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wavelet filter banr selection based on power spectral density

Wavelet filter banr selection based on power spectral densit...

引用

International conference on Computer and Automation Engineering, ICCAE

作者： Zohre Foroushi Mijid R. Ardestini Ali Asghire Beheshti Shirizi Image Processing Lab Iran University of Science and Technology Tehran Tehran Iran Imige Processing Lib School of Electricil Eng. Ir in University of Science ind Technology Tehrin Irin

Filter banr design for wavelet compression schemes is very important. Although, JPEG2000 standard adopted bi-orthogonal 9/7-tap Daubechies wavelet, it is experimentally shown that this banr is well suited for natural images, which they have small amount of energy in the high frequency in horizontal and vertical directions. In this paper, we introduce a method for filter banr design according to power spectral density function of input source. By this method we propose a new efficient 9/7 wavelet filter banr for image compression applications, whose coefficients are adaptively chosen according to power spectral density function of the input image. The experimental results for images by substituting our filter banr in the JPEG2000 standard coding mode show that little gain was obtained by for natural images, since they have small amount of energy in the high frequency bands in horizontal and vertical directions. However, 0.5–1 dB improvement of PSNR has been obtained for images such as Fingerprint, which have a large amount of energy in high frequency range.

关键词： image coding Filter bank Discrete wavelet transforms Bit rate image reconstruction Transform coding Frequency Density functional theory signal synthesis Band pass filters

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Fractional Fourier-Contourlet Deblurring of Space Variant Degradation Coupled with Noise

Fractional Fourier-Contourlet Deblurring of Space Variant De...

引用

International conference on Pervasive Computing signal processing and applications (PCSPA)

作者： Hui Wan Ran Tao Yue Wang Department of Electronic Engineering Beijing Institute of Technology Beijing China

Fourier domain deblurring methods are not fit for space variant degradation due to time invariant property of the Fourier transform (FT). Filtering in the fractional Fourier transform (FRFT) domain can deblur space variant degradation effectively, but hardly denoise substantially in the meantime. We propose a fractional Fourier-contourlet restoration algorithm to remove the space variant blur and the white Gaussian noise in images. The deblurring is realized by the fractional Fourier filtering while denoising through the coutourlet shrinkage. Our hybrid scheme is based on the MSE minimization principle. This scheme resolves the problem of contradiction between deblurring and denoising in a single transform domain. Experiments demonstrate that the proposed algorithm can yield favorable performance to satisfy both sides of deblurring and denoising.

关键词： Computed tomography Noise Noise reduction Degradation Filtering image restoration wavelet transforms

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TEMPORAL MOTION SMOOTHNESS MEASUREMENT FOR REDUCED-REFERENCE VIDEO QUALITY ASSESSMENT

TEMPORAL MOTION SMOOTHNESS MEASUREMENT FOR REDUCED-REFERENCE...

引用

IEEE International conference on Acoustics, Speech, and signal processing

作者： Kai Zeng Zhou Wang Dept. of Electrical and Computer Engineering University of Waterloo Waterloo Ontario Canada

ISBN: (纸本)9781424442959

Reduced-reference (RR) video quality measures aim to predict the perceptual quality of distorted video signals using only partial information about the reference video. Existing RR video quality assessment models are mostly designed and/or trained for specific applications such as lossy compression, where the detectable distortion types are often fixed and limited. Here we propose a novel approach that measures temporal motion smoothness of a video sequence by examining the temporal variations of local phase structures in the complex wavelet transform domain. We show that the proposed measure can detect a wide range of well-known practical distortions, including noise contamination, blurring, line or frame jittering, and frame dropping. In addition, the proposed algorithm does not require a costly motion estimation process and has a low RR data rate, making it much easier to be adopted in real-world visual communication applications.

关键词： perceptual image quality temporal motion smoothness reduced-reference video quality assessment complex wavelet transform local phase correlation video jittering video frame dropping complex wavelet transform Videotapes Video sequences Smoothness Video signals Sound contamination lossy compression motion estimation

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Enhanced B-spline based compression performance for images

Enhanced B-spline based compression performance for images

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Gamal Fahmy Til Aach German University in Cairo Egypt RWTH Aachen University Germany

The B-spline mathematical functions have long been utilized for signal representation, zooming and interpolation. However they have not been investigated for different image coding applications. In spite of the fact that B-splines are a semi-orthogonal basis (not full orthogonal) they still can be utilized for redundancy removal and decorrelation maximization prior to any compression scheme. This is due to their distinctive feature of preserving energy in low frequencies. In this paper we propose a novel technique for preprocessing signals/images prior to the decomposition stage in different image coders based on the B-spline decomposition. Mathematical explanation and derivation for the proposed B-spline decomposition basis is presented and analyzed. We derive our theoretic/mathematical justification, through some Eigen analysis calculations, for the enhancement in compression performance achieved with our B-spline based compression approach. We also present a straightforward approach for calculating the B-spline basis in a fast and efficient manner. Extensive simulations have been carried out on the well known SPIHT image coder with and without the proposed correlation removal methodology. Simulation results that demonstrate the effectiveness of the proposed technique are presented.

关键词： Spline image coding Discrete cosine transforms Correlation PSNR Pixel wavelet transforms

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A biometric identification system based on the fusion of palmprint and speech signal

A biometric identification system based on the fusion of pal...

引用

International conference on signal and image processing (ICSIP)

作者： P.K. Mahesh M.N. Shanmukha Swamy Department of Electronics and Communication J.S.S. research foundation Mysore University Mysore Karnataka India

Biometric systems allow automatic person recognition based on physical or behavioral features which belong to a certain person. Each biometric feature has its limits and no biometric system is perfect so unimodal biometric systems raise a variety of problems. To over fulfilling some of the mentioned inconvenient and limitations and to increase the level of security the multimodal biometric systems are used. This paper proposes the multimodal biometrics system for identity verification using two traits, i.e., speech signal and palmprint. The proposed system is designed for applications where the training data contains a speech signal and palmprint. The matching score level architecture uses weighted sum of score technique. The features are extracted from the pre-processed palm image and pre-processed speech signal. The features of a query image and speech signal are compared with those of a database images and speech signal to obtain matching scores. The individual scores generated after matching are passed to the fusion module. This module consists of three major steps i.e., normalization, generation of similarity score and fusion of weighted scores. The final score is then used to declare the person as genuine or an impostor. The system is tested on database collected by the authors for 120 subjects and gives an overall accuracy of 98.63% with FAR of 1.67% and FRR of 0.84%.

关键词： Speech Kernel Principal component analysis Feature extraction wavelet transforms Biometrics Filter bank

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Efficient medical image transformation method for lossless compression by considering real time applications

Efficient medical image transformation method for lossless c...

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International conference on signal processing and Communication Systems, ICSPCS

作者： Farshid Sepehrband Mohammad Mortazavi Seyed Ghorshi Jeiran Choupan School of Science and Engineering Sharif University of Technology Iran

Medical images contain human body pictures and used widely in diagnosis and surgical purposes. Compression is needed for medical images for some applications such as profiling patient's data or transmission systems Due to the importance of the information of medical images, lossless or visually lossless compression preferred. Lossless compression mainly consists of transformation and encoding steps. On the other hand, hardware implementation of lossless compression algorithm accelerates real time tasks such as online diagnosis and telemedicine. Lossless JPEG, JPEG-LS and lossless version of JPEG2000 are few well known methods for lossless compression. This paper is focused on the transformation step of compression and introduced a new transformation which is efficient in both entropy reduction and computational complexity. A new method is then achieved by improving the perdition model which is used in lossless JPEG. Our new transformation increases the energy compaction of prediction model and as a result reduces entropy value of transformed image. However, our new method is low complex. After a mathematical proof for efficiency of the new method, it is applied to more than hundreds of test-cases and the results are compared with previous methods and it shows about 8 percent improvement in average. As a result, the new algorithm shows a better efficiency for transforming lossless medical images, especially for online applications.

关键词： image coding Transform coding Entropy Compaction Biomedical imaging Pixel Discrete wavelet transforms

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A New Approach to Time-Frequency Analysis

A New Approach to Time-Frequency Analysis

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Data Compression conference (DCC)

作者： Xiteng Liu Electrical and Computer Engineering Department McMaster University Hamilton ONT Canada

ISBN: (纸本)9781424464258;9780769539942

Summary form only given. Time-frequency analysis is the fundamental methodology in signal processing. It provides a description of signal in the time-frequency plane. Conventionally, in applications of time-frequency analysis, the time domain of a signal is partitioned into intervals at first. Interval by interval, one computes the local frequency spectrum in an interval and then makes signal processing with respect to this local spectrum. The whole procedure goes on while time interval changes. This is the popular, classic approach to time-frequency analysis. To date, the research and applications of time-frequency analysis have been taking this approach. By this approach, signal contents are treated interval by interval locally in time. It neglects the statistical dependency between local frequency spectra in neighboring time intervals. Data compression is an important and successful application of time-frequency analysis. The international standards JPEG(1990), MPEG1(1993), MPEG2(1994), MPEG4(1998), H.264(2003) and JPEG XR(2009) are all good examples. In these systems, image data are encoded in the classic approach to time-frequency analysis. Separately block by block, image data are transformed, quantized and entropy encoded. Another mentionable image coding scheme in classic approach was introduced, where image data are transformed by 8 x 8 DCT. After transform, the 64 coefficients in an 8 x 8 block are treated as a depth-3 tree, without any inter-block regroupment or other operations. Within each block, the coefficients are separately quantized and encoded by the famous EZW method which is popular in wavelet-based image coding. In this paper, we change the way and advocate a new approach to time-frequency analysis. We make signal processing within frequency bands rather than time intervals. We treat signal contents band by band locally in frequency. The new approach gives rise to a good platform to exploit the dependency between local frequency spectra. The ba

关键词： Time frequency analysis signal processing Transform coding Data compression image coding Data engineering Application software Time domain analysis Entropy Discrete cosine transforms

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Statistical measurement of ultrasound placenta images using segmentation approach

Statistical measurement of ultrasound placenta images using ...

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International conference on signal and image processing (ICSIP)

作者： G. Malathi V. Shanthi Department of Computer Science Mother Teresa Women''s University Kodaikannal India Department of Computer Applications Saint Joseph''s College of Engineering Chennai India

Medical diagnosis is the major challenge faced by the medical experts. Highly specialized tools are necessary to assist the experts in diagnosing the diseases. Gestational Diabetes Mellitus is a condition in pregnant women which increases the blood sugar levels. It complicates the pregnancy by affecting the placental growth. The ultrasound screening of placenta in the initial stages of gestation helps to identify the complication induced by GDM on the placental development which accounts for the fetal growth. This work focus on the classification of ultrasound placenta images into normal and abnormal images based on statistical measurements. The ultrasound images are usually low in resolution which may lead to loss of characteristic features of the ultrasound images. The placenta images obtained in an ultrasound examination is stereo mapped to reconstruct the placenta structure from the ultrasound images. The dimensionality reduction is done on stereo mapped placenta images using wavelet decomposition. The ultrasound placenta image is segmented using watershed approach to obtain the statistical measurements of the stereo mapped placenta images. Using the statistical measurements, the ultrasound placenta images are then classified as normal and abnormal using Back Propagation neural networks.

关键词： image segmentation Ultrasonic imaging image edge detection Pixel Diabetes Kernel Ultrasonic variables measurement

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A comprehensive approach for texture classification

A comprehensive approach for texture classification

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International Symposium on signal processing and Its applications (ISSPA)

作者： P. Ammi Reddy P. S. R. Chandra Murty E. Sreenivasa Reddy Jawaharlal Nehru Technological University Kakinada A.P. India Department of Computer Science and Engineering Vasireddy Venkatadri Institute of Technology Guntur A.P. India

Classification of textures based on wavelet pattern analysis is one of the most effective methods in texture classification. However using all frequency sub-bands in decomposition for classification may increase time complexity of classification algorithms. To reduce the time complexity, sub-bands with high energy and entropy are selected for classification. Fractal dimension can be used to select such significant sub-bands for decomposition at each level. Further statistical features of these significant sub-bands are given to modified K-NN classifier for classification. This paper describes texture classification using sub-bands of wavelets based on fractal dimensions and their results are compared with the results of texture classification using conventional features and also with different classifiers. Success rate is very high and time complexity is also reduced to the order of O(n).

关键词： Wool Weaving image recognition Computers

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Digital image watermarking scheme based on histogram in DWT domain

Digital image watermarking scheme based on histogram in DWT ...

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International conference on Digital Content, Multimedia Technology and its applications (IDC)

作者： Xiao-Chen Yuan Chi-Man Pun Department of Computer and Information Science University of Macau Macao China

A robust and geometric invariant digital watermarking scheme for gray-level images is proposed in this paper. The scheme carries out watermark embedding and extraction based on histogram in DWT domain. For watermark embedding, the original image is decomposed into the approximation and details sub-bands. Pixels of the approximation sub-band are grouped into m blocks, each of which has the same number of intensity-levels, thus the block histogram is generated; with the block histogram, pixels are moved to form a specific pattern in the intensity-level histogram distribution, indicating the watermark. For watermark extraction, the watermarked image is decomposed into the approximation and details sub-bands; then the pixels in the approximation sub-band are grouped into blocks in the similar manner. According to the histogram distribution in each block, the watermark is extracted. Experimental results show that the proposed scheme is highly robust against JPEG compression, geometric attacks and some common signal processing.

关键词： image coding Discrete wavelet transforms Fractals Robustness Cryptography Pixel Transform coding

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