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4th Conference on Mathematics of Image and Data coding, Compression, and Encryption

作者： Ishibashi, H Tanaka, K Shinshu Univ Fac Engn Nagano 3808553 Japan

ISBN: (纸本)0819441899

In this work, we extend arithmetic coding and present a data encryption scheme that achieves data compression and data security at the same time. This scheme is based on a chaotic dynamics, which makes use of the fact that the decoding process of arithmetic coding scheme can be considered as the repetition of Bernoulli shift map. Data encryption is achieved by controlling the piecewise linear maps by a secret key in three kinds of approach: (i) perturbation method, (ii) switching method, and (iii) source extension method. Experimental results show that the obtained arithmetic codes for a message are randomly distributed on the mapping domain [0,1) by using different keys without seriously deteriorating the compression ratio, and the transition of the orbits in the domain [0,1) is similar to the chaotic dynamics.

关键词： arithmetic coding data encryption data compression chaotic dynamical system pieceivise linear map

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Universal lossless data compression with side information by using a conditional MPM grammar transform

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IEEE TRANSACTIONS ON INFORMATION THEORY 2001年第6期47卷 2130-2150页

作者： Yang, EH Kaltchenko, A Kieffer, JC Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA

A grammar transform is a transformation that converts any data sequence to be compressed into a grammar from which the original data sequence can be fully reconstructed. In a grammar-based code, a data sequence is first converted into a grammar by a grammar transform and then losslessly encoded. Among several recently proposed grammar transforms is the multilevel pattern matching (MPM) grammar transform. In this paper, the MPM grammar transform is first extended to the case of side information known to both the encoder and decoder, yielding a conditional MPM (CMPM) grammar transform. A new simple linear-time and space complexity algorithm is then proposed to implement the MPM and CMPM grammar transforms. Based on the CMPM grammar transform, a universal lossless data compression algorithm with side information is developed, which can achieve asymptotically the conditional entropy rate of any stationary, ergodic source pair. It is shown that the algorithm's worst case redundancy/sample against the k-context conditional empirical entropy among all individual sequences of length n is upper-bounded by c (1/ log n), where c is a constant. The proposed algorithm with side information is the first in the coming family of conditional grammar-based codes, whose expected high efficiency is due to the efficiency of the corresponding unconditional codes.

关键词： arithmetic coding coding with side information entropy grammar-based source codes multilevel pattern matching (MPM) redundancy string matching universal data compression

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A rapid probability estimator and binary arithmetic coder

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IEEE TRANSACTIONS ON INFORMATION THEORY 2001年第4期47卷 1533-1537页

作者： Withers, WD USN Acad Dept Math Annapolis MD 21402 USA Pegasus Imaging Corp Imagetech Tampa FL 33607 USA

We present a new integrated algorithm fur binary arithmetic coding and probability estimation, competitive in speed and compression performance with state-of-the-art algorithms such as the QM-coder and Z-coder. The chief innovation is representing the bracketing interval width both directly and by a logarithmic approximation. Performance is evaluated by experiments using bilevel-image data sets. An open-source software version is available.

关键词： algorithms arithmetic coding data compression entropy coding

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Lossy compression of grayscale document images by adaptive-offset quantization

Lossy compression of grayscale document images by adaptive-o...

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8th Annual Document Recognition and Retrieval Conference

作者： Popat, K Xerox Palo Alto Res Ctr Palo Alto CA 94304 USA

ISBN: (纸本)0819439851

This paper describes an adaptive-offset quantization scheme and considers its application to the lossy compression of grayscale document images. The technique involves scalar-quantizing and entropy-coding pixels sequentially, such that the quantizer's offset is always chosen to minimize the expected number of bits emitted for each pixel, where the expectation is based on the predictive distribution used for entropy coding. To accomplish this, information is fed back from the entropy coder's statistical modeling unit to the quantizer. This feedback path is absent in traditional compression schemes. Encouraging but preliminary experimental results are presented comparing the technique with JPEG and with fixed-offset quantization on a scanned grayscale text image.

关键词： document image compression quantization entropy coding arithmetic coding

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An adaptable binary entropy coder

An adaptable binary entropy coder

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Data Compression Conference (DCC 2001)

作者： Kiely, A Klimesh, M CALTECH Jet Prop Lab Pasadena CA 91109 USA

ISBN: (纸本)0769510310

We present a novel entropy coding technique which is based on recursive interleaving of variable-to-variable length binary source codes. The encoding is adaptable in that each bit to be encoded may have an associated probability estimate which depends on previously encoded bits. The technique may have advantages over arithmetic coding. The technique can achieve arbitrarily small redundancy, and admits a simple and fast decoder. We discuss code design and performance estimation methods, as well as practical encoding and decoding algorithms.

关键词： Binary entropy coding ENCODER Statistical analysis decoding algorithm Source code Entropy coding arithmetic coding Performance Evaluation

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Group Testing for Wavelet Packet image compression

Group Testing for Wavelet Packet image compression

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Data Compression Conference (DCC 2001)

作者： Hong, ES Ladner, RE Riskin, EA Univ Washington Dept Comp Sci & Engn Seattle WA 98195 USA

ISBN: (纸本)0769510310

This paper introduces Group Testing for Wavelet Packets (GTWP), a novel embedded image compression algorithm based on wavelet packets and group testing. This algorithm extends the Group Testing for Wavelets (GTW) algorithm [7] to handle wavelet packets. Like its predecessor, GTWP obtains good compression performance without the use of arithmetic coding. It also shows that the group testing methodology is very flexible and can be applied in many different circumstances.

关键词： Group Testing Wavelet packets image compression algorithm arithmetic coding Image compression Data compression

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arithmetic coding revisited

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ACM TRANSACTIONS ON INFORMATION SYSTEMS 1998年第3期16卷 256-294页

作者： Moffat, A Neal, RM Witten, IH Univ Melbourne Dept Comp Sci Parkville Vic 3052 Australia Univ Toronto Dept Comp Sci Toronto ON Canada Univ Toronto Dept Stat Toronto ON Canada Univ Waikato Dept Comp Sci Hamilton New Zealand

Over the fast decade, arithmetic coding has emerged as an important compression tool. It is now the method of choice for adaptive coding on multisymbol alphabets because of its speed, low storage requirements, and effectiveness of compression. This article describes a new implementation of arithmetic coding that incorporates several improvements over a widely used earlier version by Witten, Neal, and Cleary, which has become a de facto standard. These improvements include fewer multiplicative operations, greatly extended range of alphabet sizes and symbol probabilities, and the use of low-precision arithmetic, permitting implementation by fast shift/add operations. We also describe a modular structure that separates the coding, modeling, and probability estimation components of a compression system. To motivate the improved coder, we consider the needs of a word-based text compression program. We report a range of experimental results using this and other models. Complete source code is available.

关键词： algorithms performance approximate coding arithmetic coding text compression word-based model

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A VLSI architecture for arithmetic coding of multilevel images

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING 1998年第1期45卷 163-168页

作者： Boo, M Bruguera, JD Lang, T Univ Calif Irvine Dept Elect & Comp Engn Irvine CA 92664 USA

We describe a VLSI architecture of an arithmetic coder for a multilevel alphabet (256 symbols) that includes the storing and updating of probabilities, the updating of the interval, and the correction of the codeword, The architecture is based on the utilization of redundant arithmetic, and the development of new schemes for storing and updating the cumulative probabilities and updating the range and left point of the current interval. The proposed implementation is compared with one that does not include these improvements, and is shown to result in a significantly lower complexity and shorter cycle.

关键词： arithmetic coding redundant representation VLSI architecture

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Compression of sparse matrices by arithmetic coding

Compression of sparse matrices by arithmetic coding

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Data Compression Conference

作者： Bell, T McKenzie, B Univ Canterbury Dept Comp Sci Christchurch 1 New Zealand

ISBN: (纸本)0818684062

The compression of matrices where the majority of the entries are a fixed constant (most typically zero), usually referred to as sparse matrices, has received much attention. We evaluate the performance of existing methods, and consider how arithmetic coding can be applied to the problem to achieve better compression. The result is a method that gives better compression than existing methods, and still allows constant-time access to individual elements if required. Although for concreteness we express our method in terms of two-dimensional matrices where the majority of the values are zero, it is equally applicable to matrices of any number of dimensions and where the fixed known constant is any value. We assume that the number of dimensions and their ranges are known, but will not assume that any information is available externally regarding the number of non-zero entries.

关键词： arithmetic coding Sparse matrix compression entry dimensions Zero

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Piecewise integer mapping for arithmetic coding

Piecewise integer mapping for arithmetic coding

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Data Compression Conference

作者： Stuiver, L Moffat, A Univ Melbourne Dept Comp Sci Parkville Vic 3052 Australia

ISBN: (纸本)0818684062

By asking afresh exactly what it is the arithmetic coder must do, we show how much of the complexity of current coders can be dispensed with. In particular, we eliminate all multiplicative operations in both the encoder and decoder, replacing them by comparisons and additions. The essence of the proposal is a simple piecewise integer mapping. Graf (1997) has made use of a similar integer mapping in his proposal for a fast entropy coder. Our work is related to but independent of his. As in all non-exact coders, some inefficiency is introduced. We give an analysis that shows the average loss caused by the revised coder to be bounded in an expected sense by 0.0861 bits per symbol, which for most compression applications is just one or two percent. As an additional modification, we discuss a mechanism that allows multi-bit output of codewords without compromising the precision of the probability estimates that may be employed. Finally, we give performance results that show that in combination the two improvements yield a coder as much as 40% faster than previous benchmark arithmetic coders.

关键词： arithmetic coding Integer Piecewise Essences

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