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AN ADAPTIVE DEPENDENCY SOURCE MODEL FOR DATA-COMPRESSION

COMMUNICATIONS OF THE ACM 1989年第1期32卷 77-83页

作者： ABRAHAMSON, DM Trinity College Dublin Ireland

The adaptive dependency source model, as described in this article, provides a simple way to benefit from the interdependency between the successive characters in a text. For most files, when compared with either the adaptive arithmetic coding model by Witten et al., or Gallager's adaptive Huffman encoding model, the adaptive dependency model produces a 12 to 15 percent increase in compression efficiency. [ABSTRACT FROM AUTHOR]

关键词： Adaptive dependency adaptive modeling arithmetic coding Huffman coding

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M-ABRC (Adaptive Binary Range Coder) using Virtual Sliding Window technique and its VLSI implementation

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MICROPROCESSORS AND MICROSYSTEMS 2019年 71卷 102901-000页

作者： Mrudula, S. T. Murthy, K. E. Srinivasa Prasad, M. N. Giri JNTUA Dept ECE Ananthapuramu AP India G Pullaiah Coll Engn & Technol Dept ECE Kurnool AP India

arithmetic coding is the data compression techniques, which encodes the data by generating the code string that represents a functional value between 0 and 1. In this paper, we propose a modified-Adaptive Binary-RC (Range Coder) or M-ABRC. Our algorithm minimizes the multiplication bit capacity through introducing the VLSI architecture, proposed algorithm uses the LUP (Look UP Table)-VSW (Virtual Sliding Window) for the probability estimation. In order to achieve the higher compression rate, our method M-ABRC has been implemented, this in terms provides the better adoption probability in encoding phase and also gives the absolute estimation of low-EBS(entropy binary sources). Moreover In order to evaluate the algorithm we have compared with the several existing technique, comparison takes place based on the two parameter i.e. device utilization and the power dissipation (static and dynamic). (C) 2019 Elsevier B.V. All rights reserved.

关键词： arithmetic coding M-ABRC VSW VLSI

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Compression Of Gray Scale Images Using Alphabet Reduction Models

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International Journal of Modelling and Simulation 1995年第3期15卷 107-112页

作者： Mu-King Tsay Chia-Hsu Kuo Cheng-Chang Lu Ming-Ko Chiu Institute of Computer Science and Electronic Engineering National Central University Chung-Li Taiwan ROC Email: cs7933@mbox.ee.ncu.edu.tw Institute of Computer Science and Electronic Engineering National Central University Chung-Li Taiwan ROC Email: cs7933@mbox.ee.ncu.edu.tw Department of Mathematics and Computer Science Kent State University P.O. Box 5190 Kent OH 44242-0001 USA Email: lucc@mcs.kent.edu Institute of Computer Science and Electronic Engineering National Central University Chung-Li Taiwan ROC Email: cs7933@mbox.ee.ncu.edu.tw

In this paper, the problems arising in modelling digital gray-level images for noiseless compression are discussed. An alphabet reduction model for compressing gray-level images using arithmetic coding is proposed. The byte image source is divided into eight bitplanes. For each bitplane, a finite state macliine model is generated. The results are compared to traditional compression methods. The proposed algorithm improves the coding efficiency with lower complexity

关键词： Alphabet reduction arithmetic coding Data compression

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Two pass improved encoding and its parallel processing for fractal image compression

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JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY 2007年第3期1卷 381-407页

作者： Ong, Ghim-Hwee Ching, Kin-Wah Eugene Natl Univ Singapore Sch Comp Singapore Singapore

An improvement scheme, so named the Two-Pass Improved Encoding Scheme (TIES), for the application to image compression through the extension of the existing concept of fractal image compression (FIC), which capitalizes on the self-similarity within a given image which is to be compressed, is proposed in this paper. This paper first briefly explores the existing image compression technology based on FIC, before exploring the areas which can be improved and hence establishing the concept behind the TIES algorithm. An effective encoding and decoding algorithm for the implementation of TIES is developed, through the consideration of the domain pool, block scaling and transformation, range block approximation using linear combinations and arithmetic encoding for storing data as close to source entropy as possible. The performance of TIES is then explicitly compared against that of FIC under the same conditions. Finally, due to the long encoding time required by TIES, this paper then proceeds to propose parallelized versions of the two TIES algorithms, before finally concluding with an empirical analysis of the speedup and scalability of the parallelized TIES algorithms, as well as compare the effect of parallelization between the two.

关键词： Fractal image compression quad-tree partitioning peak signal-to-noise ratio arithmetic coding linear combination

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Contribution to S-EMG Signal Compression in 1D by the Combination of the Modified Discrete Wavelet Packet Transform (MDWPT) and the Discrete Cosine Transform (DCT)

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Journal of Signal and Information Processing 2020年第3期11卷 35-57页

作者： Colince Welba Aimé Joseph Oyobé Okassa Pascal Ntsama Eloundou Pierre Ele Department of Fundamental Science Faculty of Mines and Petroleum Industries University of Maroua Maroua Cameroon School of Engineering of Masuku Franceville Gabon Physics Department Faculty of Sciences University of Ngaoundere Ngaoundere Cameroon Electrical Engineering and Telecommunications Department National Advanced School of EngineeringUniversity of Yaounde 1 Ya-oundé Cameroon

A new Modified Discrete Wavelets Packets Transform (MDWPT) based method for the compression of Surface EMG signal (s-EMG) data is presented. A Modified Discrete Wavelets Packets Transform (MDWPT) is applied to the digitized s-EMG signal. A Discrete Cosine Transforms (DCT) is applied to the MDWPT coefficients (only on detail coefficients). The MDWPT+ DCT coefficients are quantized with a Uniform Scalar Dead-Zone Quantizer (USDZQ). An arithmetic coder is employed for the entropy coding of symbol streams. The proposed approach was tested on more than 35 actuals S-EMG signals divided into three categories. The proposed approach was evaluated by the following parameters: Compression Factor (CF), Signal to Noise Ratio (SNR), Percent Root mean square Difference (PRD), Mean Frequency Distortion (MFD) and the Mean Square Error (MSE). Simulation results show that the proposed coding algorithm outperforms some recently developed s-EMG compression algorithms.

关键词： S-EMG Compression MDWPT DCT arithmetic coding Uniform Scalar Dead-Zone Quantizer (USDZQ)

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A Study of Joint Lossless Compression and Encryption Scheme

A Study of Joint Lossless Compression and Encryption Scheme

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IEEE International Conference on Circuit ,Power and Computing Technologies (ICCPCT)

作者： Raju, Jini TKM Coll Engn Dept CSE Kollam India

ISBN: (纸本)9781509049677

Data compression and encryption are the two fundamental steps needed for the secure transmission of large amount of data. Compression is needed because of the limitations in storage capacity and bandwidth requirements. In normal cases, the compressed data is encrypted and transmitted. But, this sequential approach is time consuming and computationally expensive. In this paper, a study on simultaneous compression and encryption scheme, based on the compression ratio and time, is done for different sized input sets. In simultaneous scheme, compression and encryption can be done at single step which reduces time for the entire operation. Compression is done using arithmetic coding and encryption is done using XOR encryption. The XOR encryption introduces some randomness because of the presence of pseudorandom number generator. Thus the scheme is more secure against attacks. Also, the integrity of the seed value from the random number generator is also preserved using the DSA algorithm.

关键词： compression pseudorandom number arithmetic coding XOR encryption

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Quantitative Comparative Study of the Performance of Lossless Compression Methods Based on a Text Data Model

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Open Journal of Applied Sciences 2024年第7期14卷 1944-1962页

作者： Namogo Silué Sié Ouattara Mouhamadou Dosso Alain Clément Laboratoire des Sciences et Technologies de la Communication et de lInformation (LSTCI) Institut National Polytechnique Houphout Boigny (INPHB) Yamoussoukro Cte dIvoire Institut National Polytechnique Houphout Boigny (INPHB) Yamoussoukro Cte dIvoire UFR Mathmatique-Informatique Ecole Doctorale Sciences-Technologie et Agriculture Durable (ED STAD) Universit Felix Houphout-Boigny (UFHB) Abidjan Cte dIvoire Ecole de Gomatique et du Territoire (EGT) Abidjan Cte dIvoire LARIS SFR MATHSTIC Universit dAngers Angers France

Data compression plays a key role in optimizing the use of memory storage space and also reducing latency in data transmission. In this paper, we are interested in lossless compression techniques because their performance is exploited with lossy compression techniques for images and videos generally using a mixed approach. To achieve our intended objective, which is to study the performance of lossless compression methods, we first carried out a literature review, a summary of which enabled us to select the most relevant, namely the following: arithmetic coding, LZW, Tunstall’s algorithm, RLE, BWT, Huffman coding and Shannon-Fano. Secondly, we designed a purposive text dataset with a repeating pattern in order to test the behavior and effectiveness of the selected compression techniques. Thirdly, we designed the compression algorithms and developed the programs (scripts) in Matlab in order to test their performance. Finally, following the tests conducted on relevant data that we constructed according to a deliberate model, the results show that these methods presented in order of performance are very satisfactory:- LZW- arithmetic coding- Tunstall algorithm- BWT + RLELikewise, it appears that on the one hand, the performance of certain techniques relative to others is strongly linked to the sequencing and/or recurrence of symbols that make up the message, and on the other hand, to the cumulative time of encoding and decoding.

关键词： arithmetic coding BWT Compression Ratio Comparative Study Compression Techniques Shannon-Fano Huffman Lossless Compression LZW Performance Redundancy RLE Text Data Tunstall

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On the Randomness of Compressed Data

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INFORMATION 2020年第4期11卷 196-196页

作者： Klein, Shmuel T. Shapira, Dana Bar Ilan Univ Comp Sci Dept IL-5290002 Ramat Gan Israel Ariel Univ Data Sci & Artificial Intelligence Ctr Comp Sci Dept IL-40700 Ariel Israel

It seems reasonable to expect from a good compression method that its output should not be further compressible, because it should behave essentially like random data. We investigate this premise for a variety of known lossless compression techniques, and find that, surprisingly, there is much variability in the randomness, depending on the chosen method. arithmetic coding seems to produce perfectly random output, whereas that of Huffman or Ziv-Lempel coding still contains many dependencies. In particular, the output of Huffman coding has already been proven to be random under certain conditions, and we present evidence here that arithmetic coding may produce an output that is identical to that of Huffman.

关键词： data compression Huffman coding arithmetic coding Ziv-Lempel coding

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HIGHLY EFFICIENT, LOW COMPLEXITY arithmetic CODER FOR JPEG2000

HIGHLY EFFICIENT, LOW COMPLEXITY ARITHMETIC CODER FOR JPEG20...

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IEEE International Conference on Image Processing

作者： Francesc Auli-Llinas Department of Information and Communications Engineering Universitat Autonoma de Barcelona

ISBN: (纸本)9781479957521

arithmetic coding is employed in image and video coding schemes to reduce the statistical redundancy of symbols emitted by coding engines. Most arithmetic coders proposed in the literature generate variable-length codes, i.e., they produce one long codeword of variable size. This requires renormalization operations to control the internal registers of the coder and the propagation of carry bits. This paper introduces an arithmetic coder that generates fixed-length codewords. The main advantage of the proposed coder is that it avoids renormalization procedures, which reduces computational complexity. Also, it uses a variable-size sliding window mechanism to estimate with high precision the probability of the emitted symbols. Experimental results indicate that the proposed coder achieves coding efficiency superior to those coders employed in JPEG2000 and HEVC while having lower computational costs. When integrated in a JPEG2000 implementation, the proposed coder achieves coding gains between 0.5 to 1 dB at medium and high rates, and speedups between 1.1 to 1.3 in the bitplane coding stage.

关键词： arithmetic coding Context-adaptive models

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An Improved Iterative Decoding Scheme based on Error-resistant arithmetic Code

An Improved Iterative Decoding Scheme based on Error-resista...

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IEEE International Symposium on Circuits and Systems

作者： Qiuzhen Lin Kwok-Wo Wong College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Electronic Engineering City University of Hong Kong Hong Kong SAR China

ISBN: (纸本)9781479934331

In this paper, an improved soft in soft out (SISO) iterative decoding scheme for joint source-channel coding is presented. It is realized as the iterative soft decoding of arithmetic code based on sequential decoding to successively prune the decoding tree. Making use of the forecasted forbidden symbols, an error-resistant arithmetic code with an improved a posteriori probability (APP) metric is adopted to further enhance the error correction performance. Simulation results have validated the superiority of our scheme in terms of packet error rate for the AWGN channel.

关键词： Joint Source-Channel coding arithmetic coding Iterative Decoding

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