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A secure and efficient entropy coding based on arithmetic coding

COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2009年第12期14卷 4304-4318页

作者： Li, Hengjian Zhang, Jiashu SW Jiaotong Univ Sichuan Prov Key Lab Signal & Informat Proc Chengdu 610031 Sichuan Peoples R China

A novel security arithmetic coding scheme based on nonlinear dynamic filter (NDF) with changeable coefficients is proposed in this paper. The NDF is employed to generate the pseudorandom number generator (NDF-PRNG) and its coefficients are derived from the plaintext for higher security. During the encryption process, the mapping interval in each iteration of arithmetic coding (AC) is decided by both the plaintext and the initial values of NDF, and the data compression is also achieved with entropy optimality simultaneously. And this modification of arithmetic coding methodology which also provides security is easy to be expanded into the most international image and video standards as the last entropy coding stage without changing the existing framework. Theoretic analysis and numerical simulations both on static and adaptive model show that the proposed encryption algorithm satisfies highly security without loss of compression efficiency respect to a standard AC or computation burden. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Data security Entropy coding Chaos arithmetic coding Nonlinear dynamic filter

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A configurable statistical lossless compression core based on variable order Markov modeling and arithmetic coding

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IEEE TRANSACTIONS ON COMPUTERS 2005年第11期54卷 1345-1359页

作者： Nunez-Yanez, JL Chouliaras, VA Univ Bristol Dept Elect & Elect Engn Bristol BS8 1UB Avon England Univ Loughborough Dept Elect & Elect Engn Loughborough LE11 1TU Leics England

This paper presents a practical realization in hardware of the concepts of variable order Markov modeling using multisymbol alphabets and arithmetic coding for lossless compression of universal data. This type of statistical coding algorithm has long been regarded as being able to deliver very high compression ratios close to the information content of the source data. However, their high computational complexity has limited their practical application in embedded environments such as in mobile computing and wireless communications. In this paper, a hardware amenable algorithm named PPMH and based on these principles has been developed and its architecture and implementation detailed. This novel lossless compression core offers innovative solutions to the computational issues in both stages of modeling and coding and delivers high compression efficiency and throughput. The configurability features of the core allow efficient use of the embedded SRAM present in modern FPGA technologies where memory resources range from a few kilobits to several megabits per device family. The core has been targeted to the Altera Stratix FPGA family and performance, coding efficiency, and complexity measured for different memory configurations.

关键词： Markov modeling statistical compression lossless compression arithmetic coding

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Application of arithmetic coding to compression of VLSI test data

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IEEE TRANSACTIONS ON COMPUTERS 2005年第9期54卷 1166-1177页

作者： Hashempour, H Lombardi, F LTX Corp IC Dev & Appl Res San Jose CA 95134 USA Northeastern Univ Dept Elect & Comp Engn Boston MA 02115 USA

This paper proposes arithmetic coding for application to data compression for VLSI testing. The use of arithmetic codes results in a codeword whose length is close to the optimal value (as predicted by entropy in information theory), thus achieving a higher compression. Previous techniques (such as those based on Huffman or Golomb coding) result in optimal codes for data sets in which the probability model of the symbols satisfies specific requirements. This paper shows empirically and analytically that Huffman and Golomb codes can result in a large difference between the bound established by the entropy and the attained compression;therefore, the worst-case difference is studied using information theory. Compression results for arithmetic coding are presented using ISCAS benchmark circuits;a practical integer implementation of arithmetic coding/decoding and an analysis of its deviation from the entropy bound are pursued. A software implementation is proposed using embedded DSP cores. In the experimental evaluation, fully specified test vectors and test cubes from two different ATPG programs are utilized. The implications of arithmetic coding on manufacturing test using an ATE are also investigated.

关键词： test data compression Golomb coding Huffman coding arithmetic coding SoC ATE

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arithmetic coding of speech and audio spectra using tcx based on linear predictive spectral envelopes 40

Arithmetic coding of speech and audio spectra using tcx base...

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Backstrom, Tom Helmrich, Christian R. Erlangen Germany

ISBN: (纸本)9781467369978

Unified speech and audio codecs often use a frequency domain coding technique of the transform coded excitation (TCX) type. It is based on modeling the speech source with a linear predictor, spectral weighting by a perceptual model and entropy coding of the frequency components. While previous approaches have used neighbouring frequency components to form a probability model for the entropy coder of spectral components, we propose to use the magnitude of the linear predictor to estimate the variance of spectral components. Since the linear predictor is transmitted in any case, this method does not require any additional side info. Subjective measurements show that the proposed methods give a statistically significant improvement in perceptual quality when the bit-rate is held constant. Consequently, the proposed method has been adopted to the 3GPP Enhanced Voice Services speech coding standard. © 2015 IEEE.

关键词： arithmetic coding frequency domain coding speech and audio coding

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A new arithmetic coding model for a block-based lossless image compression based on exploiting inter-block correlation

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SIGNAL IMAGE AND VIDEO PROCESSING 2015年第5期9卷 1021-1027页

作者： Masmoudi, Atef Masmoudi, Afif Univ Sfax Sfax Preparatory Engn Inst Sfax Tunisia Univ Sfax Fac Sci Sfax Lab Stat & Probabil Sfax Tunisia

In this paper, we investigate a new approach for a block-based lossless image compression using arithmetic coding. The conventional arithmetic encoders encode and decode images pixel by pixel in raster scan order by using a statistical model which provides probabilities for the whole source symbols to be encoded. However, in the proposed scheme, the arithmetic encoders encode an image block by block from left to right, and block-row by block-row from top to bottom. The proposed model estimates the probability distribution of each block by exploiting the high correlation between neighboring image blocks. Therefore, the probability distribution of each block of pixels is estimated by minimizing the Kullback-Leibler distance between the exact probability distribution of that block and the probability distributions of its neighboring blocks in causal order. The results of comparative experiments show significant improvements over conventional arithmetic encoders in both static and adaptive order-0 models, reducing the bitrate by an average of 15.5 and 16.4 % respectively.

关键词： arithmetic coding Lossless compression Kullback-Leibler distance

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Reversible Natural Language Watermarking Using Synonym Substitution and arithmetic coding

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Computers, Materials & Continua 2018年第6期55卷 541-559页

作者： Lingyun Xiang Yan Li Wei Hao Peng Yang Xiaobo Shen Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha 410114HunanChina School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha 410114HunanChina School of Traffic&Transportation Engineering Changsha University of Science&TechnologyChangsha 410114HunanChina Hunan Branch of CNCERT/CC Changsha 410004HunanChina School of Computer Science and Engineering Nanyang Technological University639798Singapore

For protecting the copyright of a text and recovering its original content harmlessly,this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution *** analyzing relative frequencies of synonymous words,synonyms employed for carrying payload are quantized into an unbalanced and redundant binary *** quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional ***,the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible *** the receiver side,the watermark and compressed data can be extracted by decoding the values of synonyms in the watermarked text,as a result of which the original context can be perfectly recovered by decompressing the extracted compressed data and substituting the replaced synonyms with their original *** results demonstrate that the proposed method can extract the watermark successfully and achieve a lossless recovery of the original ***,it achieves a high embedding capacity.

关键词： arithmetic coding synonym substitution lossless compression reversible watermarking.

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Secure image compression approach based on fusion of 3D chaotic maps and arithmetic coding

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IET SIGNAL PROCESSING 2019年第3期13卷 286-295页

作者： Darwish, Saad Mohamed Noori, Zainab H. Alexandria Univ Dept Informat Technol Inst Grad Studies & Res 163 Horreya AveEl Shatby 21526POB 832 Alexandria Egypt Univ Babylon Dept Comp Sci Hillah Iraq

Advances in digital image processing and communications have created a great demand for real-time secure image transmission over the networks. However, the development of effective, fast and secure dependent image compression-encryption systems are still a research problem as the intrinsic features of images. A new approach is suggested in this study for partial image encryption-compression that adopts chaotic three-dimensional (3D) cat map to de-correlate relations among pixels in conjunction with an adaptive thresholding technique that is utilised as a lossy compression technique instead of using complex quantisation techniques and also as a substitution technique to increase the security of the cipher image. The proposed scheme is based on employing both of lossless compression with encryption on the most significant part of the image after contourlet transform. However, the least significant parts are lossy compressed by employing a simple thresholding rule and arithmetic coding to render the image totally unrecognisable. Due to the weakness of 3D cat map to chosen plain text attack, the suggested scheme incorporates a mechanism to generate random key depending on the contents of the image (context key). Several experiments were done on benchmark images to insure the validity of the proposed technique.

关键词： image processing cryptography image coding data compression 3D chaotic maps arithmetic coding digital image processing communications great demand real-time secure image transmission dependent image compression-encryption systems bulk data capacity high correlation pixels traditional joint encryption-compression methods partial image encryption-compression three-dimensional cat map de-correlate relations adaptive thresholding technique lossy compression technique complex quantisation techniques substitution technique cipher image lossless compression significant part 3D cat map benchmark images compression analysis suggested technique real-time image secure image compression approach

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A secure arithmetic coding based on Markov model

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2011年第6期16卷 2554-2562页

作者： Duan, Lili Liao, Xiaofeng Xiang, Tao Chongqing Univ State Key Lab Power Transmiss Equipment & Syst Se Coll Comp Sci Chongqing 400044 Peoples R China

We propose a modification of the standard arithmetic coding that can be applied to multimedia coding standards at entropy coding stage. In particular, we introduce a randomized arithmetic coding scheme based on order-1 Markov model that achieves encryption by scrambling the symbols' order in the model and choosing the relevant order's probability randomly, which is done with higher compression efficiency and good security. Experimental results and security analyses indicate that the algorithm can not only resist to existing attacks based on arithmetic coding, but also be immune to other cryptanalysis. (C) 2010 Elsevier B.V. All rights reserved.

关键词： arithmetic coding Markov model Image encryption

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Embedding channel coding in arithmetic coding

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IEE PROCEEDINGS-COMMUNICATIONS 1999年第2期146卷 73-78页

作者： Elmasry, GF New Jersey Inst Technol Dept Elect & Comp Engn New Jersey Ctr Multimedia Res Newark NJ 07102 USA

An arithmetic coding algorithm that incorporates channel coding is presented. For a source alphabet with m symbols, the selected Mt code points over the [0-1) interval have a desired minimum Hamming distance d(min) between them. The decoder utilises this d(min) in conjunction with the self-synchronisation property of arithmetic coding and knowledge of the source statistics to recover the original sequence of symbols, in the presence of channel errors, without the use of known channel coding techniques. The selected d(min) provides a desired error protection level. The introduced scheme is suitable for bandwidth-limited binary symmetric channels (BSCs) with moderate to high error rates.

关键词： decoder channel coding arithmetic codes source alphabet self-synchronisation property bandwidth-limited binary symmetric channels minimum Hamming distance Codes error correction codes error statistics arithmetic coding error protection decoding

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Highly Scalable Parallel arithmetic coding on Multi-Core Processors Using LDPC Codes

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IEEE TRANSACTIONS ON COMMUNICATIONS 2012年第2期60卷 289-294页

作者： Hu, Weidong Wen, Jiangtao Wu, Weiyi Han, Yuxing Yang, Shiqiang Villasenor, John Tsinghua Univ Dept Comp Sci & Technol Beijing 10084 Peoples R China Univ Calif Los Angeles Dept Elect Engn Los Angeles CA 90095 USA

We describe a highly scalable parallel arithmetic coder for Markov inputs suitable for implementation on modern multi-core processors. The algorithm divides the input into interleaved sub-sequences which can be then processed independently on different processing units using LDPC-based Slepian-Wolf coding. Experimental simulations show good scalability of the proposed algorithm while also maintaining good compression performance. Notably, when compared with traditional parallel arithmetic coding, the proposed method maintains a much higher efficiency both respect to the entropy limit as well as in terms of the ability to distribute computations across multiple cores without performance loss.

关键词： arithmetic coding Slepian-Wolf coding multi-core architecture

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