Increase of number of the nodes in the wireless computing environment leads to different issues
like power, data rate, QoS, simulators and security. Among these the security is the peak issue
faced by most of the wireless networks. Especially networks without having a centralized system
(MANETS) is facing severe security issues. One of the major security issues is the wormhole
attack while finding the shortest path. The aim of this paper is to propose an algorithm to find a
secure shortest path against wormhole attack. Existing algorithms are mainly concentrated on
detecting the malicious node but they are hardware specific like directional antennas and
synchronized clocks. But the proposed algorithm is both software and hardware specific.
RTOS is included to make the ad hoc network a real time application.
Discrete cosine transform (DCT) is a widely used tool in image and video compression applications. Recently, the high-throughput DCT designs have been adopted to fit the requirements of real-time application.
Operating the shifting and addition in parallel, an error-compensated adder-tree (ECAT) is proposed to deal with the truncation errors and to achieve low-error and high-throughput discrete cosine transform (DCT) design. Instead of the 12 bits used in previous works, 9-bit distributed arithmetic. DA-based DCT core with an error-compensated adder-tree (ECAT). The proposed ECAT operates shifting and addition in parallel by unrolling all the words required to be computed. Furthermore, the error-compensated circuit alleviates the truncation error for high accuracy design. Based on low-error ECAT, the DA-precision in this work is chosen to be 9 bits instead of the traditional 12 bits. Therefore, the hardware cost is reduced, and the speed is improved using the proposed ECAT.
A Novel Algorithm for Watermarking and Image Encryption cscpconf
Digital watermarking is a method of copyright protection of audio, images, video and text. We
propose a new robust watermarking technique based on contourlet transform and singular value
decomposition. The paper also proposes a novel encryption algorithm to store a signed double
matrix as an RGB image. The entropy of the watermarked image and correlation coefficient of
extracted watermark image is very close to ideal values, proving the correctness of proposed
algorithm. Also experimental results show resiliency of the scheme against large blurring attack
like mean and gaussian filtering, linear filtering (high pass and low pass filtering) , non-linear
filtering (median filtering), addition of a constant offset to the pixel values and local exchange of pixels .Thus proving the security, effectiveness and robustness of the proposed watermarking algorithm.
IMAGE CODING THROUGH ZTRANSFORM WITH LOW ENERGY AND BANDWIDTH (IZEB) cscpconf
In this paper a Z-transform based image coding technique has been proposed. The techniques uses energy efficient and low bandwidth based invisible data embedding with a minimal
computational complexity. In this technique near about half the bandwidth is required compared to the traditional Z–transform while transmitting the multimedia content such as images through network.
Image coding through ztransform with low energy and bandwidth (izeb)csandit
In this paper a Z-transform based image coding technique has been proposed. The techniques
uses energy efficient and low bandwidth based invisible data embedding with a minimal
computational complexity. In this technique near about half the bandwidth is required
compared to the traditional Z–transform while transmitting the multimedia content such as
images through network.
This document proposes an enhanced adaptive data hiding technique in the discrete wavelet transform (DWT) domain. It begins with background information on DWT and quantization techniques like uniform and adaptive quantization. It then describes how data can be embedded in the non-zero DWT coefficients after adaptive quantization. Specifically, it embeds secret data by modifying the quantized DWT coefficients in a way that minimizes distortion to maintain good visual quality of the cover image. The goal is to improve data hiding capacity while preserving the quality of the cover image as measured by metrics like peak signal-to-noise ratio (PSNR) and the human visual system (HVS).
Non standard size image compression with reversible embedded waveletseSAT Publishing House
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.
A Novel Facial Recognition Method using Discrete Wavelet Transform Multiresolution Pyramid..........1
G. Preethi
Enhancing Energy Efficiency in WSN using Energy Potential and Energy Balancing Concepts ................. 9
Sheetalrani R. Kawale
DNS: Dynamic Network Selection Scheme for Vertical Handover in Heterogeneous Wireless Networks
.................................................................................................................................................................... 19
M. Deva Priya, D. Prithviraj and Dr. M. L Valarmathi
Implementation of Image based Flower Classification System................................................................ 35
Tanvi Kulkarni and Nilesh. J. Uke
A Survey on Knowledge Analytics of Text from Social Media .................................................................. 45
Dr. J. Akilandeswari and K. Rajalakshm
Progression of String Matching Practices in Web Mining – A Survey ..................................................... 62
Kaladevi A. C. and Nivetha S. M.
Virtualizing the Inter Communication of Clouds ...............................................................................72
Subho Roy Chowdhury, Sambit Kumar Patel, Ankita Vinod Mandekar and G. Usha Devi
Tracing the Adversaries using Packet Marking and Packet Logging ....................................................... 86
A. Santhosh and Dr. J. Senthil Kumar
An Improved Energy Efficient Clustering Algorithm for Non Availability of Spectrum in Cognitive Radio
Users ....................................................................................................................................................... 101
EFFICIENT IMAGE COMPRESSION USING LAPLACIAN PYRAMIDAL FILTERS FOR EDGE IMAGESijcnac
This project presents a new image compression technique for the coding of retinal and
fingerprint images. Retinal images are used to detect diseases like diabetes or
hypertension. Fingerprint images are used for the security purpose. In this work, the
contourlet transform of the retinal and fingerprint image is taken first. The coefficients of
the contourlet transform are quantized using adaptive multistage vector quantization
scheme. The number of code vectors in the adaptive vector quantization scheme depends
on the dynamic range of the input image.
Discrete cosine transform (DCT) is a widely used tool in image and video compression applications. Recently, the high-throughput DCT designs have been adopted to fit the requirements of real-time application.
Operating the shifting and addition in parallel, an error-compensated adder-tree (ECAT) is proposed to deal with the truncation errors and to achieve low-error and high-throughput discrete cosine transform (DCT) design. Instead of the 12 bits used in previous works, 9-bit distributed arithmetic. DA-based DCT core with an error-compensated adder-tree (ECAT). The proposed ECAT operates shifting and addition in parallel by unrolling all the words required to be computed. Furthermore, the error-compensated circuit alleviates the truncation error for high accuracy design. Based on low-error ECAT, the DA-precision in this work is chosen to be 9 bits instead of the traditional 12 bits. Therefore, the hardware cost is reduced, and the speed is improved using the proposed ECAT.
A Novel Algorithm for Watermarking and Image Encryption cscpconf
Digital watermarking is a method of copyright protection of audio, images, video and text. We
propose a new robust watermarking technique based on contourlet transform and singular value
decomposition. The paper also proposes a novel encryption algorithm to store a signed double
matrix as an RGB image. The entropy of the watermarked image and correlation coefficient of
extracted watermark image is very close to ideal values, proving the correctness of proposed
algorithm. Also experimental results show resiliency of the scheme against large blurring attack
like mean and gaussian filtering, linear filtering (high pass and low pass filtering) , non-linear
filtering (median filtering), addition of a constant offset to the pixel values and local exchange of pixels .Thus proving the security, effectiveness and robustness of the proposed watermarking algorithm.
IMAGE CODING THROUGH ZTRANSFORM WITH LOW ENERGY AND BANDWIDTH (IZEB) cscpconf
In this paper a Z-transform based image coding technique has been proposed. The techniques uses energy efficient and low bandwidth based invisible data embedding with a minimal
computational complexity. In this technique near about half the bandwidth is required compared to the traditional Z–transform while transmitting the multimedia content such as images through network.
Image coding through ztransform with low energy and bandwidth (izeb)csandit
In this paper a Z-transform based image coding technique has been proposed. The techniques
uses energy efficient and low bandwidth based invisible data embedding with a minimal
computational complexity. In this technique near about half the bandwidth is required
compared to the traditional Z–transform while transmitting the multimedia content such as
images through network.
This document proposes an enhanced adaptive data hiding technique in the discrete wavelet transform (DWT) domain. It begins with background information on DWT and quantization techniques like uniform and adaptive quantization. It then describes how data can be embedded in the non-zero DWT coefficients after adaptive quantization. Specifically, it embeds secret data by modifying the quantized DWT coefficients in a way that minimizes distortion to maintain good visual quality of the cover image. The goal is to improve data hiding capacity while preserving the quality of the cover image as measured by metrics like peak signal-to-noise ratio (PSNR) and the human visual system (HVS).
Non standard size image compression with reversible embedded waveletseSAT Publishing House
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.
A Novel Facial Recognition Method using Discrete Wavelet Transform Multiresolution Pyramid..........1
G. Preethi
Enhancing Energy Efficiency in WSN using Energy Potential and Energy Balancing Concepts ................. 9
Sheetalrani R. Kawale
DNS: Dynamic Network Selection Scheme for Vertical Handover in Heterogeneous Wireless Networks
.................................................................................................................................................................... 19
M. Deva Priya, D. Prithviraj and Dr. M. L Valarmathi
Implementation of Image based Flower Classification System................................................................ 35
Tanvi Kulkarni and Nilesh. J. Uke
A Survey on Knowledge Analytics of Text from Social Media .................................................................. 45
Dr. J. Akilandeswari and K. Rajalakshm
Progression of String Matching Practices in Web Mining – A Survey ..................................................... 62
Kaladevi A. C. and Nivetha S. M.
Virtualizing the Inter Communication of Clouds ...............................................................................72
Subho Roy Chowdhury, Sambit Kumar Patel, Ankita Vinod Mandekar and G. Usha Devi
Tracing the Adversaries using Packet Marking and Packet Logging ....................................................... 86
A. Santhosh and Dr. J. Senthil Kumar
An Improved Energy Efficient Clustering Algorithm for Non Availability of Spectrum in Cognitive Radio
Users ....................................................................................................................................................... 101
EFFICIENT IMAGE COMPRESSION USING LAPLACIAN PYRAMIDAL FILTERS FOR EDGE IMAGESijcnac
This project presents a new image compression technique for the coding of retinal and
fingerprint images. Retinal images are used to detect diseases like diabetes or
hypertension. Fingerprint images are used for the security purpose. In this work, the
contourlet transform of the retinal and fingerprint image is taken first. The coefficients of
the contourlet transform are quantized using adaptive multistage vector quantization
scheme. The number of code vectors in the adaptive vector quantization scheme depends
on the dynamic range of the input image.
A High Performance Modified SPIHT for Scalable Image CompressionCSCJournals
In this paper, we present a novel extension technique to the Set Partitioning in Hierarchical Trees (SPIHT) based image compression with spatial scalability. The present modification and the preprocessing techniques provide significantly better quality (both subjectively and objectively) reconstruction at the decoder with little additional computational complexity. There are two proposals for this paper. Firstly, we propose a pre-processing scheme, called Zero-Shifting, that brings the spatial values in signed integer range without changing the dynamic ranges, so that the transformed coefficient calculation becomes more consistent. For that reason, we have to modify the initialization step of the SPIHT algorithms. The experiments demonstrate a significant improvement in visual quality and faster encoding and decoding than the original one. Secondly, we incorporate the idea to facilitate resolution scalable decoding (not incorporated in original SPIHT) by rearranging the order of the encoded output bit stream. During the sorting pass of the SPIHT algorithm, we model the transformed coefficient based on the probability of significance, at a fixed threshold of the offspring. Calling it a fixed context model and generating a Huffman code for each context, we achieve comparable compression efficiency to that of arithmetic coder, but with much less computational complexity and processing time. As far as objective quality assessment of the reconstructed image is concerned, we have compared our results with popular Peak Signal to Noise Ratio (PSNR) and with Structural Similarity Index (SSIM). Both these metrics show that our proposed work is an improvement over the original one.
The document proposes a new video watermarking algorithm using the dual-tree complex wavelet transform (DTCWT). The DTCWT offers advantages like shift invariance and directional selectivity. The algorithm embeds a watermark by adding its coefficients to high frequency DTCWT coefficients of video frames. Masks are used to hide the watermark perceptually. Experimental results show the proposed method is robust to geometric distortions, lossy compression, and a joint attack, outperforming comparable DWT-based methods. It is suitable for playback control due to its robustness and simple implementation.
Performance Evaluation of Quarter Shift Dual Tree Complex Wavelet Transform B...IJECEIAES
In this paper, multifocus image fusion using quarter shift dual tree complex wavelet transform is proposed. Multifocus image fusion is a technique that combines the partially focused regions of multiple images of the same scene into a fully focused fused image. Directional selectivity and shift invariance properties are essential to produce a high quality fused image. However conventional wavelet based fusion algorithms introduce the ringing artifacts into fused image due to lack of shift invariance and poor directionality. The quarter shift dual tree complex wavelet transform has proven to be an effective multi-resolution transform for image fusion with its directional and shift invariant properties. Experimentation with this transform led to the conclusion that the proposed method not only produce sharp details (focused regions) in fused image due to its good directionality but also removes artifacts with its shift invariance in order to get high quality fused image. Proposed method performance is compared with traditional fusion methods in terms of objective measures.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document provides an overview of wavelet-based image fusion techniques. It discusses wavelet transform theory, including continuous and discrete wavelet transforms. For discrete wavelet transforms, it describes decimated, undecimated, and non-separated approaches. It explains how wavelet transforms can extract detail information from images at different resolutions, which can then be combined to create a fused image containing the best characteristics of the original images. While providing improved results over traditional fusion methods, wavelet-based approaches still have limitations such as artifact introduction that researchers continue working to address.
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.
International Journal of Engineering Research and DevelopmentIJERD Editor
1. The document compares the compression efficiency of different embedded image compression techniques - Discrete Wavelet Transform (DWT) with Embedded Zero Coding (EZW) and Set Partitioning in Hierarchical Trees (SPIHT) algorithms.
2. It analyzes the performance of EZW and SPIHT algorithms using different wavelet families (biorthogonal, daubechies, coiflets) on the Lena test image. Results show that biorthogonal wavelets like bior4.4 and bior6.8, and daubechies wavelets like db4 and db10 achieved good Peak Signal to Noise Ratio at low bit rates.
3. The document further improves compression by applying H
Architectural implementation of video compressioniaemedu
The document discusses video compression using wavelet transform coding and EZW coding. It begins with an introduction to wavelet transforms and their use in image and video compression. It then describes performing a Haar wavelet transform on video frames, downsampling the frames, and encoding the output with EZW coding. The encoded data is transmitted through a channel encoder. At the receiver, the reverse process of decoding and upsampling is performed to reconstruct the video. Video quality is assessed using peak signal-to-noise ratio between frames. The method aims to remove blocking artifacts and improve video quality compared to standard DCT-based compression.
Image compression using Hybrid wavelet Transform and their Performance Compa...IJMER
Images may be worth a thousand words, but they generally occupy much more space in hard disk, or
bandwidth in a transmission system, than their proverbial counterpart. Compressing an image is significantly
different than compressing raw binary data. Of course, general purpose compression programs can be used to
compress images, but the result is less than optimal. This is because images have certain statistical properties
which can be exploited by encoders specifically designed for them. Also, some of the finer details in the image
can be sacrificed for the sake of saving a little more bandwidth or storage space. Compression is the process of
representing information in a compact form. Compression is a necessary and essential method for creating
image files with manageable and transmittable sizes. The data compression schemes can be divided into
lossless and lossy compression. In lossless compression, reconstructed image is exactly same as compressed
image. In lossy image compression, high compression ratio is achieved at the cost of some error in reconstructed
image. Lossy compression generally provides much higher compression than lossless compression.
The document discusses using triangular basis functions for image transforms and compression. It proposes that triangular waveforms can be used as non-sinusoidal orthogonal basis functions for image transforms. The key steps include: (1) deriving the triangular basis functions from orthogonal matrices of different sizes, (2) using the basis functions to decompose images into frequency components through triangular transforms, (3) compressing images by selecting and quantizing the lowest frequency components obtained from the transforms. The approach allows for reconstructing damaged images by recalculating values using the derived basis functions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
PERFORMANCE EVALUATION OF DIFFERENT TECHNIQUES FOR TEXTURE CLASSIFICATION cscpconf
This document compares different techniques for texture classification, including wavelet transforms and co-occurrence matrices. It finds that the Haar wavelet technique is the most efficient in terms of time complexity and classification accuracy, except when images are rotated. The co-occurrence matrix method has higher time requirements but excellent classification results, except for rotated images where accuracy is greatly reduced due to its dependence on pixel values. Overall, the Haar wavelet proves to be the best method for texture classification based on the performance assessment parameters of time complexity and classification accuracy.
Fpga implementation of fusion technique for fingerprint applicationIAEME Publication
Image Fusion is a process of combining relevant information from a set of images, into a
single image, wherein the resultant fused image will be more informative and complete than any of
the input images. This paper discusses Laplacian Pyramid (LP) based image fusion techniques for
fingerprint application. The technique is implemented in MatLab and evaluation parameters Mean
Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Matching score are discussed. As well
the same implemented on Virtex-5 FPGA development board using Verilog HDL. LP based
technique provides better results for image fusion than other techniques.
This document discusses image compression using a Raspberry Pi processor. It begins with an abstract stating that image compression is needed to reduce file sizes for storage and transmission while retaining image quality. The document then discusses various image compression techniques like discrete wavelet transform (DWT) and discrete cosine transform (DCT), as well as JPEG compression. It states that the Raspberry Pi allows implementing DWT to provide JPEG format images using OpenCV. The document provides details of the image compression method tested, which involves capturing images with a USB camera connected to the Raspberry Pi, compressing the images using DWT and wavelet transforms, transmitting the compressed images over the internet, decompressing the images on a server, and displaying the decompressed images
This document discusses the discrete wavelet transform (DWT) and its implementation in MATLAB. It begins with an introduction to DWTs, explaining that they decompose signals into different frequency bands using low-pass and high-pass filters. It then describes how 2D DWTs are implemented by applying 1D transforms separately to rows and columns, producing subbands that emphasize different types of edges. The document provides steps for performing DWTs in MATLAB, including single-level and multi-level decomposition and reconstruction. It concludes by showing decomposed images and discussing how DWTs separate approximation and detail information.
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.
Image Compression Using Discrete Cosine Transform & Discrete Wavelet Transformijbuiiir1
This research paper presents a proposed method for the compression of medical images using hybrid compression technique (DWT, DCT and Huffman coding). The objective of this hybrid scheme is to achieve higher compression rates by first applying DWT and DCT on individual components RGB. After applying this image is quantized to calculate probability index for each unique quantity so as to find out the unique binary code for each unique symbol for their encoding. Finally the Huffman compression is applied. Results show that the coding performance can be significantly improved by the hybrid DWT, DCT and Huffman coding algorithm
This document presents a new technique for enhancing the contrast of low-contrast satellite images using discrete wavelet transform (DWT) and singular value decomposition (SVD). It begins with an abstract and introduction describing the technique. The technique uses DWT to decompose an input satellite image into frequency subbands, and SVD to estimate the singular value matrix of the low-low subband. The singular values are modified to enhance contrast before reconstructing the final image. The proposed DWT-SVD technique is compared to general histogram equalization (GHE) and singular value equalization (SVE), with results suggesting it outperforms these methods both visually and quantitatively. The document also discusses using fast Fourier transform and bi-log
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A Comparative Study of Wavelet and Curvelet Transform for Image DenoisingIOSR Journals
Abstract : This paper describes a comparison of the discriminating power of the various multiresolution based thresholding techniques i.e., Wavelet, curve let for image denoising.Curvelet transform offer exact reconstruction, stability against perturbation, ease of implementation and low computational complexity. We propose to employ curve let for facial feature extraction and perform a thorough comparison against wavelet transform; especially, the orientation of curve let is analysed. Experiments show that for expression changes, the small scale coefficients of curve let transform are robust, though the large scale coefficients of both transform are likely influenced. The reason behind the advantages of curvelet lies in its abilities of sparse representation that are critical for compression, estimation of images which are denoised and its inverse problems, thus the experiments and theoretical analysis coincide . Keywords: Curvelet transform, Face recognition, Feature extraction, Sparse representation Thresholding rules,Wavelet transform..
A High Performance Modified SPIHT for Scalable Image CompressionCSCJournals
In this paper, we present a novel extension technique to the Set Partitioning in Hierarchical Trees (SPIHT) based image compression with spatial scalability. The present modification and the preprocessing techniques provide significantly better quality (both subjectively and objectively) reconstruction at the decoder with little additional computational complexity. There are two proposals for this paper. Firstly, we propose a pre-processing scheme, called Zero-Shifting, that brings the spatial values in signed integer range without changing the dynamic ranges, so that the transformed coefficient calculation becomes more consistent. For that reason, we have to modify the initialization step of the SPIHT algorithms. The experiments demonstrate a significant improvement in visual quality and faster encoding and decoding than the original one. Secondly, we incorporate the idea to facilitate resolution scalable decoding (not incorporated in original SPIHT) by rearranging the order of the encoded output bit stream. During the sorting pass of the SPIHT algorithm, we model the transformed coefficient based on the probability of significance, at a fixed threshold of the offspring. Calling it a fixed context model and generating a Huffman code for each context, we achieve comparable compression efficiency to that of arithmetic coder, but with much less computational complexity and processing time. As far as objective quality assessment of the reconstructed image is concerned, we have compared our results with popular Peak Signal to Noise Ratio (PSNR) and with Structural Similarity Index (SSIM). Both these metrics show that our proposed work is an improvement over the original one.
The document proposes a new video watermarking algorithm using the dual-tree complex wavelet transform (DTCWT). The DTCWT offers advantages like shift invariance and directional selectivity. The algorithm embeds a watermark by adding its coefficients to high frequency DTCWT coefficients of video frames. Masks are used to hide the watermark perceptually. Experimental results show the proposed method is robust to geometric distortions, lossy compression, and a joint attack, outperforming comparable DWT-based methods. It is suitable for playback control due to its robustness and simple implementation.
Performance Evaluation of Quarter Shift Dual Tree Complex Wavelet Transform B...IJECEIAES
In this paper, multifocus image fusion using quarter shift dual tree complex wavelet transform is proposed. Multifocus image fusion is a technique that combines the partially focused regions of multiple images of the same scene into a fully focused fused image. Directional selectivity and shift invariance properties are essential to produce a high quality fused image. However conventional wavelet based fusion algorithms introduce the ringing artifacts into fused image due to lack of shift invariance and poor directionality. The quarter shift dual tree complex wavelet transform has proven to be an effective multi-resolution transform for image fusion with its directional and shift invariant properties. Experimentation with this transform led to the conclusion that the proposed method not only produce sharp details (focused regions) in fused image due to its good directionality but also removes artifacts with its shift invariance in order to get high quality fused image. Proposed method performance is compared with traditional fusion methods in terms of objective measures.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This document provides an overview of wavelet-based image fusion techniques. It discusses wavelet transform theory, including continuous and discrete wavelet transforms. For discrete wavelet transforms, it describes decimated, undecimated, and non-separated approaches. It explains how wavelet transforms can extract detail information from images at different resolutions, which can then be combined to create a fused image containing the best characteristics of the original images. While providing improved results over traditional fusion methods, wavelet-based approaches still have limitations such as artifact introduction that researchers continue working to address.
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.
International Journal of Engineering Research and DevelopmentIJERD Editor
1. The document compares the compression efficiency of different embedded image compression techniques - Discrete Wavelet Transform (DWT) with Embedded Zero Coding (EZW) and Set Partitioning in Hierarchical Trees (SPIHT) algorithms.
2. It analyzes the performance of EZW and SPIHT algorithms using different wavelet families (biorthogonal, daubechies, coiflets) on the Lena test image. Results show that biorthogonal wavelets like bior4.4 and bior6.8, and daubechies wavelets like db4 and db10 achieved good Peak Signal to Noise Ratio at low bit rates.
3. The document further improves compression by applying H
Architectural implementation of video compressioniaemedu
The document discusses video compression using wavelet transform coding and EZW coding. It begins with an introduction to wavelet transforms and their use in image and video compression. It then describes performing a Haar wavelet transform on video frames, downsampling the frames, and encoding the output with EZW coding. The encoded data is transmitted through a channel encoder. At the receiver, the reverse process of decoding and upsampling is performed to reconstruct the video. Video quality is assessed using peak signal-to-noise ratio between frames. The method aims to remove blocking artifacts and improve video quality compared to standard DCT-based compression.
Image compression using Hybrid wavelet Transform and their Performance Compa...IJMER
Images may be worth a thousand words, but they generally occupy much more space in hard disk, or
bandwidth in a transmission system, than their proverbial counterpart. Compressing an image is significantly
different than compressing raw binary data. Of course, general purpose compression programs can be used to
compress images, but the result is less than optimal. This is because images have certain statistical properties
which can be exploited by encoders specifically designed for them. Also, some of the finer details in the image
can be sacrificed for the sake of saving a little more bandwidth or storage space. Compression is the process of
representing information in a compact form. Compression is a necessary and essential method for creating
image files with manageable and transmittable sizes. The data compression schemes can be divided into
lossless and lossy compression. In lossless compression, reconstructed image is exactly same as compressed
image. In lossy image compression, high compression ratio is achieved at the cost of some error in reconstructed
image. Lossy compression generally provides much higher compression than lossless compression.
The document discusses using triangular basis functions for image transforms and compression. It proposes that triangular waveforms can be used as non-sinusoidal orthogonal basis functions for image transforms. The key steps include: (1) deriving the triangular basis functions from orthogonal matrices of different sizes, (2) using the basis functions to decompose images into frequency components through triangular transforms, (3) compressing images by selecting and quantizing the lowest frequency components obtained from the transforms. The approach allows for reconstructing damaged images by recalculating values using the derived basis functions.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
PERFORMANCE EVALUATION OF DIFFERENT TECHNIQUES FOR TEXTURE CLASSIFICATION cscpconf
This document compares different techniques for texture classification, including wavelet transforms and co-occurrence matrices. It finds that the Haar wavelet technique is the most efficient in terms of time complexity and classification accuracy, except when images are rotated. The co-occurrence matrix method has higher time requirements but excellent classification results, except for rotated images where accuracy is greatly reduced due to its dependence on pixel values. Overall, the Haar wavelet proves to be the best method for texture classification based on the performance assessment parameters of time complexity and classification accuracy.
Fpga implementation of fusion technique for fingerprint applicationIAEME Publication
Image Fusion is a process of combining relevant information from a set of images, into a
single image, wherein the resultant fused image will be more informative and complete than any of
the input images. This paper discusses Laplacian Pyramid (LP) based image fusion techniques for
fingerprint application. The technique is implemented in MatLab and evaluation parameters Mean
Square Error (MSE), Peak Signal to Noise Ratio (PSNR) and Matching score are discussed. As well
the same implemented on Virtex-5 FPGA development board using Verilog HDL. LP based
technique provides better results for image fusion than other techniques.
This document discusses image compression using a Raspberry Pi processor. It begins with an abstract stating that image compression is needed to reduce file sizes for storage and transmission while retaining image quality. The document then discusses various image compression techniques like discrete wavelet transform (DWT) and discrete cosine transform (DCT), as well as JPEG compression. It states that the Raspberry Pi allows implementing DWT to provide JPEG format images using OpenCV. The document provides details of the image compression method tested, which involves capturing images with a USB camera connected to the Raspberry Pi, compressing the images using DWT and wavelet transforms, transmitting the compressed images over the internet, decompressing the images on a server, and displaying the decompressed images
This document discusses the discrete wavelet transform (DWT) and its implementation in MATLAB. It begins with an introduction to DWTs, explaining that they decompose signals into different frequency bands using low-pass and high-pass filters. It then describes how 2D DWTs are implemented by applying 1D transforms separately to rows and columns, producing subbands that emphasize different types of edges. The document provides steps for performing DWTs in MATLAB, including single-level and multi-level decomposition and reconstruction. It concludes by showing decomposed images and discussing how DWTs separate approximation and detail information.
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.
Image Compression Using Discrete Cosine Transform & Discrete Wavelet Transformijbuiiir1
This research paper presents a proposed method for the compression of medical images using hybrid compression technique (DWT, DCT and Huffman coding). The objective of this hybrid scheme is to achieve higher compression rates by first applying DWT and DCT on individual components RGB. After applying this image is quantized to calculate probability index for each unique quantity so as to find out the unique binary code for each unique symbol for their encoding. Finally the Huffman compression is applied. Results show that the coding performance can be significantly improved by the hybrid DWT, DCT and Huffman coding algorithm
This document presents a new technique for enhancing the contrast of low-contrast satellite images using discrete wavelet transform (DWT) and singular value decomposition (SVD). It begins with an abstract and introduction describing the technique. The technique uses DWT to decompose an input satellite image into frequency subbands, and SVD to estimate the singular value matrix of the low-low subband. The singular values are modified to enhance contrast before reconstructing the final image. The proposed DWT-SVD technique is compared to general histogram equalization (GHE) and singular value equalization (SVE), with results suggesting it outperforms these methods both visually and quantitatively. The document also discusses using fast Fourier transform and bi-log
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A Comparative Study of Wavelet and Curvelet Transform for Image DenoisingIOSR Journals
Abstract : This paper describes a comparison of the discriminating power of the various multiresolution based thresholding techniques i.e., Wavelet, curve let for image denoising.Curvelet transform offer exact reconstruction, stability against perturbation, ease of implementation and low computational complexity. We propose to employ curve let for facial feature extraction and perform a thorough comparison against wavelet transform; especially, the orientation of curve let is analysed. Experiments show that for expression changes, the small scale coefficients of curve let transform are robust, though the large scale coefficients of both transform are likely influenced. The reason behind the advantages of curvelet lies in its abilities of sparse representation that are critical for compression, estimation of images which are denoised and its inverse problems, thus the experiments and theoretical analysis coincide . Keywords: Curvelet transform, Face recognition, Feature extraction, Sparse representation Thresholding rules,Wavelet transform..
This document describes a hybrid technique for image enhancement that uses both frequency domain and spatial domain techniques. It begins with applying frequency domain techniques like discrete cosine transform (DCT) or discrete wavelet transform (DWT) to separate an image into magnitude and phase spectra. The magnitude is then enhanced before recombining it with the phase using inverse DCT/DWT. Spatial domain techniques like power law or log transforms are then applied to further enhance contrast and brightness. The technique is evaluated on sample images and shown to achieve better PSNR and lower MSE than frequency domain techniques alone. In conclusion, combining frequency and spatial domain methods provides an effective approach for image enhancement.
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This document presents a new image denoising technique using pixel-component-analysis. It begins by discussing existing denoising methods like spatial filtering, transform domain filtering using wavelets, and non-local mean approaches. It then proposes a two-stage denoising method using principal component analysis (PCA) on local pixel coherence (LPC) vectors. In the first stage, PCA is applied to transform and filter LPC vectors. In the second stage, denoising is repeated on the output of stage one to further reduce noise. Experimental results on test images show PSNR and SSIM improvements between the single-stage and two-stage approaches, demonstrating the effectiveness of the proposed two-stage LPC-PCA deno
The usage of a fused image and compressed model in a VLSI implementation is demonstrated. In this study, distortion correction is also considered. In distortion correction models, least-squares estimate is utilized. The technique of picture fusion is widely employed in medical imaging. Many pictures are obtained from various sensors (or) multiple images are captured at different times by one sensor in the image fusion approach. CT scans give useful information on denser tissue with the least amount of distortion. The information obtained from a magnetic resonance imaging (MRI) of soft tissue with significant distortion is useful. The DWT-based image fusion approach employs discrete wavelet transforms, a novel multi-resolution analytic tool. Back mapping expansion polynomial is used to reduce computer complexity. Using 0.18um technology, the suggested VLSI design achieves 218MHz with 1480 logical components.
Transform coding is used in image and video processing to exploit correlations between neighboring pixels. The discrete cosine transform (DCT) is commonly used as it provides good energy compaction and de-correlation. DCT represents data as a sum of variable frequency cosine waves in the frequency domain. It has properties like separability and orthogonality that make it efficient for computation. DCT exhibits excellent energy compaction and removal of redundancy between pixels, making it useful for image and video compression.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
FINGERPRINTS IMAGE COMPRESSION BY WAVE ATOMScscpconf
The fingerprint images compression based on geometric transformed presents important
research topic, these last year’s many transforms have been proposed to give the best
representation to a particular type of image “fingerprint image”, like classics wavelets and
wave atoms. In this paper we shall present a comparative study between this transforms, in
order to use them in compression. The results show that for fingerprint images, the wave atom
offers better performance than the current transform based compression standard. The wave
atoms transformation brings a considerable contribution on the compression of fingerprints
images by achieving high values of ratios compression and PSNR, with a reduced number of
coefficients. In addition, the proposed method is verified with objective and subjective testing.
helping users to embed images in other images to maintain the integrity of the images being transferred. Watermarking is one technique through which we can accomplish this. Here we are using few algorithms, like Least Significant Bit ,Wavelet Image Watermarking , DCT Image watermarking and FFT Image watermarking. Our aim was to study different watermarking techniques and implement the one which is most resistant to all types of attack, scalar or geometric.
Ijri ece-01-02 image enhancement aided denoising using dual tree complex wave...Ijripublishers Ijri
This paper presents a novel way to reduce noise introduced or exacerbated by image enhancement methods, in particular algorithms based on the random spray sampling technique, but not only. According to the nature of sprays, output images of spray-based methods tend to exhibit noise with unknown statistical distribution. To avoid inappropriate assumptions on the statistical characteristics of noise, a different one is made. In fact, the non-enhanced image is considered to be either free of noise or affected by non-perceivable levels of noise. Taking advantage of the higher sensitivity of the human visual system to changes in brightness, the analysis can be limited to the luma channel of both the non-enhanced and enhanced image. Also, given the importance of directional content in human vision, the analysis is performed through the dual-tree complex wavelet transform , lanczos interpolator and edge preserving smoothing filters. Unlike the discrete wavelet transform, the DTWCT allows for distinction of data directionality in the transform space. For each level of the transform, the standard deviation of the non-enhanced image coefficients is computed across the six orientations of the DTWCT, then it is normalized.
Keywords: dual-tree complex wavelet transform (DTWCT), lanczos interpolator, edge preserving smoothing filters.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
This document proposes an Adaptive Resolution Enhancement Algorithm (AREA) using an Edge Targeted Filter (ETF) and Dual Tree Complex Wavelet Transform (DTCWT) to enhance the resolution and image quality of low-quality, low-resolution images. The ETF first detects edges in an input image and generates a mask. It then focuses on improving edge reconstruction. The output is input to DTCWT, which analyzes subband coefficients to detect flaws and interpolates coefficients to enhance spectral resolution. The inverse DTCWT produces a spatially enhanced output image with improved resolution up to 17% compared to existing techniques. Simulation results demonstrate the effectiveness of the proposed algorithm.
Ijri ece-01-02 image enhancement aided denoising using dual tree complex wave...Ijripublishers Ijri
This paper presents a novel way to reduce noise introduced or exacerbated by image enhancement methods, in particular
algorithms based on the random spray sampling technique, but not only. According to the nature of sprays,
output images of spray-based methods tend to exhibit noise with unknown statistical distribution. To avoid inappropriate
assumptions on the statistical characteristics of noise, a different one is made. In fact, the non-enhanced image is
considered to be either free of noise or affected by non-perceivable levels of noise. Taking advantage of the higher sensitivity
of the human visual system to changes in brightness, the analysis can be limited to the luma channel of both the
non-enhanced and enhanced image. Also, given the importance of directional content in human vision, the analysis is
performed through the dual-tree complex wavelet transform , lanczos interpolator and edge preserving smoothing filters.
Unlike the discrete wavelet transform, the DTWCT allows for distinction of data directionality in the transform space.
For each level of the transform, the standard deviation of the non-enhanced image coefficients is computed across the
six orientations of the DTWCT, then it is normalized.
Keywords: dual-tree complex wavelet transform (DTWCT), lanczos interpolator, edge preserving smoothing filters.
Wavelet-Based Warping Technique for Mobile Devicescsandit
The document proposes a wavelet-based warping technique to render novel views of compressed images on mobile devices. It uses Haar wavelet transform to compress large reference and depth images, reducing their size. The technique decomposes the images into approximation and detail parts, but only uses the approximation parts for warping. This improves rendering speed on mobile devices. The framework is implemented using Android tools and experiments show it provides faster rendering times for large images compared to direct warping without compression.
4.[23 28]image denoising using digital image curveletAlexander Decker
This document summarizes research on using curvelet transforms for image denoising. It begins with an introduction to wavelet denoising and its limitations in capturing edges. Curvelet transforms are proposed to overcome these limitations by providing directional selectivity and anisotropic elements that better represent curved edges. The document then describes steps to denoise an image using curvelet transforms, including adding noise, applying the curvelet transform, and calculating performance metrics like PSNR and MSE. It provides details on the curvelet transform and compares it to ridgelet transforms. The research aims to exhibit higher PSNR than wavelet methods across different noise levels on standard test images like Lenna.
4.[23 28]image denoising using digital image curveletAlexander Decker
This document summarizes research on using curvelet transforms for image denoising. It begins by discussing limitations of wavelet transforms for image processing, including lack of directionality and shift sensitivity. Curvelet transforms overcome these issues by providing high directional specificity and approximate shift invariance. The document proposes using digital implementations of curvelet, ridgelet, and contourlet transforms to denoise images corrupted by different types of noise. It describes the steps taken, which include applying the transforms after adding noise, then calculating peak signal-to-noise ratio and mean squared error to compare reconstruction quality. The transforms are found to provide better denoising performance than wavelet transforms as measured by these metrics.
Similar to RTOS BASED SECURE SHORTEST PATH ROUTING ALGORITHM IN MOBILE AD- HOC NETWORKS (20)
ANALYSIS OF LAND SURFACE DEFORMATION GRADIENT BY DINSAR cscpconf
The progressive development of Synthetic Aperture Radar (SAR) systems diversify the exploitation of the generated images by these systems in different applications of geoscience. Detection and monitoring surface deformations, procreated by various phenomena had benefited from this evolution and had been realized by interferometry (InSAR) and differential interferometry (DInSAR) techniques. Nevertheless, spatial and temporal decorrelations of the interferometric couples used, limit strongly the precision of analysis results by these techniques. In this context, we propose, in this work, a methodological approach of surface deformation detection and analysis by differential interferograms to show the limits of this technique according to noise quality and level. The detectability model is generated from the deformation signatures, by simulating a linear fault merged to the images couples of ERS1 / ERS2 sensors acquired in a region of the Algerian south.
4D AUTOMATIC LIP-READING FOR SPEAKER'S FACE IDENTIFCATIONcscpconf
A novel based a trajectory-guided, concatenating approach for synthesizing high-quality image real sample renders video is proposed . The lips reading automated is seeking for modeled the closest real image sample sequence preserve in the library under the data video to the HMM predicted trajectory. The object trajectory is modeled obtained by projecting the face patterns into an KDA feature space is estimated. The approach for speaker's face identification by using synthesise the identity surface of a subject face from a small sample of patterns which sparsely each the view sphere. An KDA algorithm use to the Lip-reading image is discrimination, after that work consisted of in the low dimensional for the fundamental lip features vector is reduced by using the 2D-DCT.The mouth of the set area dimensionality is ordered by a normally reduction base on the PCA to obtain the Eigen lips approach, their proposed approach by[33]. The subjective performance results of the cost function under the automatic lips reading modeled , which wasn’t illustrate the superior performance of the
method.
MOVING FROM WATERFALL TO AGILE PROCESS IN SOFTWARE ENGINEERING CAPSTONE PROJE...cscpconf
Universities offer software engineering capstone course to simulate a real world-working environment in which students can work in a team for a fixed period to deliver a quality product. The objective of the paper is to report on our experience in moving from Waterfall process to Agile process in conducting the software engineering capstone project. We present the capstone course designs for both Waterfall driven and Agile driven methodologies that highlight the structure, deliverables and assessment plans.To evaluate the improvement, we conducted a survey for two different sections taught by two different instructors to evaluate students’ experience in moving from traditional Waterfall model to Agile like process. Twentyeight students filled the survey. The survey consisted of eight multiple-choice questions and an open-ended question to collect feedback from students. The survey results show that students were able to attain hands one experience, which simulate a real world-working environment. The results also show that the Agile approach helped students to have overall better design and avoid mistakes they have made in the initial design completed in of the first phase of the capstone project. In addition, they were able to decide on their team capabilities, training needs and thus learn the required technologies earlier which is reflected on the final product quality
PROMOTING STUDENT ENGAGEMENT USING SOCIAL MEDIA TECHNOLOGIEScscpconf
This document discusses using social media technologies to promote student engagement in a software project management course. It describes the course and objectives of enhancing communication. It discusses using Facebook for 4 years, then switching to WhatsApp based on student feedback, and finally introducing Slack to enable personalized team communication. Surveys found students engaged and satisfied with all three tools, though less familiar with Slack. The conclusion is that social media promotes engagement but familiarity with the tool also impacts satisfaction.
A SURVEY ON QUESTION ANSWERING SYSTEMS: THE ADVANCES OF FUZZY LOGICcscpconf
In real world computing environment with using a computer to answer questions has been a human dream since the beginning of the digital era, Question-answering systems are referred to as intelligent systems, that can be used to provide responses for the questions being asked by the user based on certain facts or rules stored in the knowledge base it can generate answers of questions asked in natural , and the first main idea of fuzzy logic was to working on the problem of computer understanding of natural language, so this survey paper provides an overview on what Question-Answering is and its system architecture and the possible relationship and
different with fuzzy logic, as well as the previous related research with respect to approaches that were followed. At the end, the survey provides an analytical discussion of the proposed QA models, along or combined with fuzzy logic and their main contributions and limitations.
DYNAMIC PHONE WARPING – A METHOD TO MEASURE THE DISTANCE BETWEEN PRONUNCIATIONS cscpconf
Human beings generate different speech waveforms while speaking the same word at different times. Also, different human beings have different accents and generate significantly varying speech waveforms for the same word. There is a need to measure the distances between various words which facilitate preparation of pronunciation dictionaries. A new algorithm called Dynamic Phone Warping (DPW) is presented in this paper. It uses dynamic programming technique for global alignment and shortest distance measurements. The DPW algorithm can be used to enhance the pronunciation dictionaries of the well-known languages like English or to build pronunciation dictionaries to the less known sparse languages. The precision measurement experiments show 88.9% accuracy.
INTELLIGENT ELECTRONIC ASSESSMENT FOR SUBJECTIVE EXAMS cscpconf
In education, the use of electronic (E) examination systems is not a novel idea, as Eexamination systems have been used to conduct objective assessments for the last few years. This research deals with randomly designed E-examinations and proposes an E-assessment system that can be used for subjective questions. This system assesses answers to subjective questions by finding a matching ratio for the keywords in instructor and student answers. The matching ratio is achieved based on semantic and document similarity. The assessment system is composed of four modules: preprocessing, keyword expansion, matching, and grading. A survey and case study were used in the research design to validate the proposed system. The examination assessment system will help instructors to save time, costs, and resources, while increasing efficiency and improving the productivity of exam setting and assessments.
TWO DISCRETE BINARY VERSIONS OF AFRICAN BUFFALO OPTIMIZATION METAHEURISTICcscpconf
African Buffalo Optimization (ABO) is one of the most recent swarms intelligence based metaheuristics. ABO algorithm is inspired by the buffalo’s behavior and lifestyle. Unfortunately, the standard ABO algorithm is proposed only for continuous optimization problems. In this paper, the authors propose two discrete binary ABO algorithms to deal with binary optimization problems. In the first version (called SBABO) they use the sigmoid function and probability model to generate binary solutions. In the second version (called LBABO) they use some logical operator to operate the binary solutions. Computational results on two knapsack problems (KP and MKP) instances show the effectiveness of the proposed algorithm and their ability to achieve good and promising solutions.
DETECTION OF ALGORITHMICALLY GENERATED MALICIOUS DOMAINcscpconf
In recent years, many malware writers have relied on Dynamic Domain Name Services (DDNS) to maintain their Command and Control (C&C) network infrastructure to ensure a persistence presence on a compromised host. Amongst the various DDNS techniques, Domain Generation Algorithm (DGA) is often perceived as the most difficult to detect using traditional methods. This paper presents an approach for detecting DGA using frequency analysis of the character distribution and the weighted scores of the domain names. The approach’s feasibility is demonstrated using a range of legitimate domains and a number of malicious algorithmicallygenerated domain names. Findings from this study show that domain names made up of English characters “a-z” achieving a weighted score of < 45 are often associated with DGA. When a weighted score of < 45 is applied to the Alexa one million list of domain names, only 15% of the domain names were treated as non-human generated.
GLOBAL MUSIC ASSET ASSURANCE DIGITAL CURRENCY: A DRM SOLUTION FOR STREAMING C...cscpconf
The document proposes a blockchain-based digital currency and streaming platform called GoMAA to address issues of piracy in the online music streaming industry. Key points:
- GoMAA would use a digital token on the iMediaStreams blockchain to enable secure dissemination and tracking of streamed content. Content owners could control access and track consumption of released content.
- Original media files would be converted to a Secure Portable Streaming (SPS) format, embedding watermarks and smart contract data to indicate ownership and enable validation on the blockchain.
- A browser plugin would provide wallets for fans to collect GoMAA tokens as rewards for consuming content, incentivizing participation and addressing royalty discrepancies by recording
IMPORTANCE OF VERB SUFFIX MAPPING IN DISCOURSE TRANSLATION SYSTEMcscpconf
This document discusses the importance of verb suffix mapping in discourse translation from English to Telugu. It explains that after anaphora resolution, the verbs must be changed to agree with the gender, number, and person features of the subject or anaphoric pronoun. Verbs in Telugu inflect based on these features, while verbs in English only inflect based on number and person. Several examples are provided that demonstrate how the Telugu verb changes based on whether the subject or pronoun is masculine, feminine, neuter, singular or plural. Proper verb suffix mapping is essential for generating natural and coherent translations while preserving the context and meaning of the original discourse.
EXACT SOLUTIONS OF A FAMILY OF HIGHER-DIMENSIONAL SPACE-TIME FRACTIONAL KDV-T...cscpconf
In this paper, based on the definition of conformable fractional derivative, the functional
variable method (FVM) is proposed to seek the exact traveling wave solutions of two higherdimensional
space-time fractional KdV-type equations in mathematical physics, namely the
(3+1)-dimensional space–time fractional Zakharov-Kuznetsov (ZK) equation and the (2+1)-
dimensional space–time fractional Generalized Zakharov-Kuznetsov-Benjamin-Bona-Mahony
(GZK-BBM) equation. Some new solutions are procured and depicted. These solutions, which
contain kink-shaped, singular kink, bell-shaped soliton, singular soliton and periodic wave
solutions, have many potential applications in mathematical physics and engineering. The
simplicity and reliability of the proposed method is verified.
AUTOMATED PENETRATION TESTING: AN OVERVIEWcscpconf
The document discusses automated penetration testing and provides an overview. It compares manual and automated penetration testing, noting that automated testing allows for faster, more standardized and repeatable tests but has limitations in developing new exploits. It also reviews some current automated penetration testing methodologies and tools, including those using HTTP/TCP/IP attacks, linking common scanning tools, a Python-based tool targeting databases, and one using POMDPs for multi-step penetration test planning under uncertainty. The document concludes that automated testing is more efficient than manual for known vulnerabilities but cannot replace manual testing for discovering new exploits.
CLASSIFICATION OF ALZHEIMER USING fMRI DATA AND BRAIN NETWORKcscpconf
Since the mid of 1990s, functional connectivity study using fMRI (fcMRI) has drawn increasing
attention of neuroscientists and computer scientists, since it opens a new window to explore
functional network of human brain with relatively high resolution. BOLD technique provides
almost accurate state of brain. Past researches prove that neuro diseases damage the brain
network interaction, protein- protein interaction and gene-gene interaction. A number of
neurological research paper also analyse the relationship among damaged part. By
computational method especially machine learning technique we can show such classifications.
In this paper we used OASIS fMRI dataset affected with Alzheimer’s disease and normal
patient’s dataset. After proper processing the fMRI data we use the processed data to form
classifier models using SVM (Support Vector Machine), KNN (K- nearest neighbour) & Naïve
Bayes. We also compare the accuracy of our proposed method with existing methods. In future,
we will other combinations of methods for better accuracy.
VALIDATION METHOD OF FUZZY ASSOCIATION RULES BASED ON FUZZY FORMAL CONCEPT AN...cscpconf
The document proposes a new validation method for fuzzy association rules based on three steps: (1) applying the EFAR-PN algorithm to extract a generic base of non-redundant fuzzy association rules using fuzzy formal concept analysis, (2) categorizing the extracted rules into groups, and (3) evaluating the relevance of the rules using structural equation modeling, specifically partial least squares. The method aims to address issues with existing fuzzy association rule extraction algorithms such as large numbers of extracted rules, redundancy, and difficulties with manual validation.
PROBABILITY BASED CLUSTER EXPANSION OVERSAMPLING TECHNIQUE FOR IMBALANCED DATAcscpconf
In many applications of data mining, class imbalance is noticed when examples in one class are
overrepresented. Traditional classifiers result in poor accuracy of the minority class due to the
class imbalance. Further, the presence of within class imbalance where classes are composed of
multiple sub-concepts with different number of examples also affect the performance of
classifier. In this paper, we propose an oversampling technique that handles between class and
within class imbalance simultaneously and also takes into consideration the generalization
ability in data space. The proposed method is based on two steps- performing Model Based
Clustering with respect to classes to identify the sub-concepts; and then computing the
separating hyperplane based on equal posterior probability between the classes. The proposed
method is tested on 10 publicly available data sets and the result shows that the proposed
method is statistically superior to other existing oversampling methods.
CHARACTER AND IMAGE RECOGNITION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHcscpconf
Data collection is an essential, but manpower intensive procedure in ecological research. An
algorithm was developed by the author which incorporated two important computer vision
techniques to automate data cataloging for butterfly measurements. Optical Character
Recognition is used for character recognition and Contour Detection is used for imageprocessing.
Proper pre-processing is first done on the images to improve accuracy. Although
there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify
words of basic fonts. Contour detection is an advanced technique that can be utilized to
measure an image. Shapes and mathematical calculations are crucial in determining the precise
location of the points on which to draw the body and forewing lines of the butterfly. Overall,
92% accuracy were achieved by the program for the set of butterflies measured.
SOCIAL MEDIA ANALYTICS FOR SENTIMENT ANALYSIS AND EVENT DETECTION IN SMART CI...cscpconf
Smart cities utilize Internet of Things (IoT) devices and sensors to enhance the quality of the city
services including energy, transportation, health, and much more. They generate massive
volumes of structured and unstructured data on a daily basis. Also, social networks, such as
Twitter, Facebook, and Google+, are becoming a new source of real-time information in smart
cities. Social network users are acting as social sensors. These datasets so large and complex
are difficult to manage with conventional data management tools and methods. To become
valuable, this massive amount of data, known as 'big data,' needs to be processed and
comprehended to hold the promise of supporting a broad range of urban and smart cities
functions, including among others transportation, water, and energy consumption, pollution
surveillance, and smart city governance. In this work, we investigate how social media analytics
help to analyze smart city data collected from various social media sources, such as Twitter and
Facebook, to detect various events taking place in a smart city and identify the importance of
events and concerns of citizens regarding some events. A case scenario analyses the opinions of
users concerning the traffic in three largest cities in the UAE
SOCIAL NETWORK HATE SPEECH DETECTION FOR AMHARIC LANGUAGEcscpconf
The anonymity of social networks makes it attractive for hate speech to mask their criminal
activities online posing a challenge to the world and in particular Ethiopia. With this everincreasing
volume of social media data, hate speech identification becomes a challenge in
aggravating conflict between citizens of nations. The high rate of production, has become
difficult to collect, store and analyze such big data using traditional detection methods. This
paper proposed the application of apache spark in hate speech detection to reduce the
challenges. Authors developed an apache spark based model to classify Amharic Facebook
posts and comments into hate and not hate. Authors employed Random forest and Naïve Bayes
for learning and Word2Vec and TF-IDF for feature selection. Tested by 10-fold crossvalidation,
the model based on word2vec embedding performed best with 79.83%accuracy. The
proposed method achieve a promising result with unique feature of spark for big data.
GENERAL REGRESSION NEURAL NETWORK BASED POS TAGGING FOR NEPALI TEXTcscpconf
This article presents Part of Speech tagging for Nepali text using General Regression Neural
Network (GRNN). The corpus is divided into two parts viz. training and testing. The network is
trained and validated on both training and testing data. It is observed that 96.13% words are
correctly being tagged on training set whereas 74.38% words are tagged correctly on testing
data set using GRNN. The result is compared with the traditional Viterbi algorithm based on
Hidden Markov Model. Viterbi algorithm yields 97.2% and 40% classification accuracies on
training and testing data sets respectively. GRNN based POS Tagger is more consistent than the
traditional Viterbi decoding technique.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
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How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
2. 196 Computer Science & Information Technology (CS & IT)
frequency information and the temporal information is lost in transformation process, where as
wavelets preserves both frequency and temporal information. The wavelet transform is often
compared with the Fourier transform, in which signals are represented as a sum of sinusoids.
The main difference is that wavelets are localized in both time and frequency whereas the
standard Fourier transform is only localized in frequency. Wavelets often give a better signal
representation using Multiresolution analysis, with balanced resolution at any time and frequency.
The use of interband prediction is to improve compression by predicting color channels within an
image. Interband prediction is performed instead of an RGB to YUV color space transform as is
done in JPEG and JPEG 2000.Interband prediction aids compression when used with wavelet
transforms producing gains in PSNR of several dB.
Lossy compression techniques such as JPEG and JPEG 2000 provide the ability to achieve
relatively high compression rates at the expense of image quality. These schemes allow the loss to
be adjusted so as to trade image quality for bit rate. Both JPEG and JPEG 2000 apply a spectral
transform to color images as an initial step before applying a spatial transform. The spectral
transform acts to reduce the statistical dependency between different spectral channels. This
discussion gives an alternate approach that exploits the statistical dependency to implement
interband prediction of the spectral channels.
This paper is organized as follows. Section 1 gives an overview of the image compression
techniques used in the industry, comparison between Fourier transform and Wavelet transforms,
explaining the advantages of using reversible wavelet transform techniques. Section 2 explains
problem formulation of the reversible wavelet transform technique. Step by Step procedure is also
explained with required equations. Section 3 deals with compressing a standard color image using
MATLAB code explaining salient points. Two standard color images Lenna (512 X 512) and
Gold hill (720 X 576) are used to validate this code whose results are documented in this section.
Section 4 explains conclusions and future scope pertaining to this paper.
2. PROCESS FORMULATION FOR LOSSLESS COMPRESSION OF COLOR
IMAGE
This section explains the process followed in compressing color images using spatial and spectral
decorrelation procedures. Steps involved in this process are explained in the following flow chart
shown in Figure 1.
2.1 Input
Two experimental test images of different sizes are considered as input images to carry out this
process. The color images Lenna of size 512 X 512 and Gold hill of size 720 X 576 are taken.
2.2 Spatial Decorrelation of Color Bands
Traditional color image compression methods typically apply a spectral Decorrelation across the
color components first. Then spatial transforms are employed to decorrelate individual spectral
bands further. If spectral and spatial transforms are carried out independently, their order is
insignificant and can be reversed. This offers the opportunity to apply different spectral
transforms to associated color subbands sharing the same scale and orientation. The result is an
effective lossless image compression algorithm.
3. Computer Science & Information Technology (CS & IT) 197
For lossless (or reversible) image compression, it is important to represent transform coefficients
with integer numbers. As a result, for progressive-resolution transmission applications, reversible
wavelet transforms (RWTs), such as the S-transform or the SP-transform, are often used.
The one-dimensional S-transform reduces the necessary word length by making intelligent use of
rounding operations. It successively decimates some input sequence sk[n] at resolution r = 2-k
into
truncated average or coarse versions sk+1[n] and associated difference or detail signals dk+1[n] at
resolution r = 2-k-1
. Applying the S-transform to an input signal s[n] = so[n] at resolution r = 1, we
obtain resolutions that are negative powers of two only, i.e.,r = 2- k
, k> 0.
Figure 1. Flow chart for process formulation
Wavelet transform can also be viewed as a pyramid decomposition scheme. A powerful, but
conceptually simple structure for representing images at more than one resolution is the image
pyramid. An image pyramid is a collection of decreasing resolution images arranged in the shape
of a pyramid. The base of the pyramid shows the high resolution representation of the image
being processed; the apex contains the low resolution approximation. As we move up the pyramid
both the resolution and size decreases.
4. 198 Computer Science & Information Technology (CS & IT)
The detail signals (wavelet coefficients), which are composed of positive and negative integers,
on the other hand, require a signed representation. Their number precision, thus, exceeds the
original storage format. The significantly lower entropies of difference signals, however,
compensate for their longer internal word lengths, since they facilitate the use of efficient coding
methods.
A two-dimensional S-transform can be obtained by applying the 1-D S-transform sequentially to
the rows and columns of a color image. In this case (truncated) average (or LL) bands at
successively lower resolutions are recursively computed by
Where the (integer) averages along row along row r and incolor channel l are computed
via
)
Wavelet coefficients follow as associated directional differences. In Eq. (2), the sample Sk[m,n,l]
describes a color pixel at row m, column n, and spectral band l ,observed at resolution r = 2-k
.The
red, green and blue color bands are specified by indices l {1, 2, 3},respectively. For brevity, the
matrix of all pixels in the lth
color band at resolution 2-k
, 0 ≤ k ≤ K, is denoted as
The parameters M and N are image height and width, respectively. For simplicity, it is assumed
that M =N = 2K
. This facilitates a K-level wavelet transform.
The rounding operations introduce nonlinearity into the S-transform which produces a noteworthy
side-effect. Since both row and column averages are truncated, fractional parts are always
discarded. As a result, the transform becomes biased, i.e., integer scaling coefficients at
progressively lower resolutions get increasingly smaller than the true local averages. Although
this is a minor side-effect of the S-transform, the balanced rounding or BR-transform offers a
simple yet effective solution to this problem. It compensates for the round off error by rounding
up along image rows while truncating along image columns.
2.3 Spectral Decorrelation of Subband Channels
A reversible wavelet transform is first applied to each color band sk[l] at resolution 2-k
. These
yields three transform matrices
(4)
Where l {1,2,3}. Applying a reversible spectral transform (ST) to Sk+l[l], 0 ≤ l ≤ 3, we obtain
associated prediction errors denoted as
(5)
5. Computer Science & Information Technology (CS & IT) 199
The combination of inverse spectral transform (ST-l
) and inverse reversible wavelet transforms
(RWT-I
) finally reconstructs the original RGB color channels exactly as explained in Figure 2.
For a particular color l, the transform matrix Sk+l[l] can either be considered as an ensemble of
transform coefficients or be viewed as a collection of four oriented sub bands. Adopting the
second point of view, we describe a color sub band with orientation η at resolution 2-k-1
, as
(6)
for 1 ≤ l ≤ 3 and η {LL, LH, HL, HH}.
The letters stand for low (L) and high (H) bands corresponding to the separable application of low
pass of high pass filters along the rows and columns, respectively. Consequently, the LL-band of
S k+1[l] is called , the LH-band is represented by , the HL-band referred to as
and the HH-band finally denoted
Figure 2.Proposed color decorrelation method
Decomposing of original image into approx. (average) and wavelet (detail) coefficients are shown
below for 3 levels RWT.
Performing a K-level wavelet transform on so[l], the red band of the input color image with size
2K x 2K, we obtain a total of 3K + 1 oriented red sub bands. They comprise 3K channels with
wavelet coefficients and one low pass coefficient representing the mean of the red spectral band.
Applying the same RWT to the remaining green and blue color bands, we finally get sets of
associated red, green, and blue sub bands which can be effectively spectrally decorrelated. Since
there are potentially as many different spectral transforms for a K-level wavelet transform of
color images as there are different subbands, it is normally no longer possible to switch the order
of the spatial and spectral transforms. Instead, we gain the opportunity to apply an adaptive
spectral decorrelation method. It is based on Interband prediction.
2.3.1 Interband Prediction Procedure
The standard JPEG and JPEG 2000 compression schemes convert the image to YUV color space
to reduce the statistical dependency between channels. Rather than trying to reduce this
correlation between channels by transforming the color space, the proposed scheme tries to utilize
6. 200 Computer Science & Information Technology (CS & IT)
this redundancy by working with the R, G and B components of the image.Figure 3.depicts the
overall view of Interband Predictor.
Figure 3. Overall View of Interband Predictor
The steps in in Interband prediction procedure are as follows:
1)Each color channel is independently transformed using a wavelet transform (S) or DCT.
2) Prediction is then performed across the color channels:
(a) Choose an “anchor” color channel A which will not be predicted. This channel will allow the
data to be recovered during decompression by serving as the basis for predicting the second
channel.
(b) A second color channel B is then predicted from A using a linear predictor. =αA(7)
(c) The third color channel is then predicted from A and B using a linear
predictor. (8)
Note that the channels A, B and C are chosen so as to minimize the entropy of the residuals after
prediction.
3) The prediction errors are given by following formulae.
e1=A (9)
(10)
7. Computer Science & Information Technology (CS & IT) 201
(11)
2.3.2 Interband Prediction Coefficients
For three color bands, at most a two band predictor is needed to predict the third subband from
the remaining two. After Interband prediction, each color subband coefficient in the lth
band is
replaced by its difference with respect to the linear combination of the remaining spectral
neighbors. The two band prediction Sk+1
(η)
for the lth
color subband at resolution 2-k-1
and
orientation η can be compactly expressed as
(12)
With i ≠ j ≠ l and i, j, l Є {1,2,3}
and are the neighboring color subbands, while refers to the mean of the lth
color subbands. This third order prediction model gives rise to the following procedure for integer
subband residuals.
(13)
At spectral location l:
1) Compute prediction
(
14)
Where =E ( [.]). For high frequency subbands (wavelet coefficients), we have
(15)
integer values are enforced by using the rounding operator [.]R
2) Compute prediction error.
(16)
The error subband comprises differences between actual and predicted color subband
coefficients at the spatial locations
3) Encode prediction error and include all necessary side information such as prediction
coefficients. Then store or transmit it.
The prediction coefficients α1 and α2 are obtained by straight forward application of least square
regression formulas[3].
2.3.4 Interband Prediction Order
Reversible linear prediction must be implemented such that it can be resolved based on the
information already received. Since loss less prediction involves nonlinear rounding operations,
8. 202 Computer Science & Information Technology (CS & IT)
color subband Decorrelation must be carried out sequentially. To this end, an anchor band has to
be specified first. Its serves as a reference for predicting the second color subband. Finally the
first two subbands provide the basis from which to predict the remaining third. A prediction order
must be found such that the overall entropy after color subband prediction is minimized. If we
restrict ourselves to single subband prediction, then this problem can be modeled into a graph
theoretic problem. While such an approach wholes some promise for multispectral images with
hundreds of different bands, better color compression results are obtained when two band
predictions is also considered.
Then a scheme for color subband Decorrelation leads to 3! =6 different scenarios. For example,
the green subband component can be used as an anchor to predict the red, then red and green can
be employed to predict the blue subband coefficients. It determines the prediction order such that
approximated sum of subband entropies after prediction is smallest.
It can be shown that an approximation of the first order entropy of a color subband is given by
Above equation provides an entropy estimate for color subbands based on their shape factor,
and their variance .
Two obtain error variances; we select the anchor subband first. Let it be denoted as Sk+1(η).
Subtracting the associated rounded mean R, we get the first error subband ek+1(η)[i].
Next, the anchor band is used to predict the second color subband Sk+1(η)[j].The resulting
prediction error is called ek+1(η)[j]). Third, Sk+1(η)[i] and Sk+1(η) [j] are combined to
estimateSk+1(η) [l]. This two-step prediction yields the difference band ek+1(η)[l]. Finally the
variances of the error subbands are computed. They are:
Note that var{ek+1(η)[i]} is associated with a zero mean color subband, while var{ek+1(η)[j]}, and
var{ek+1(η)[l]} result from prediction residuals.
Once the variances have been computed, entropies of their associated subbands are estimated.
The sum of entropies of all three transform subbands at resolution 2-k-1 and orientation n is
called Hk+1(η). According to equation (5) it can be approximated by
9. Computer Science & Information Technology (CS & IT) 203
The shape factors γi, γj, γl are associated with pdf’s of and respectively.
Each prediction yields a different value for . The best ordering is found by selecting the
prediction sequence resulting in a smallest value for for simplicity, we assume that the
product of shape factors remains constant regardless of the prediction sequence chosen. The
underlying assumption is that the overall statistical character of the prediction errors remains the
same regardless of the prediction order. Since the logarithm is monotonically increasing, we only
need to compare products of error variances.
2.4 Calculations of Performance Metrics
2.4.1 Entropy
In information theory, entropy is a measure of the uncertainty associated with a random variable.
In this context, the term usually refers to the Shannon entropy, which quantifies the expected
value of the information contained in a message, usually in units such as bits. Entropy is a
measure of disorder, or more precisely unpredictability. For example, a series of coin tosses with
a fair coin has maximum entropy, since there is no way to predict what will come next. A string
of coin tosses with a two-headed coin has zero entropy, since the coin will always come up heads.
If a compression scheme is lossless, that is, we can always recover the entire original message by
uncompressing, then a compressed message has the same total entropy as the original, but in
fewer bits. That is, it has more entropy per bit. This means a compressed message is more
unpredictable, which is why messages are often compressed before being encrypted. Entropy
effectively bounds the performance of the strongest lossless (or nearly lossless) compression
possible.
It is defined as average information per source output denoted asH(z).This is also known as
uncertainty.
provides an entropy estimate for color subbands based on their shape factor, γx, and their
variance σx
2
.
2.4.2 PSNR (Peak Signal to Noise Ratio)
The PSNR is most commonly used as a measure of quality of reconstruction of image
compression. The signal in this case is the original data, and the noise is the error introduced by
compression.
Where,Err signal=input image -- output image
2.4.3 Average Bit Rate Per Pixel (bpp)
It is based on compressed file size and takes all the side information necessary to losslessly
reconstruct the original image. The lesser the value of bpp the better the compression.
10. 204 Computer Science & Information Technology (CS & IT)
Average bit rate per pixel (bpp) R = (total file length (in bits)) / no. pixels.
2.4.4 Compression Ratio (CR)
The compression ratio is equal to the size of the compressed image to the size of the original
image. This ratio gives an indication of how much compression is achieved for a particular image.
Most algorithms have a typical range of compression ratios that they can achieve over a variety of
images. Because of this, it is usually more useful to look at an average compression ratio for a
particular method.
3. RESULTS
Two standard color images Lenna (512 X 512) and Gold hill (720 X 576) are used to validate this
code whose results are discussedhere.
Table1: Results summary of Lenna and Goldhill images using RWT
Table1 gives an insight to salient results like PSNR, CR and bpp. Results indicate higher
compression ratios and lower bpp. The higher the PSNR indicate good quality of reconstruction
of an image.
Table 2: bpp comparison chart
Images
Lenna 4.35 11.115 11.113
Gold hill 4.31 12.540 12.554
Images Lenna Goldhill
No. of rows (M): 512 576
No. of columns (N): 512 720
No. of color bands (L) 3 3
No. of compression levels
(K): 4 4
Peak Signal to Noise Ratio
(PSNR): 36.88 35.66
Total number of bits in i/p
image: 6291456 9953280
Total number of bits in
compressed image: 1141500 1786100
Percentage of compression: 81.86% 82.06%
average bit rate per
pixel(bpp): 4.35 4.31
11. Computer Science & Information Technology (CS & IT) 205
Table 2 gives the comparison based on the average bit rate per pixel (bpp) simply denoted by R.
The bit rates obtained with S transforms followed by spectral decorrelation is indicated . The
outcomes associated with TT filter band are labeled and compression with reversible
embedded wavelet is labeled with . The results of last two columns referred in table 2 are
taken from [1]. One can observe the lowest bit rates with the implemented method.
4. CONCLUSIONS AND FUTURE SCOPE
In this paper we have demonstrated that interband prediction between RGB color channels can be
used to improve compression when used with wavelet transforms. The results of testing revealed
improved gains of several Db. Faster and exact reconstruction of image with minimum entropy
and variance is observed. This technique optimizes progressive image transmission with better
compression ratios and high PSNR values. S-Transform with predictor completely eliminates the
contouring artifacts usually present in bit plane coded images. The implemented algorithm can
achieve bit rates that are 20% less than results obtained with comparable lossless image
compression techniques supporting progressive resolution transmission of color images.
Interband prediction does not perform well if the image contains relatively low correlation
between the color channels. In this case the predictor is unable to accurately predict the color
channels and thus the error signals have a high variance, resulting in large entropy. A little
improvement beyond spatial decorrelation should be expected. A good reversible sub band
transforms are essential in this case. They are normally well designed filter banks characterized
by longer analysis high pass filters with higher stop band attenuation.
Fortunately, in many cases color bands are strongly correlated. Then a lossless image
compression for progressive resolution transmission requires a simple S-transform followed by
adaptive spectral prediction.
ACKNOWLEDGEMENTS
The authors would like to acknowledge the infrastructural support provided by VGST DST Gov.
of Karnataka to establish the center of excellence in Image and audio processing and implement
the above project. The authors would like to thank the Management and Principal CMRIT for all
the support.
REFERENCES
[1] N. Strobel, S. K. Mitra, and B. S. Manjunath.Reversible wavelet and spectral transforms for
lossless compression of color images. In Proc. IEEE Intern. Conf. Image Processing, ICIP-98,
volume3, pages 896–900, Chicago, IL, Oct 1998.
[2] Glen Gibb. Wavelet coding of color images using a spectral transform in the sub band domain.
Stanford, 2006.
[3] Fox, John."Linear Least Squares Regression." In Applied Regression Analysis, Linear Models, and
Related Methods,85-111. Thousand Oaks, CA: Sage, 1997.
[4] Grewal, B.S. Higher Engineering Mathematics, Khanna Publishers, New Delhi, 2010.
[5] Woods and Gonzalez. Digital Image Processing Using Matlab, Prentice Hall, 2004.
12. 206 Computer Science & Information Technology (CS & IT)
[6] Soman, K. P. and Ramchandran, K. I. Insight into Wavelets from Theory to Practice. Prentice-Hall
of India, 2010.
[7] S.R Tate, Band ordering in lossless compression by multi spectral images. IEEE Transactions on
Computers, Volume 46 Issue 4, April 1997.
[8] Stephen J. Chapman, MATLAB Programming for Engineers, 4e, Cengage Learning, 2008.
[9] Sanjit K. Mitra, Digital Signal Processing: A Computer-Based Approach, 4e, McGraw- Hill, 2010.
[10] N. Strobel, S. K. Mitra, and B. S. Manjunath. “Lossless compression of color images for digital
image libraries,”In Proceedings of the 13th
Inter-national Conference on Digital Signal Processing,
volume 1, pages 435-438, Santorin, Greece, 1997..
[11] W.K.Pratt, “Spatial transform coding of color images,”IEEE Transactions on Communications
Technology, 19(6):980-992, 1971.
[12] O.Rioul, “A discrete-time Multiresolution theory,” IEEE Transactions on Signal Processing,
41(8):2591-2606, 1995.
[13] M.J.Gormish, E.Schwartz, A.Keith, M.Boliek and A.zandi, “Lossless and nearly lossless
compression for high quality images” in Proceedings of the SPIE, volume 3025, SanJose, CA,
February 1997.
[14] Olivier Rioul and Martin Vetterli, “Wavelets and Signal Processing”, IEEE Trans. on Signal
Processing, Vol. 8, Issue 4, pp. 14 - 38 October 1991.
[15] Boliek, M., Gormish, M. J., Schwartz, E. L., and Keith, “A. Next Generation Image Compression
and Manipulation Using CREW”, Proc. IEEE ICIP, 1997.
[16] A. Zandi, J. Allen, E. Schwartz, and M. Boliek, “CREW: Compression with reversible embedded
wavelets,” IEEE Data Compression Conference, Snowbird, UT, pp. 212–221, March 1995.
[17] A. Said and W. A. Peralman, "An Image Multiresolution Representation for Lossless and Lossy
Compression," IEEE Trans. on Image Processing, Vol. 5, pp. 1303-1310, September 1996.
[18] Amir Said, and Pearlman. W. A, “ A New, Fast, and Efficient Image Codec Based on Set
Partitioning in Hierarchical Trees” IEEE Trans. Circuit and systems for Video Technology, vol. 6,
no. 3, pp. 243-250, June 1996.
[19] Asad Islam & Pearlman, “An embedded and efficient low-complexity, hierarchical image coder”,
Visual Communication and Image processing” 99 proceedings of SPIE.,Vol 3653,pp294-305, Jan.,
1999.
[20] J. Shapiro,” Embedded image coding using zero tress of wavelet coefficients," IEEE Trans. Signal
Processing 41, pp. 3445-3462, Dec. 1993.
13. Computer Science & Information Technology (CS & IT) 207
Authors
B.E, Electronics and Communication and M Tech, Industrial Electronics from
Vishveshvaraya technological University and pursuing Ph.D. in Dr M G R Educational
and Research Institute, Chennai; Having more than 20 years of experience in Industry
and Educational Institutions handling various responsibilities and currently working in
CMR Institute of Technology, Bangalore as professor and head, department of
electronics ; established several labs &conducted 2 National Conferences with the
support from DST/DIT/ISRO/DRDO/ISTE and conducted several courses & FDP;
Published 16 papers in national/International conferences and Journals.
The area of interest is VLSI and Embedded Systems; ISTE Life member.P.G. Scholar in
Digital Electronics from CMR Institute of Technology.Department of Electronics and
communication Bangalore, the area of interest is Analog and Digital Electronics, Image
processing and power Electronics.