate segmentation process. Pre-estimation of segmentation parameter is more practical and efficient in OBIA. Assessment of segmentation algorithms and estimation of segmentation parameters are examined based on the very high-resolution multi-spectral WorldView-3(0.3m, PAN sharpened) data.
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
IMAGE SEGMENTATION BY USING THRESHOLDING TECHNIQUES FOR MEDICAL IMAGEScseij
Image binarization is the process of separation of pixel values into two groups, black as background and
white as foreground. Thresholding can be categorized into global thresholding and local thresholding. This
paper describes a locally adaptive thresholding technique that removes background by using local mean
and standard deviation. Most common and simplest approach to segment an image is using thresholding.
In this work we present an efficient implementation for threshoding and give a detailed comparison of
Niblack and sauvola local thresholding algorithm. Niblack and sauvola thresholding algorithm is
implemented on medical images. The quality of segmented image is measured by statistical parameters:
Jaccard Similarity Coefficient, Peak Signal to Noise Ratio (PSNR).
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Image fusion is a technique used to integrate a highresolution
panchromatic image with multispectral low-resolution
image to produce a multispectral high-resolution image, that
contains both the spatial information of the panchromatic highresolution
image and the color information of the multispectral
image .Although an increasing number of high-resolution images
are available along with sensor technology development, the
process of image fusion is still a popular and important method to
interpret the image data for obtaining a more suitable image for a
variety of applications, like visual interpretation and digital
classification. To get the complete information from the single
image we need to have a method to fuse the images. In the current
paper we are going to propose a method that uses hybrid of
wavelets for Image fusion.
The Effects of Segmentation Techniques in Digital Image Based Identification ...TELKOMNIKA JOURNAL
This paper presents the effects of segmentation techniques in the identification of Ethiopian
coffee variety. In Ethiopia, coffee varieties are classified based on their growing region. The most widely
coffee growing regions in Ethiopia are Bale, Harar, Jimma, Limu, Sidamo and Welega. Coffee beans of
these regions very in color shape and texture. We investigated various segmentation techniques for
efficient coffee beans variety identification system. Images of six different coffee beans varieties in Oromia
and Southern Ethiopia were acquired and analyzed. For this study Otsu, Fuzzy-C-Means (FCM) and Kmeans
segmentation techniques are considered. For classification of the varieties of Ethiopian coffee
beans back propagation neural network (BPNN) is used. From the experiment 94.54% accuracy is
achieved when BPNN is used on FCM segmentation technique.
Dear students get fully solved assignments
Send your semester & Specialization name to our mail id :
help.mbaassignments@gmail.com
or
call us at : 08263069601
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSIONacijjournal
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of
image fusion algorithms that would combine the image from these sensors in an efficient way to give an
image that is more perceptible to human eye. Multispectral Image fusion is the process of combining
images optically acquired in more than one spectral band. In this paper, we present a pixel-level image
fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um),
mid infrared(1.55-1.75um),thermal- infrared(10.4-12.5um) and mid infrared(2.08-2.35um) to give a
composite colour image. The work coalesces a fusion technique that involves linear transformation based
on Cholesky decomposition of the covariance matrix of source data that converts multispectral source
images which are in grayscale into colour image. This work is composed of different segments that
includes estimation of covariance matrix of images, cholesky decomposition and transformation ones.
Finally, the fused colour image is compared with the fused image obtained by PCA transformation.
Comparison of Segmentation Algorithms and Estimation of Optimal Segmentation ...Pinaki Ranjan Sarkar
Recent advancement in sensor technology allows very high spatial resolution along with multiple spectral bands. There are many studies, which highlight that Object Based Image Analysis(OBIA) is more accurate than pixel-based classification for high resolution(< 2m) imagery. Image segmentation is a crucial step for OBIA and it is a very formidable task to estimate optimal parameters for segmentation as it does not have any unique solution. In this paper, we have studied different segmentation algorithms (both mono-scale and multi-scale) for different terrain categories and showed how the segmented output depends on upon various parameters. Later, we have introduced a novel method to estimate optimal segmentation parameters. The main objectives of this study are to highlight the effectiveness of presently available segmentation techniques on very high-resolution satellite data and to automate segmentation process. Pre-estimation of segmentation parameter is more practical and efficient in OBIA. Assessment of segmentation algorithms and estimation of segmentation parameters are examined based on the very high-resolution multi-spectral WorldView-3(0.3m, PAN sharpened) data.
To get this project in ONLINE or through TRAINING Sessions,
Contact:JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Pillar, Chennai -83. Landmark: Next to Kotak Mahendra Bank. Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry -9. Landmark: Next to VVP Nagar Arch. Mobile: (0) 9952649690 , Email: jpinfotechprojects@gmail.com, web: www.jpinfotech.org Blog: www.jpinfotech.blogspot.com
IMAGE SEGMENTATION BY USING THRESHOLDING TECHNIQUES FOR MEDICAL IMAGEScseij
Image binarization is the process of separation of pixel values into two groups, black as background and
white as foreground. Thresholding can be categorized into global thresholding and local thresholding. This
paper describes a locally adaptive thresholding technique that removes background by using local mean
and standard deviation. Most common and simplest approach to segment an image is using thresholding.
In this work we present an efficient implementation for threshoding and give a detailed comparison of
Niblack and sauvola local thresholding algorithm. Niblack and sauvola thresholding algorithm is
implemented on medical images. The quality of segmented image is measured by statistical parameters:
Jaccard Similarity Coefficient, Peak Signal to Noise Ratio (PSNR).
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Image fusion is a technique used to integrate a highresolution
panchromatic image with multispectral low-resolution
image to produce a multispectral high-resolution image, that
contains both the spatial information of the panchromatic highresolution
image and the color information of the multispectral
image .Although an increasing number of high-resolution images
are available along with sensor technology development, the
process of image fusion is still a popular and important method to
interpret the image data for obtaining a more suitable image for a
variety of applications, like visual interpretation and digital
classification. To get the complete information from the single
image we need to have a method to fuse the images. In the current
paper we are going to propose a method that uses hybrid of
wavelets for Image fusion.
COLOUR IMAGE REPRESENTION OF MULTISPECTRAL IMAGE FUSION acijjournal
ABSTRACT
The availability of imaging sensors operating in multiple spectral bands has led to the requirement of image fusion algorithms that would combine the image from these sensors in an efficient way to give an image that is more perceptible to human eye. Multispectral Image fusion is the process of combining images optically acquired in more than one spectral band. In this paper, we present a pixel-level image fusion that combines four images from four different spectral bands namely near infrared(0.76-0.90um), mid infrared(1.55-1.75um),thermal- infrared(10.4-12.5um) and mid infrared(2.08-2.35um) to give a composite colour image. The work coalesces a fusion technique that involves linear transformation based on Cholesky decomposition of the covariance matrix of source data that converts multispectral source images which are in grayscale into colour image. This work is composed of different segments that includes estimation of covariance matrix of images, cholesky decomposition and transformation ones. Finally, the fused colour image is compared with the fused image obtained by PCA transformation.
Performance Analysis and Optimization of Nonlinear Image Restoration Techniqu...CSCJournals
Abstract: This paper is concerned with critical performance analysis of spatial nonlinear restoration techniques for continuous tone images from various fields (Medical images, Natural images, and others images).The performance of the nonlinear restoration methods is provided with possible combination of various additive noises and images from diversified fields. Efficiency of nonlinear restoration techniques according to difference distortion and correlation distortion metrics is computed.Tests performed on monochrome images, with various synthetic and real-life degradations, without and with noise, in single frame scenarios, showed good results, both in subjective terms and in terms of the increase of signal to noise ratio(ISNR) measure. The comparison of the present approach with previous individual methods in terms of mean square error, peak signal-to-noise ratio, and normalised absolute error is also provided. In comparisons with other state of art methods, our approach yields better to optimization, and shows to be applicable to a much wider range of noises. We discuss how experimental results are useful to guide to select the effective combination. Promising performance analysed through computer simulation and compared to give critical analysis.
A New Approach of Medical Image Fusion using Discrete Wavelet TransformIDES Editor
MRI-PET medical image fusion has important
clinical significance. Medical image fusion is the important
step after registration, which is an integrative display method
of two images. The PET image shows the brain function with
a low spatial resolution, MRI image shows the brain tissue
anatomy and contains no functional information. Hence, a
perfect fused image should contains both functional
information and more spatial characteristics with no spatial
& color distortion. The DWT coefficients of MRI-PET
intensity values are fused based on the even degree method
and cross correlation method The performance of proposed
image fusion scheme is evaluated with PSNR and RMSE and
its also compared with the existing techniques.
A Novel Color Image Fusion for Multi Sensor Night Vision ImagesEditor IJCATR
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.
An Efficient Image Denoising Approach for the Recovery of Impulse NoisejournalBEEI
Image noise is one of the key issues in image processing applications today. The noise will affect the quality of the image and thus degrades the actual information of the image. Visual quality is the prerequisite for many imagery applications such as remote sensing. In recent years, the significance of noise assessment and the recovery of noisy images are increasing. The impulse noise is characterized by replacing a portion of an image’s pixel values with random values Such noise can be introduced due to transmission errors. Accordingly, this paper focuses on the effect of visual quality of the image due to impulse noise during the transmission of images. In this paper, a hybrid statistical noise suppression technique has been developed for improving the quality of the impulse noisy color images. We further proved the performance of the proposed image enhancement scheme using the advanced performance metrics.
Image fusion can be defined as the process by which several images or some of their features
are combined together to form a fused image. Its aim is to combine maximum information
from multiple images of the same scene such that the obtained new image is more suitable for
human visual and machine perception or further image processing and analysis tasks. The
fusion of images acquired from dissimilar modalities or instrument has been successfully used
for remote sensing images. The biomedical image fusion plays an important role in analysis
towards clinical application which can support more accurate information for physician to
diagnose different diseases.
With the improvements in Image acquisition systems there is an increasing concentration in the direction of
High Dynamic Range (HDR) images where the amount of intensity levels varies among 2 to 10,000. With these
numerous intensity levels the exact representation of luminance variations is entirely possible. But, because the
normal display devices are shaped to exhibit Low Dynamic Range (LDR) images, there is necessary to translate
HDR images to LDR images without down significant image structures in HDR images. In this paper four TMOs
like Reinhard, Gamma and color correction TMOs are evaluated .In this paper two novel TMOs are projected.
Keywords — HDR, LDR, Tone mapping, Gamma correction.
PCA & CS based fusion for Medical Image FusionIJMTST Journal
Compressive sampling (CS), also called Compressed sensing, has generated a tremendous amount of excitement in the image processing community. It provides an alternative to Shannon/ Nyquist sampling when the signal under acquisition is known to be sparse or compressible. In this paper, we propose a new efficient image fusion method for compressed sensing imaging. In this method, we calculate the two dimensional discrete cosine transform of multiple input images, these achieved measurements are multiplied with sampling filter, so compressed images are obtained. we take inverse discrete cosine transform of them. Finally, fused image achieves from these results by using PCA fusion method. This approach also is implemented for multi-focus and noisy images. Simulation results show that our method provides promising fusion performance in both visual comparison and comparison using objective measures. Moreover, because this method does not need to recovery process the computational time is decreased very much.
Mr image compression based on selection of mother wavelet and lifting based w...ijma
Magnetic Resonance (MR) image is a medical image technique required enormous data to be stored and
transmitted for high quality diagnostic application. Various algorithms have been proposed to improve the
performance of the compression scheme. In this paper we extended the commonly used algorithms to image
compression and compared its performance. For an image compression technique, we have linked different
wavelet techniques using traditional mother wavelets and lifting based Cohen-Daubechies-Feauveau
wavelets with the low-pass filters of the length 9 and 7 (CDF 9/7) wavelet transform with Set Partition in
Hierarchical Trees (SPIHT) algorithm. A novel image quality index with highlighting shape of histogram
of the image targeted is introduced to assess image compression quality. The index will be used in place of
existing traditional Universal Image Quality Index (UIQI) “in one go”. It offers extra information about
the distortion between an original image and a compressed image in comparisons with UIQI. The proposed
index is designed based on modelling image compression as combinations of four major factors: loss of
correlation, luminance distortion, contrast distortion and shape distortion. This index is easy to calculate
and applicable in various image processing applications. One of our contributions is to demonstrate the
choice of mother wavelet is very important for achieving superior wavelet compression performances based
on proposed image quality indexes. Experimental results show that the proposed image quality index plays
a significantly role in the quality evaluation of image compression on the open sources “BrainWeb:
Simulated Brain Database (SBD) ”.
Single image super resolution with improved wavelet interpolation and iterati...iosrjce
IOSR journal of VLSI and Signal Processing (IOSRJVSP) is a double blind peer reviewed International Journal that publishes articles which contribute new results in all areas of VLSI Design & Signal Processing. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced VLSI Design & Signal Processing concepts and establishing new collaborations in these areas.Design and realization of microelectronic systems using VLSI/ULSI technologies require close collaboration among scientists and engineers in the fields of systems architecture, logic and circuit design, chips and wafer fabrication, packaging, testing and systems applications. Generation of specifications, design and verification must be performed at all abstraction levels, including the system, register-transfer, logic, circuit, transistor and process levels.
ADAPTIVE PDE-BASED MEDIAN FILTER FOR THE RESTORATION OF HIGH-DENSITY IMPULSE ...ijait
This proposed Adaptive PDE-based Median Filter (APM Filter) is devised to suppress the high-density fixed-value impulse noise that degrades the quality of images. It is apparent from the quantitative measure - the PSNR values and the qualitative measure - the human visual perception that the noise suppression potential of APM filter is significantly higher. This filter broadly finds application in the areas, such as image/video documentation, medical imaging and remote sensing.
AN ADAPTIVE THRESHOLD SEGMENTATION FOR DETECTION OF NUCLEI IN CERVICAL CELLS ...cscpconf
PAP smear test is the most efficient and easy procedure to detect any abnormality in cervical cells. It becomes difficult for the cytologist to analyse a large set of PAP smear test images
when there is a rapid increase in the incidence of cervical cancer. On the replacement, image analysis could swap manual interpretation. This paper proposes a method for the detection of cervical cells in pap smear images using wavelet based thresholding. First, Wiener filter is used for smoothing to suppress the noise and to improve the contrast of the image. Second, optimal threshold is been obtained for segmenting the cell by various Wavelet shrinkage techniques like VisuShrink, BayesShrink and SureShrink thresholding which segment the foreground from the background and detect cell component like nucleus from the clustered cell images. From the
results, it is proved that the performance of the adaptive Wiener filter with combination of SureShrink thresholding performs better in terms of threshold values and Mean Squared Error
than the other comparative methods. The succeeding research work can be carried out based on the size of the segmented nucleus which therefore helps in differentiating abnormality among the cells.
An adaptive threshold segmentation for detection of nuclei in cervical cells ...csandit
PAP smear test is the most efficient and easy procedure to detect any abnormality in cervical
cells. It becomes difficult for the cytologist to analyse a large set of PAP smear test images
when there is a rapid increase in the incidence of cervical cancer. On the replacement, image
analysis could swap manual interpretation. This paper proposes a method for the detection of
cervical cells in pap smear images using wavelet based thresholding. First, Wiener filter is used
for smoothing to suppress the noise and to improve the contrast of the image. Second, optimal
threshold is been obtained for segmenting the cell by various Wavelet shrinkage techniques like
VisuShrink, BayesShrink and SureShrink thresholding which segment the foreground from the
background and detect cell component like nucleus from the clustered cell images. From the
results, it is proved that the performance of the adaptive Wiener filter with combination of
SureShrink thresholding performs better in terms of threshold values and Mean Squared Error
than the other comparative methods. The succeeding research work can be carried out based on
the size of the segmented nucleus which therefore helps in differentiating abnormality among
the cells.
Similar to Color Guided Thermal image Super Resolution (20)
Application-Aware Big Data Deduplication in Cloud EnvironmentSafayet Hossain
Here I present a paper based on Application-Aware Big Data Deduplication in Cloud Environment. It is published on IEEE on 31 May 2017.
Abstract of this paper:
Deduplication has become a widely deployed technology in cloud data centers to improve IT resources efficiency. However, traditional techniques face a great challenge in big data deduplication to strike a sensible tradeoff between the conflicting goals of scalable deduplication throughput and high duplicate elimination ratio. We propose AppDedupe, an application-aware scalable inline distributed deduplication framework in cloud environment, to meet this challenge by exploiting application awareness, data similarity and locality to optimize distributed deduplication with inter-node two-tiered data routing and intra-node application-aware deduplication. It first dispenses application data at file level with an application-aware routing to keep application locality, then assigns similar application data to the same storage node at the super-chunk granularity using a handprinting-based stateful data routing scheme to maintain high global deduplication efficiency, meanwhile balances the workload across nodes. AppDedupe builds application-aware similarity indices with super-chunk handprints to speedup the intra-node deduplication process with high efficiency. Our experimental evaluation of AppDedupe against state-of-the-art, driven by real-world datasets, demonstrates that AppDedupe achieves the highest global deduplication efficiency with a higher global deduplication effectiveness than the high-overhead and poorly scalable traditional scheme, but at an overhead only slightly higher than that of the scalable but low duplicate-elimination-ratio approaches.
Link of this paper:
https://ieeexplore.ieee.org/document/7936577
Find Transitive closure of a Graph Using Warshall's AlgorithmSafayet Hossain
Here I actually describe how we can find transitive closure of a graph using warshall' algorithm. It will be easy to learn about transitive closure, their time complexity, count space complexity.
Information technology (IT) is the application of computers to store, study, retrieve, transmit, and manipulate data, or information, often in the context of a business or other enterprise. IT is considered a subset of information and communications technology (ICT).
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
CW RADAR, FMCW RADAR, FMCW ALTIMETER, AND THEIR PARAMETERSveerababupersonal22
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3. COLOR GUIDED THERMAL IMAGE SUPER
RESOLUTION
Xiaohui Chen(1) , Guangtao Zhai1 , Jia Wang (2) ,Chunjia Hu (1) and
Yuanchun Chen(2)
Institute of Image Communication and Information Processing, Shanghai Jiao Tong
University, Shanghai, China
• 1 {(fxhuichen.cn,zhaiguangtao,huchunjia.sjtug)@gmail.com},
2{(fjiawang,chenyuanchung)@sjtu.edu.cn}
4. ABSTRACT OF THIS PAPER
Use the visible camera as a guidance to supper resolution the IR
images.
Setup a prototype of the IR-color multi-sensor imaging system
Construct a dataset including videos collected from different scenes
for further research.
Present their color guided algorithm which is suitable for this kind of
super resolution problem.
5. INTRODUCTION
A registered high-quality texture image can provide significant information to
enhance the infrared image due to their strong correlation.
Use a guided filter[1] in the correlated region between IR image and color image.
Construct a cost volume of IR image values probability based on the input image.
A best cost selecting and sub-pixel refinement are taken to produce a refined IR
image.
The output image is got after a outlier detection.
1. Z. Zhang, “A flexible new technique for camera calibration,” Pattern
6. SYSTEM SETUP AND PREPROCESSING
System Setting
Camera Calibration and Color- IR Registration
Proposed Approach
8. CAMERA CALIBRATION AND COLOR-IR
REGISTRATION
First they tried to use mature algorithm proposed by Zhang [1].
Then finally they used the method proposed by Han [2].
1. Z. Zhang, “A flexible new technique for camera calibration,” Pattern
2. J. Han, E. Pauwels, and P. de Zeeuw, “Visible and infrared image registration employing line-based geometric analysis,” in Computational Intelligence for Multimedia
Understanding. Springer, 2011, pp. 114–125.
11. COST VOLUME
A coarse cost volume is first built to preserve the sub-pixel accuracy of the input
IR image based on current IR image estimation Ii
As the differences get large, the cost function should become constant in order to
make candidate IR values vary a lot because the current values are not
necessarily correct. The truncated quadric model is one of available function.
Thus the cost function can be defined as following:
Where L is the search range,ƞ is a constant, d means a candidate IR image.
12. GUIDANCE SELECTION
The infrared image discontinuities often co-occur with color or
brightness changes within the associated camera image of the
same scene.
A color camera is a combination of three sensors: red, green, and
blue. Different channels have different correlation with IR image. To
verify this, we calculate the PSNR and SSIM between different
channels and the corresponding IR images in our database.
14. THE CORRELATED REGION
To avoid wrong texture transfer, they only applied guided
filter in their correlated region. The correlated region could
be calculated by their cross-correlation in a small patch. If
the value is bigger than the threshold T, the point is regard
as one point of correlated region. The others is in
uncorrelated region.
15. GUIDED FILTER IN CORRELATED REGION
The guided image filter is a novel explicit image filter. It
not only has good edge-preserving smoothing properties
like the bilateral filter[1], but also makes the filtering output
more structured and keeps more details than other edge-
preserving filters.
1. C. Tomasi and R. Manduchi, “Bilateral filtering for gray and color
16. SUB-PIXEL ESTIMATION
As we mentioned in Cost volume, the discontinuity of cost
function and limited search range result in the
discontinuity of IR images. In order to eliminate this effect,
quadratic polynomial interpolation is adopted here to
approximate the cost function.
17. OUTLIER DETECTION
Outlier detection is used here to solve the problem that sometimes
black points may appear where tiny edges only exist in IR image.
we use outlier detection method to find the incorrect points and then
we adopt a median filter around them to eliminate outlier points.
19. EXPERIMENTAL RESULTS
Experiment results. From left to right are the suitable channel images, the ground truth IR images, the bicubic
interpolation results, the result using JBU and the results using our proposed algorithm. The result images has
been upsampled by a factor of 1:4 (in each axis).
21. ACKNOWLEDGEMENT
• This work was supported in part by the National Science Foundation of China
under Grants 61422112, 61371146, 61521062, 61527804, and National High-tech
R&D Program of China under Grant 2015AA01590.