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International Conference on Electrical and Electronics Engineering

作者： Selcuk Aslan Hasan Badem Dervis Karaboga Alper Basturk Tayyip Ozcan Erciyes University Engineering Faculty Computer Engineering Department

ISBN: (纸本)9781467379120

The Discrete Haar wavelet Transform has a wide range of applications from signal processing to video and image processing. Data-intensive structure and easy of implementation make Discrete Haar wavelet Transform convenient to distribute fundamental operations to multi-CPU and multi-GPU systems. In this paper, the wavelet transform was ported in a compute-efficient way to CPU cluster and programmable GPU cluster by utilizing MPI and CUDA respectively. Experimental studies conducted as part of the parallelization strategies for two-dimensional Discrete Haar wavelet Transform show that the total running time required to process all rows and columns of an image with different size is significantly decreased on the GPU cluster when compared to the its counterparts on a single CPU, single GPU and CPU cluster. Besides the speedup of the GPU based transform, preliminary analysis also showed that the size of the image is an important parameter on the scalability of the GPU cluster.

关键词： GPU CPU CUDA

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An efficient low dynamic range image compression using improved block based EZW

An efficient low dynamic range image compression using impro...

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IEEE Workshop on Computational Intelligence: Theories, applications and Future Directions (WCI)

作者： Ch. Naveen V. R. Satpute A. G. Keskar Department of ECE VNIT Nagpur India

ISBN: (纸本)9781467382199

This papers deals with an efficient image compression technique for images having low dynamic range. The images with low dynamic range generally have low intensity variations. By considering this fundamental characteristic into account we can go for image compression at higher ratio with small modifications to the existing block based EZW algorithm. To achieve the improvement in compression ratio, block-wise Embedded Zero wavelet (EZW) is applied on the images by forcing all the blocks in the image to take the same number of dominant and sub-ordinate passes. The number of passes applied on each block of the image will be equal to the lowest number of passes taken by one of the blocks in image. This downside the number of passes applied on the image which reduces the number of bits used for encoding the image which successively increase the compression ratio. The proposed algorithm is analyzed with respect to the normal block-wise EZW by mathematical parameters as well as with visual quality. The mathematical parameters chosen for comparison are Peak signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) index. The algorithm is tested from low resolution to UHD resolution images.

关键词： image coding Discrete wavelet transforms image reconstruction Algorithm design and analysis Decoding Dynamic range signal processing algorithms

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Multiscale Derivative Transform and Its Application to image Watermarking

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DIGITAL signal processing 2014年 33卷 148-155页

作者： Nezhadarya, Ehsan Ward, Rabab K. Univ British Columbia Dept Elect & Comp Engn Vancouver BC V5Z 1M9 Canada

A transform that estimates the first and higher-order derivatives of images at multiple scales is proposed. The proposed transform, called Multi-Scale Derivative Transform (MSDT), is specially designed for image watermarking applications. To calculate the first and higher-order image derivatives, MSDT uses the detail wavelet coefficients of the image. Unlike traditional wavelet-based image derivative estimators that use only the horizontal and vertical wavelet coefficients, the proposed transform maps the diagonal as well as the horizontal and vertical wavelet coefficients to the horizontal and vertical derivatives of the image. The inverse transform is designed such that any change in the image derivative domain results in the minimum possible change in the wavelet coefficients. This renders a watermark, that is embedded in the derivative domain, less visible in the image domain. The application of this transform to image watermarking is discussed, and the results are compared with those obtained using traditional wavelet-based image derivative estimators. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Derivative transform wavelet transform Watermarking Multi-scale transform Angle quantization index modulation (AQIM)

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A New Approach for an Effective Eye Movement Artifact Elimination from EEG signal

A New Approach for an Effective Eye Movement Artifact Elimin...

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IEEE International Conference on signal and image processing applications

作者： Ibrahim Amer Ibrahim Jayasree Santhosh Mahmoud Moghawemi Dept. of Electrical Engineering University Malaya 50603 Kuala Lumpur Malaysia ALKHWARIZMI Engineering University of Baghdad Baghdad Iraq Dept. of Biomedical Engineering University Malaya 50603 Kuala Lumpur Malaysia Dept. of Electrical Engineering University Malaya 50603 Kuala Lumpur Malaysia Center of Research in Applied Electronics (CRAE) University of Science and Culture Tehran Iran

ISBN: (纸本)9781479989973

EEG signals collected non-invasively from the cerebral cortex are often contaminated with signals from eye movement [EOG], which considerably degrades the reliability of extracting proper information from the actual signals. This study attempts a two-step algorithm to obtain an EOG artifact free EEG signal with best performance index. Two types of decomposing methods namely Discrete wavelet Transform (DWT) and Empirical Mode Decomposition (EMD) were used initially to decompose the contaminated signal The resultant signal further undergoes two processes each;first by Canonical Correlation analysis (CCA) technique and the second one by reduced frequency components using threshold level to identify the unwanted frequency components (TH.-FFT). The output signal from each of these two processes are reconstructed to obtain a clean signal Comparison between the reconstructed cleaned signals and the contaminated EEG signal reveal that the reconstructed signal is cleaner when (CCA) technique was used as compared with that of (TH.-FFT). Thus the performance indexes of this experiment for the two methods, measured with RMSD and SDR, indicated that combined DWT, EMD and CCA method outperforms the combined DWT, EMD and TH.-FFT method in elimination of eye movement contamination from EEG signal. The present algorithm gave better performance results compared to other existing methods and hence would be better suited for various offline analyses involving the low frequency bands of EEG signals.

关键词： EEG (Electroencephalogram) EOG (Electrooculography) CCA (Canonical Correlation analysis) EMD (Empirical Mode Decomposition) DWT (Discrete wavelet Transform) Artifact Elimination signals Electroencephalography Eye Movements handicrafts Artifacts Frequency bands Electrooculography Cleaners outgoing signal SDPR gene

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Exponential spline perfect reconstruction, decomposition and reconstruction with applications in compression and denoising

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signal image AND VIDEO processing 2014年第6期8卷 1111-1120页

作者： Fahmy, M. F. Fahmy, Gamal Assiut Univ Dept Elect Engn Asyut Egypt Majmaah Univ Dept Elect Engn Al Majmaah Saudi Arabia

B-splines caught interest of many engineering applications due to their merits of being flexible and provide a large degree of differentiability and cost/quality trade-off relationship. However, they have less impact with continuous-time applications as they are constructed from piecewise polynomials. On the other hand, exponential spline polynomials (E-splines) represent the best smooth transition between continuous and discrete domains as they are made of exponential segments. In this paper, we present a complete analysis for an E-spline-based subband coding (wavelet) perfect reconstruction (PR) system. Derivations for the scaling and wavelet functions are presented, along with application of the proposed system in image compression and image denoising. In image compression, a comparison of the proposed technique compared with the B-spline-based PR system as well as the basic wavelet subband system with the SPIHT image codec is presented. In image denoising, we report the enhancement achieved with the proposed E-spline-based denoising approach compared with B-spline-based denoising and another basic denoising technique. In both applications, E-splines show superior performance as will be illustrated.

关键词： Cardinal exponential splines image compression image denoising

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Classification of breast masses in mammogram images using KNN

Classification of breast masses in mammogram images using KN...

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IEEE signal processing and Communications applications (SIU)

作者： Nuh Alpaslan Asuman Kara Büşra Zenci̇r Davut Hanbay Bilgisayar Mühendisliği Bölümü İnönü Üniversitesi Malatya Inonu Universitesi Malatya Malatya TR

Breast cancer is one of the most deadly diseases for women. Mammogram is very important imaging technique used diagnosis in early stages of breast cancer. In this study, a decision support system which helps experts to examine mammogram images in the fight against breast cancer is developed. In this study, firstly several preprocesses are applied to mammogram to make image clear and segmentation of mass is provided with an appropriate threshold value. After the segmentation processes, features of the tumor mass are obtained. The obtained features are classified as normal, benign or malignant using kNN (k-nearest neighbours) classifiers. In this study, its have been were shown that, effect of kurtosis, skewness and wavelet energy features on classification performance is shown. As a result, it has been seen that, these features improve the classification performance.

关键词： Mammography Histograms Breast cancer Delta-sigma modulation image segmentation Art

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Block-based two-dimensional wavelet transform running on graphics processing unit

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IET COMPUTERS AND DIGITAL TECHNIQUES 2014年第5期8卷 229-236页

作者： Song, Changhe Li, Yunsong Guo, Jie Lei, Jie Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China

This study explores the use of the graphics processing units (GPUs) for performing the two-dimensional discrete wavelet transform (DWT) of images. The study of fast wavelet transforms has been driven both by the enormous volumes of data produced by modern cameras and by the need for real-time processing of these data. With the emergence of general computing on GPUs, many time-consuming applications have started to reap the associated benefits. In the implementation of a GPU-based DWT, two approaches are used according to the published works, which are the row-column (RC) approach and the block-based (BB) approach. Most state-of-the-art techniques are based on the RC approach, which utilises the parallelism between different rows and columns;few works are based on the BB approach, which explores the parallelism between different blocks of the image. Although easy to implement, resource usage of the RC approach is usually related to the image size. Another shortcoming of the RC approach lies in the fact, according to the author's analysis, that more global memory access is required. The authors thus select the BB approach in this study. Experiment results show that the proposed BB approach outperforms the RC approach, being 99x faster than a native CPU implementation for 4096 x 4096 images.

关键词： image processing graphics processing units data volumes Microprocessor chips GPU block based two dimensional wavelet transform Integral transforms RC approach real-time systems time consuming applications graphics processing unit row column approach Microprocessors and microcomputers discrete wavelet transforms DWT real-time processing two dimensional discrete wavelet transform Optical, image and video signal processing Computer vision and image processing techniques global memory access BB approach block based approach

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基于多尺度的自适应采样图像分块压缩感知算法

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微型机与应用 2016年第24期35卷 42-45,49页

作者：殷长涛文志强胡骏飞智能信息感知及处理技术湖南省重点实验室湖南株洲412007

基于分块的压缩感知算法适用于图像信号的处理,通过平滑迭代阈值投影法可以快速重构图像,但存在低采样率下重构图像质量较差的缺点。基于全变差分的分块压缩感知算法,在一定程度上能提升重构效果,但降低了运算速度。针对以上算法的不足... 详细信息

基于分块的压缩感知算法适用于图像信号的处理,通过平滑迭代阈值投影法可以快速重构图像,但存在低采样率下重构图像质量较差的缺点。基于全变差分的分块压缩感知算法,在一定程度上能提升重构效果,但降低了运算速度。针对以上算法的不足,提出基于多尺度的自适应采样图像分块压缩感知算法。根据小波分解后不同层对重构结果影响所占权重不同的特性,自适应分配给每一层不同的采样率,并在重构时将平滑迭代阈值投影法应用到每一层的每一个子带的分块上。实验结果表明,与传统的迭代阈值投影法相比在重构质量上提高了1~3 d B,在重构速度上与迭代阈值投影法相当并优于全变差分法。

关键词：压缩感知多尺度小波变换自适应采样图像分块

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Secure Hybrid Robust Watermarking Technique for Medical images

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Procedia Computer Science 2015年 70卷 778-784页

作者： Abhilasha Sharma Amit Kumar Singh S.P. Ghrera Department of Computer Science & Engineering Jaypee University of Information Technology Waknaghat Solan Himachal Pradesh India

The protection of data is of at prime urgency in the medical field to boost the telemedicine applications. There is a need of robust and secure mechanism to transfer the medical images over the Internet. The proposed watermarking method is based on two popular transform domain techniques, discrete wavelet transforms (DWT) and discrete cosine transform (DCT). In the embedding process, the cover medical image is divided into two separate parts, region of interest (ROI) and non region of interest (NROI). For the identity authentication purpose, multiple watermarks in the form of image and text are embedding into ROI and NROI part of the same cover media object respectively. In order to enhance the security of the text watermark, Rivest-Shamir-Adleman (RSA) encryption technique is applied to the text watermark before embedding and the encrypted EPR data is embedded into the NROI portion of the cover medical image. The performance of the proposed method is evaluated for signal processing attacks and the desired outcome is obtained without significant degradation in extracted watermark and perceptual quality of the watermarked image.

关键词： DWT DCT medical image image and text watermarks RSA ROI and NROI

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Characteristics analysis of wavelet coefficients and its applications in image compression

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INTERNATIONAL JOURNAL OF waveletS MULTIRESOLUTION AND INFORMATION processing 2014年第3期12卷

作者： Lang, Fangnian Zhou, Jiliu Tang, Yuan Yan Yu, Hongnian Cang, Shuang Shang, Zhaowei Chengdu Univ Coll Comp Sci Chengdu 610106 Peoples R China Sichuan Univ Coll Comp Sci Chengdu 610065 Peoples R China Univ Macau Coll Sci & Technol Taipa Macau Peoples R China Bournemouth Univ Sch Tourism Poole Dorset England Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China

Currently, the wavelet transform is widely used in the signal processing domain, especially in the image compression because of its excellent de-correlation property and the redundancy property included in the wavelet coefficients. This paper investigates the redundancy relationships between any two or three components of the wavelet coefficients, the wavelet bases and the original signal. We discuss those contents for every condition according to the continuous form and the discrete form, respectively, by which we also derive a uniform formula which illuminates the inherent connection among the redundancy of the wavelet coefficients, the wavelet bases and the original signals. Finally, we present the application of the wavelet coefficient redundancy property in the still image compression domain and compare the properties of the Discrete wavelet Transform (DWT) with that of the Discrete Cosine Transform (DCT).

关键词： wavelet coefficient wavelet basis sampling theorem wavelet reproducing kernel function JPEG2000

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