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A Scheme of image coding with high compression

西南师范大学学报(自然科学版) 1999年第5期 556-561页

作者： Tang Xianghong 1,He Zhenhua 2 1 Deparment of Educational Technology,Southwest China Normal University,Chongqing 400715 2 Deparment of Information Engineering and Geophysics,Chengdu Institute of Technology,Chengdu 610059

Based on the M band wavelet transform, the properties of wavelet coefficient are analyzed. And a new scheme for image compression is proposed by using the M band wavelet transform and human visual properties. The expe... 详细信息

关键词： M band wavelet transform multiresolution analysis entropy coding quantization

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Progressive transmission of high-fidelity radiographic images at very low bit rates

Progressive transmission of high-fidelity radiographic image...

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Medical Imaging 1999 Conference - Image Processing

作者： Yang, SY Mitra, S Texas Tech Univ Dept Elect Engn Lubbock TX 79409 USA

ISBN: (纸本)0819431338

Compression of medical images has always been viewed with skepticism since the loss of information involved is thought to affect diagnostic information. Recent reports, however, indicate that some wavelet based compression techniques may not effectively reduce the image quality even when subjected to compression ratios (CRs) up to 30:1. Although generation of minimum distortion at a specific bit rate by vector quantization (VQ) has been theoretically proven from rate distortion theory almost half a century ago, practical implementation of VQ for small sizes and classes of images has been accomplished relatively recently. Many of the earlier algorithms using simple statistical clustering suffer from a number of problems namely lack of convergence, getting trapped in local minima, and inability to handle large datasets. More advanced vector quantization algorithms have eliminated some of the above problems. However, vector quantization of large data sets as encountered in many medical images still remains a challenging problem. We present here an adaptive vector quantization technique including an entropy coding module that is capable of encoding large size radiographic as well as color images with minimum distortion in the decoded images even at CRs above 100:1.

关键词： Optimized codebook adaptive vector quantization entropy coding progressive transmission high fidelity radiographic image transmission large color image compression

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Arithmetic coding with dual symbol sets and its performance analysis

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1999年第12期8卷 1667-1676页

作者： Zhu, B Yang, EH Tewfik, AH Cognicity Inc Edina MN 55439 USA Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Univ Minnesota Dept Elect Engn Minneapolis MN 55455 USA

In this paper, we propose a novel adaptive arithmetic coding method that uses dual symbol sets: A primary symbol set that contains all the symbols that are likely to occur in the near future and a secondary symbol set that contains all other symbols. The simplest implementation of our method assumes that symbols that have appeared in the recent past are highly likely to appear in the near future. It therefore fills the primary set with symbols that have occurred in the recent past. Symbols move dynamically between the two symbol sets to adapt to the local statistics of the symbol source. The proposed method works well for sources, such as images, that are characterized by large alphabets and alphabet distributions that are skewed and highly nonstationary, We analyze the performance of the proposed method and compare it to other arithmetic coding methods, both theoretically and experimentally, We show experimentally that in certain contexts, e.g,, with a wavelet-based image coding scheme that has recently appeared in the literature, the compression performance of the proposed method is better than that of the conventional arithmetic coding method and the zero-frequency escape arithmetic coding method.

关键词： arithmetic coding data compression entropy coding image compression JPEG wavelet

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Vector-scalar classification for transform image coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1999年第9期8卷 1175-1182页

作者： Pan, JP CommQuest Encinitas CA 92024 USA

This paper introduces vector-scalar classification (VSC) for discrete cosine transform (DCT) coding of images, Two main characteristics of VSC differentiate it from previously proposed classification methods, First, pattern classification is effectively performed in the energy domain of the DCT subvectors using vector quantization, Second, the subvectors, instead of the DCT vectors, are mapped into a prescribed number of classes according to a pattern-to-class link established by scalar quantization. Simulation results demonstrate that the DCT coding systems based on VSC are superior to the other proposed DCT coding systems and are competitive compared to the best subband and wavelet coding systems reported in the literature.

关键词： classification DCT image coding entropy coding image coding quantization

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Lossless image compression based on an enhanced fuzzy regression prediction

Lossless image compression based on an enhanced fuzzy regres...

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IEEE International Conference on Image Processing

作者： B. Aiazzi S. Baronti L. Alparone CNR Firenze Italy Nello Carrara I.R.O.E.-C.N.R Florence Italy Department Electron. Engin University of Florence Florence Italy

An effective method for lossless image compression is presented. It relies on a classified linear-regression prediction obtained through fuzzy techniques, followed by context based modeling of the outcome prediction errors, to enhance entropy coding. The present scheme is a reworking of the fuzzy encoder presented at ICIP'98 (FDC). Now, predictors, instead of pixel intensity patterns, are fuzzy-clustered to find out optimized MMSE prediction classes, and a novel membership function measuring the fitness of prediction is adopted. Size and shape of causal neighborhoods supporting prediction, as well as number of predictors to be blended, may be chosen by user and settle the tradeoff between coding performances and computational costs. The encoder exhibits impressive performances, thanks to the skill of predictors in fitting data patterns as well as to context modeling.

关键词： Image coding Pixel Context modeling entropy coding Predictive models Shape Computational efficiency Image reconstruction Biomedical imaging Medical diagnostic imaging

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Efficient shape coding algorithm for object-oriented video in MPEG-4

Efficient shape coding algorithm for object-oriented video i...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Chil-Cheang Ma Mei-Juan Chen Po-Yuen Cheng Institute of Electrical Engineering Taiwan

A new shape coding algorithm to improve coding efficiency is proposed. The proposed vertex selection scheme can reduce the shape points of the boundary for lossless coding and the area distortion criterion provides go... 详细信息

ISBN: (纸本)0780351231

关键词： Shape MPEG 4 Standard Turning Testing Propagation losses Arithmetic Sampling methods Encoding entropy coding Clocks

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Subband coding of RF signals in reconfigurable computing hardware

Subband coding of RF signals in reconfigurable computing har...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： C.M. Brislawn S.H. Robinson S.A. Crockett Los Alamos National Laboratory Los Alamos NM USA

A subband coding algorithm is designed for compression of wideband RF data and eventual implementation on a reconfigurable computer board. The algorithm involves a multirate filter bank, adaptive uniform scalar quantization, and Huffman entropy coding. We report the performance of the algorithm in software on RF data from the DOE satellites ALEXIS and FORTE. A reconfigurable computer array board, RCA-2, designed and assembled at LANL is presented as a target platform for hardware implementation of the algorithm.

关键词： Hardware Algorithm design and analysis Radio frequency Wideband Filter bank Quantization entropy coding Software algorithms Software performance US Department of Energy

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Probability estimation of binary information sources for image coding

Probability estimation of binary information sources for ima...

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IEEE International Conference on Image Processing

作者： I. Ueno T. Kimura T. Yanagiya M. Yoshida F. Ono Information Technology Research and Development Center Mitsubishi Electric Corporation Limited Kamakura Kanagawa Japan

Probability estimation of symbol occurrence in adaptive entropy coding used for efficient image coding can be classified into two types. One is Bayesian probability estimation, in which the probability is estimated by using accumulated occurrence counts of the information source symbols. The other is state transition probability estimation in which the probability is estimated through a state transition not always caused by every occurrence of information source symbols. In this paper, we examine the characteristic of both of the probability estimation methods, and propose a new probability estimation method in which either of the two is switched adaptively. We confirmed that the proposed probability estimation provides a higher compression performance on random sequences having wide range of occurrence probabilities, and also works well on coding of various images.

关键词： Image coding State estimation entropy coding Bayesian methods Counting circuits Arithmetic Probability Information technology Research and development Random sequences

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Zerotree coding of wavelet coefficients for image data on arbitrarily shaped support

Zerotree coding of wavelet coefficients for image data on ar...

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Data Compression Conference (DCC)

作者： A. Kawanaka V.R. Algazi Faculty of Science and Thechnology Sophia University Tokyo Japan Department of Electrical and Computer Engineering University of California Davis CA USA

[Summary form only given]. A wavelet coding method for arbitrarily shaped image data, applicable to object-oriented coding of moving pictures, and to the efficient representation of texture data in computer graphics is proposed. The wavelet transform of an arbitrarily shaped image is obtained by applying the symmetrical extension technique at region boundaries and keeping the location of the wavelet coefficient. For entropy coding of the wavelet coefficients, the zerotree coding technique is modified to work with arbitrarily shaped regions by treating missing (outside of the decomposed support) coefficients as insignificant and transmitting only those zerotree symbols which are in the decomposed support. The coding performance of the proposed method for several test images that include a person, a teapot and a necklace is compared to a shape-adaptive DCT and an ordinary DCT method applying low pass extrapolation to the DCT block containing the region boundaries. Experiments show that the proposed method has a better coding efficiency compared to SA-DCT and the ordinary DCT method.

关键词： Image coding Wavelet coefficients Discrete cosine transforms Data engineering Computer graphics Wavelet transforms entropy coding Testing Extrapolation PSNR

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A perceptually-tuned image coder with Channel-Optimized Trellis-Coded Quantization

A perceptually-tuned image coder with Channel-Optimized Trel...

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IEEE International Conference on Image Processing

作者： Tuyet Trang Lam G.P. Abousleman L.J. Karam TeleCommunication Research Center Department of Electrical Engineering Arizona State University Tempe AZ USA Speech and Signal Proc. Lab Motorola Systems Solutions Group Scottsdale AZ USA

A system is presented for the compression of digital imagery over binary symmetric channels (BSC). The objective is to minimize the perceived distortion for a desired target bit rate. The proposed system utilizes wavelet decomposition, channel-optimized trellis-coded quantization (COTCQ), and a perceptually-tuned rate allocation scheme to control the quantization. Because of the inherent noise-robust properties of the COTCQ stage, no channel coding is employed. Additionally, the COTCQ design does not utilize entropy coding. Consequently, the proposed image coder is especially suitable for wireless transmission due to its reduced complexity and robustness to channel errors. Examples are presented to illustrate the performance of the proposed image coding system.

关键词： Quantization Image coding Noise robustness Channel coding Costs Telecommunications Digital images Bit rate entropy coding Error probability

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