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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yun Gong Department of Electrical Engineering Widener University Chester PA USA

ISBN: (纸本)0780388747

A classified context quantization (CCQ) technique is proposed to code basic image VQ indexes in the setting of high order context models. The context model of an index is first classified into one of three classes according to the smoothness of the image area they represent. Then the index is coded with a context quantizer designed for that class. Experimental results show that CCQ achieves about three percent improvement over the previous best results of image VQ by conditional entropy coding of VQ indexes (CECOVI), and does so at a lower computational cost.

关键词： Image coding Context modeling entropy coding Pixel Computational efficiency Vector quantization Transform coding Bayesian methods

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A study on non-octave scalable coding using motion compensated inter-frame wavelet transform

A study on non-octave scalable coding using motion compensat...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： T. Nakachi T. Fujii NTT Network Innovation Laboratories Yokosuka Kanagawa Japan

JPEG2000, an international standard for still image compression, has three main features: 1) high coding performance; 2) unified lossless/lossy compression; and 3) resolution and SNR scalability. Resolution scalability is especially promising given the popularity of super high definition (SHD) images like digital-cinema. Unfortunately, the resolution scalability of its current implementation is restricted to powers of two. In this paper, we introduce non-octave scalable coding with a motion compensated interframe wavelet transform. By using the proposed algorithm, images of rational scales can be decoded from a compressed code stream. Experiments on SHD digital cinema test sequences show the effectiveness of the proposed algorithm.

关键词： Wavelet transforms Scalability Image coding Image resolution entropy coding Transform coding Image converters Filter bank Decoding Performance loss

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Fast macroblock intra and inter modes selection for H.264/AVC

Fast macroblock intra and inter modes selection for H.264/AV...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： E. Arsura L. Del Vecchio R. Lancini L. Nisti CEFRIEL-Politecnico di Milano Italy

The major complexity source in H.264 is the rate distortion (R-D) optimization. This work proposes a method to reduce the complexity of R-D analysis, paying a little video degradation, by estimating the encoding modes that are more likely used by the encoder. Since the encoding modes depend mainly on the typology of the video and on the quantization parameter used to encode each block, the work proposes to group the modes into subsets that depend on the quantizer level and the characteristics of the video. In particular, the motion compensability of each frame modulates the intra modes, while texture difficulty addresses the inter modes. The R-D algorithm evaluates only the modes included into the resulting subset. The usage of subset modes reduces the complexity of the encoding process (40-70%) with respect to the original R-D optimized encoder, with a slight PSNR reduction (0-0,30 dB).

关键词： Automatic voltage control Encoding Quantization Motion estimation Rate-distortion Degradation PSNR Video coding Cost function entropy coding

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On context-based entropy coding of block transform coefficients

On context-based entropy coding of block transform coefficie...

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IEEE International Conference on Image Processing

作者： Chengiie Tu T.D. Tran Department of Electrical and Computer Engineering Johns Hopkins University Baltimore MD USA

It has been well established that state-of-the-art wavelet image coders outperform block transform image coders in the rate-distortion (R-D) sense by a wide margin. An often asked question is: how much of the coding improvement is due to the transform and how much is due to the encoding strategy? A notable observation is that each block transform coefficient is highly correlated with its neighbors within the same block as well as its neighbors within the same subband. Current block transform coders suffer from poor context modeling and fail to take full advantage of intra- and inter-block correlation in both space and frequency sense. This paper presents a simple, fast and efficient adaptive block transform image coding algorithm based on high-order space-frequency, context modeling. Despite the simplicity constraints, coding results show that the proposed codec achieves competitive R-D performances comparing to the best wavelet codecs in the current literature.

关键词： entropy coding Image coding Frequency Discrete cosine transforms Wavelet transforms Context modeling Discrete wavelet transforms Transform coding Codecs Discrete transforms

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A novel DCT-based bit plane error resilient entropy coding scheme and codec for wireless image communication

A novel DCT-based bit plane error resilient entropy coding s...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Yew-San Lee Cheng-Mou Yu Hung-Kuo Wei Yen-Hsu Shih Chen-Yi Lee Department of Electronics Engineering National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)0780374487

We propose a novel bit plane error resilient entropy coding scheme for DCT-based image compression, which can control and minimize the error propagation effect. The compressed rate is similar to the JPEG standard. However, it uses only 18 VLC symbols. Hardware implementation cost and power consumption can then be minimized. Base on simulation results, the proposed coding scheme can achieve high image quality (PSNR=29.82 dB) even at bit error rate of 10/sup -3/. An image codec has been implemented for verifying the proposed bit-plane EREC coding technique. It can compress and decompress CIF size (352/spl times/288, 4:2:0 format) images at the rate of 30 frames per second using 20 MHz clock rate. It only occupies 36 k gate count and 1.90/spl times/1.90 mm/sup 2/ silicon area in a 0.35 /spl mu/m CMOS process. With 3.3 V power supply, the simulated power consumption is only 27 mWatt and 0.41 mA/MHz. This performance can meet various wireless portable multimedia system requirements.

关键词： entropy coding Codecs Wireless communication Image communication Image coding Error correction Energy consumption Communication system control Transform coding Hardware

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Causal coding of individual sequences and the Lempel-Ziv differential entropy

Causal coding of individual sequences and the Lempel-Ziv dif...

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IEEE International Symposium on Information Theory

作者： T. Linder R. Zamir Department of Mathematics & Statistics Queen's University Kingston ONT Canada Department of EE-Systems Tel-Aviv University Tel-Aviv Israel

In causal source coding, the reconstruction is restricted to be a function of the present and past source samples, while the variable-length code stream may be noncausal. Neuhoff and Gilbert [1982] showed that for memoryless sources, optimum performance among all causal lossy source codes is achieved by time-sharing at most two memoryless codes (scalar quantizers) followed by entropy coding. We extend this result to causal coding of individual sequences in the limit of small distortion. The optimum performance of finite-memory variable-rate causal codes in this setting is characterized by a deterministic analogue of differential entropy, which we call "Lempel-Ziv differential entropy." As a by-product, we also provide an individual-sequence version of the Shannon lower bound to the rate-distortion function.

关键词： Mathematics Statistics Source coding Performance loss Time sharing computer systems entropy coding Rate-distortion Councils

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Multiresolution source coding using entropy constrained dithered scalar quantization

Multiresolution source coding using entropy constrained dith...

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Data Compression Conference (DCC)

作者： Q. Zhao H. Feng M. Effros Oracle Corporation Redwood CA USA Department of Electrical Engineering University of Stanford Stanford CA USA Department of Electrical Engineering (MC 136-93) California Institute of Technology Pasadena CA USA

In this paper, we build multiresolution source codes using entropy constrained dithered scalar quantizers. We demonstrate that for n-dimensional random vectors, dithering followed by uniform scalar quantization and then by entropy coding achieves performance close to the n-dimensional optimum for a multiresolution source code. Based on this result, we propose a practical code design algorithm and compare its performance with that of the set partitioning in hierarchical trees (SPIHT) algorithm on natural images.

关键词： Source coding Quantization Decoding Partitioning algorithms Rate-distortion entropy coding Algorithm design and analysis Constraint theory Probability density function Mutual information

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Optimal context quantization in lossless compression of image data sequences

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2004年第4期13卷 509-517页

作者： Forchhammer, S Wu, XL Andersen, JD Tech Univ Denmark Res Ctr COM DK-2800 Lyngby Denmark McMaster Univ Dept Elect & Comp Engn Hamilton ON L8G 4M2 Canada

In image compression context-based entropy coding is commonly used. A critical issue to the performance of context-based image coding is how to resolve the conflict of a desire for large templates to model high-order statistic dependency of the pixels and the problem of context dilution due to insufficient sample statistics of a given input image. We consider the problem of finding the optimal quantizer Q that quantizes the K-dimensional causal context C-t = (Xt-t1, Xt-t2,..., Xt-tk) of a source symbol X-t into one of a set of conditioning states. The optimality of context quantization is defined to be the minimum static or minimum adaptive code length of given a data set. For a binary source alphabet an optimal context quantizer can be computed exactly by a fast dynamic programming algorithm. Faster approximation solutions are also proposed. In case of m-ary source alphabet a random variable can be decomposed into a sequence of binary decisions, each of which is coded using optimal context quantization designed for the corresponding binary random variable. This optimized coding scheme is applied to digital maps and a-plane sequences. The proposed optimal context quantization technique can also be used to establish a lower bound on the achievable code length, and hence is a useful tool to evaluate the performance of existing heuristic context quantizers.

关键词： adaptive code length context modeling context quantization dynamic programming entropy coding

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Context modeling based on context quantization with application in wavelet image coding

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IEEE TRANSACTIONS ON IMAGE PROCESSING 2004年第1期13卷 26-32页

作者： Chen, JH Yunnan Univ Dept Elect Engn Kunming 650091 Peoples R China

Context modeling is widely used in image coding to improve the compression performance. However, with no special treatment, the expected compression gain will be cancelled by the model cost introduced by high order context models. Context quantization is an efficient method to deal with this problem. In this paper, we analyze the general context quantization problem in detail and show that context quantization is similar to a common vector quantization problem. If a suitable distortion measure is defined, the optimal context quantizer can be designed by a Lloyd style iterative algorithm. This context quantization strategy is applied to an embedded wavelet coding scheme in which the significance map symbols and sign symbols are directly coded by arithmetic coding with context models designed by the proposed quantization algorithm. Good coding performance is achieved.

关键词： context modeling entropy coding image coding quantization wavelet

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Efficient, low-complexity image coding with a set-partitioning embedded block coder

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 2004年第11期14卷 1219-1235页

作者： Pearlman, WA Islam, A Nagaraj, N Said, A Rensselaer Polytech Inst Dept Elect Comp & Syst Engn Troy NY 12180 USA Nokia Inc Irvington TX 75039 USA GE John F Welch Technol Ctr Bangalore 560066 Karnataka India Hewlett Packard Labs Palo Alto CA 94304 USA

We propose an embedded, block-based, image wavelet transform coding algorithm of low complexity. It uses a recursive set-partitioning procedure to sort subsets of wavelet coefficients by maximum magnitude with respect to thresholds that are integer powers of two. It exploits two fundamental characteristics of an image transform-the well-defined hierarchical structure, and energy clustering in frequency and in space. The two partition strategies allow for versatile and efficient coding of several image transform structures, including dyadic, blocks inside subbands, wavelet packets, and discrete cosine transform (DCT). We describe the use of this coding algorithm in several implementations, including reversible (lossless) coding and its adaptation for color images, and show extensive comparisons with other state-of-the-art coders, such as set partitioning in hierarchical trees (SPIHT) and JPEG2000. We conclude that this algorithm, in addition to being very flexible, retains all the desirable features of these algorithms and is highly competitive to them in compression efficiency.

关键词： color image coding embedded coding entropy coding hierarchical coding image coding lossless coding wavelet coding

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