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Binary decompositions for high-order entropy coding of grayscale images

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY 1996年第1期6卷 21-31页

作者： Yu, SS Galatsanos, NP IIT CHICAGO IL 60616 USA

High-order entropy coding (HOEC) has the potential to provide higher compression ratios than the usually used zero-order entropy coding (ZOEC) approaches. However, serious implementation difficulties severely limit the practical value of HOEC for grayscale image compression. We examine the bit-plane decomposition (BPD) representation as a simple alternative that bypasses some of the implementation difficulties of HOEC. We show, however, that BPD introduces undesired coding overhead when used to represent grayscale images. We therefore propose a new binary image representation called magnitude-based binary decomposition (MBBD) which avoids any coding overhead when used to represent grayscale images. Thus, MBBD both bypasses the implementation difficulties of HOEC and does not have the drawbacks of the BPD. We present numerical experiments that verify the theoretical analysis of the BPD and MBBD representations. In addition, our experiments demonstrate that MBBD-HOEC yields better results than ZOEC for lossy image compression and is also very effective for progressive image transmission.

关键词： data compression entropy codes higher order statistics image coding image representation binary decompositions binary image representation bit plane decomposition compression ratios grayscale image compression high-order entropy coding lossy image compre compression ratio image representation Image compression Higher order statistics image coding Image communication systems lossy image compression Data compression Borderline Personality Disorder entropy coding lossy compression grayscale images

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Rate-distortion optimization for video compression

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IEEE SIGNAL PROCESSING MAGAZINE 1998年第6期15卷 74-90页

作者： Sullivan, GJ Wiegand, T PictureTel Corp Commun Core Res Andover MA USA Univ Erlangen Nurnberg D-8520 Erlangen Germany

The rate-distortion efficiency of video compression schemes is based on a sophisticated interaction between various motion representation possibilities, waveform coding of differences, and waveform coding of various refreshed regions. Hence, a key problem in high-compression video coding is the operational control of the encoder. This problem is compounded by the widely varying content and motion found in typical video sequences, necessitating the selection between different representation possibilities with varying rate-distortion efficiency. This article addresses the problem of video encoder optimization and discusses its consequences on the compression architecture of the overall coding system. Based on the well-known hybrid video coding structure, Lagrangian optimization techniques are presented that try to answer the question: what part of the video signal should be coded using what method and parameter settings?.

关键词： Rate-distortion Video compression Bit rate Video coding Quantization Switches Motion compensation Video codecs entropy coding ISO

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Wavelet-based image coder with entropy-constrained lattice vector quantizer (ECLVQ)

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 1998年第8期45卷 1015-1030页

作者： Kim, WH Hu, YH Nguyen, TQ Los Alamos Natl Lab Los Alamos NM 87545 USA Univ Wisconsin Dept Elect & Comp Engn Madison WI 53706 USA

This paper presents an algorithm that jointly optimizes a lattice vector quantizer (LVQ) and an entropy coder in a subband coding at all ranges of bit rate. Estimation formulas for both entropy and distortion of lattice quantized subband images are derived. From these estimates, we then develop dynamic algorithm optimizing the LVQ and entropy coder together for a given entropy rate. Compared to previously reported min-max approaches, or approaches using asymptotic distortion bounds, the approach reported here quickly designs a highly accurate optimal entropy-constrained LVQ, The corresponding wavelet-based image coder also has better coding performance compared to other subband coders that use entropy-constrained LVQ, especially at low bit rates.

关键词： entropy coding image coding lattice vector quantization wavelet

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entropy coding of composite sources modeled by infinite Gaussian mixture distributions

Entropy coding of composite sources modeled by infinite Gaus...

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IEEE Digital Signal Processing Workshop

作者： A. Hjorungnes J.M. Lervik T.A. Ramstad Department of Telecommunications Norwegian University of Science and Technology Trondheim Norway

A method for optimizing a multiple entropy coder system for coding of a memoryless mixture distribution is studied. The coding scheme is based on splitting the composite source into a finite number of subsources, followed by entropy coding of each subsource. A rate distortion optimal splitting scheme is found assuming an infinite Gaussian mixture distribution and one common infinite-level uniform threshold quantizer for all samples. Theoretical results quantifying the rate distortion performance for a Gaussian mixture distribution with an exponential mixing density are found for 1 to 5 entropy coders, and compared to the rate distortion function. At a signal-to-noise ratio of 30 dB the average entropy is reduced by 0.270 bits per sample, when using 5 entropy coders compared to coding of the composite source.

关键词： entropy coding Rate-distortion Stochastic processes Statistical distributions Optimization methods Signal to noise ratio Frequency domain analysis Quantization Probability density function Filling

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Fitting coding scheme for image wavelet representation

Fitting coding scheme for image wavelet representation

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Conference on Multimedia Storage and Archiving Systems III

作者： Przelaskowski, A Warsaw Univ Technol Inst Radioelect PL-00665 Warsaw Poland

ISBN: (纸本)0819429880

Efficient coding scheme for image wavelet representation in lossy compression scheme is presented. Spatial-frequency hierarchical structure of quantized coefficient and their statistics is analyzed to reduce any redundancy. We. applied context-based linear magnitude predictor to fit 1(st) order conditional probability model in arithmetic coding of significant coefficients to local data characteristics and eliminate spatial and inter-scale dependencies. Sign information is also encoded by inter and intra-band prediction and entropy coding of prediction errors. But main feature of our algorithm deals with encoding way of zerotree structures. Additional symbol of zerotree root is included into magnitude data stream. Moreover, four neighbor zerotree roots with significant parent node are included in extended high-order context model of zerotrees. This significant parent is signed as significant zerotree root and information about these roots distribution is coded separately. The efficiency of presented coding scheme was tested in dyadic wavelet decomposition scheme with two quantization procedures. Simple scalar uniform quantizer and more complex: space-frequency quantizer with adaptive data thresholding were used. The final results seem to be promising and competitive across the mast effective wavelet compression methods.

关键词： zerotree context modeling entropy coding wavelet compression

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Joint source channel coding for variable length codes

Joint source channel coding for variable length codes

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Data Compression Conference

作者： Demir, N Sayood, K Univ Nebraska Dept Elect Engn Lincoln NE 68588 USA

ISBN: (纸本)0818684062

When using entropy coding over a noisy channel it is customary to protect the highly vulnerable bitstream with error correcting code. In this paper we propose a technique which utilizes the residual redundancy at the output of the source coder to provide error protection for entropy coded systems. The proposed approach provides 4-10 dB improvement over the standard approaches at a reduced rate.

关键词： variable length codes entropy coding error protection variable length coding noisy channel bit stream ENCODER

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Image compression improvement by pre-filtering

Image compression improvement by pre-filtering

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Conference on Applications of Digital Image Processing XXI

作者： Hadar, O Stern, A Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

ISBN: (纸本)0819429155

An algorithm to improve the image compression ratio, by applying low-pass filtering before the compression process is presented. Pre-filtering images prior to encoding can remove high frequencies of the original image, and thus improve the overall performance of the coder. The image degradation caused by the filter combined with the non-linear transformation of a typical compression algorithm reduce the entropy of the original image, thus higher compression ratios can be achieved. The perceived image at the decoder side is reconstructed according to a priory knowledge of the degraded filter by applying decompression and inverse filtering. The results of this work show an improvement of the compression ratio compare to the original Joint Picture Experts Group (JPEG) algorithm, with only small reduction of Mean Square Error (MSE). Our algorithm also succeeds to reduce the blocking effect that exists in the original JPEG algorithm.

关键词： image compression entropy coding image filtering image restoration

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Combination coding: a new entropy coding technique

Combination coding: a new entropy coding technique

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Data Compression Conference (DCC)

作者： R. Fawcett Robotics Research Group Department of Engineering Science University of Oxford Oxford UK

Summary form only given. entropy coding is defined to be the compression of a stream of symbols taken from a known symbol set where the probability of occurrence of any symbol from the set at any given point in the stream is constant and independent of any known occurrences of any other symbols. Shannon and Fano showed that the information of such a sequence could be calculated. When measured in bits the information represents the optimum compressed length of the original sequence. If information about sequential redundancy is known better compression may be possible by one of the substitution coding techniques of Ziv and Lempel. In the absence of any such information, entropy coding provides an optimum coding strategy. Huffman posed an optimal variable word length coding technique. Many years later the arithmetic coding technique was formulated by IBM which provided compression close to the optimum. Combination coding is as efficient as arithmetic coding and is very fast as it only requires basic integer operations for both the compression and decompression stages. The technique is in fact for the entropy coding of a binary sequence but by the use of a binary tree, the entropy coding of a sequence of any number of symbols can be reduced to the entropy coding of a number of binary sequences.

关键词： entropy coding Binary sequences Arithmetic Robots Length measurement Binary trees Binary codes Huffman coding Table lookup

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Memory-constrained high-order entropy coding by Huffman table sharing and memory allocation

Memory-constrained high-order entropy coding by Huffman tabl...

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IEEE Asia-Pacific Conference on Circuits and Systems

作者： Seung Jun Lee Jun Seok Song Choong Woong Lee Department of Electronics Engineering Seoul National University Seoul South Korea

ISBN: (纸本)0780337026

For memory constrained high-order entropy coding, (i) the number of Huffman tables and (ii) the size of each Huffman table have to be appropriately reduced. Recently, we developed a Huffman table sharing and a memory allocation methods, each of which efficiently reduces either (i) or (ii) to meet the given memory constraint while keeping the increase in average bitrate as small as possible. However, given a memory constraint, the Huffman table sharing and the memory allocation methods have to be employed at the same time to achieve the better result. This paper presents several efficient schemes for combining the two methods along with simulation results.

关键词： entropy coding Bit rate Encoding Huffman coding Decoding Performance evaluation Vector quantization Samarium Statistics Iterative methods

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Bitplane coding of DCT coefficients for image and video compression

Bitplane coding of DCT coefficients for image and video comp...

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Meeting on Visual Communications and Image Processing

作者： Ling, F Li, WP Sun, HQ Gen Instrument San Diego CA 92121 USA

ISBN: (纸本)0819431249

In the current image and video coding standards, such as MPEG-1, MPEG-2, MPEG-4, H.261, H.263, and JPEG, quantized DCT coefficients are entropy coded using a so-called run-value coding technique. A. problem with this technique is that the statistics of the run-value symbols are highly dependent on the quantization step size and the dynamic range of the DCT coefficients. Therefore, a single fixed entropy coding table cannot achieve the optimal coding efficiency for all possible quantization step sizes and all possible dynamic ranges of the DCT coefficients. Bitplane coding of the DCT coefficients is a new coding scheme that overcomes this problem. It provides a better performance than run-value coding under all conditions.

关键词： image and video compression quantization entropy coding run_value coding bitplane coding

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