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Context weighting for general finite-context sources

IEEE TRANSACTIONS ON INFORMATION THEORY 1996年第5期42卷 1514-1520页

作者： Willems, FMJ Shtarkov, YM Tjalkens, TJ RUSSIAN ACAD SCI INST PROBLEMS INFORMAT TRANSMISSMOSCOW 101447RUSSIA

Context weighting procedures are presented for sources with models (structures) in four different classes. Although the procedures are designed for universal data compression purposes, their generality allows applicat... 详细信息

关键词： sequential data compression universal source coding finite-context sources modeling procedure arithmetic coding cumulative redundancy bounds classification procedure

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arithmetic INTERPOLATION SEARCH FOR ALPHABETIC TABLES

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IEEE TRANSACTIONS ON COMPUTERS 1992年第4期41卷 493-499页

作者： PERL, Y GABRIEL, L Dept. of Comput. & Inf. Sci. New Jersey Inst. of Technol. Newark NJ USA

One of the fastest search techniques for uniformly distributed sorted numerical tables is interpolation search. This divide and conquer technique accesses the most probable key rather than the middle key as in binary search and continues to search similarly the appropriate part of the table. In a previous work we proved a lg lg n average number of accesses for interpolation search. The inefficiency of interpolation search for an alphabetic table is demonstrated by Burton and Lewis who suggest a robust variation to improve the efficiency. This inefficiency is expected since such tables are usually far from uniform distribution. However, for nonuniformly distributed tables for which the cumulative distribution function F is known, applying F to the keys yields uniform distribution for which interpolation search is very fast. In arithmetic coding a string of characters is mapped into the [0, 1) interval according to the probabilities of its characters. We found that this transformation, designed for data compression, is actually the cumulative distribution function F for alphabetic tables. Experiments confirm that interpolation search on alphabetic tables, applying arithmetic coding to the character-strings in a sophisticated way, show a performance very close to lg lg n accesses. Hence, we design a new fast search technique for alphabetic tables.

关键词： ALPHABETIC TABLES arithmetic coding INTERPOLATION SEARCH MODIFIED INTERPOLATION SEARCH NONUNIFORMLY DISTRIBUTED TABLES

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Universal lossless compression via multilevel pattern matching

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IEEE TRANSACTIONS ON INFORMATION THEORY 2000年第4期46卷 1227-1245页

作者： Kieffer, JC Yang, EH Nelson, GJ Cosman, P Univ Minnesota Dept Elect & Comp Engn Minneapolis MN 55455 USA Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Anoka Ramsey Community Coll Coon Rapids MN 55433 USA Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92037 USA

A universal lossless data compression code called the multilevel pattern matching code (MPM code) is introduced. Ln processing a finite-alphabet data string of length n, the MPM code operates at O(log log n) levels sequentially. At each level, the MPM code detects matching patterns in the input data string (substrings of the data appearing in two or more nonoverlapping positions). The matching patterns detected at each level are of a fixed length which decreases by a constant factor from level to level, until this fixed length becomes one at the final level. The MPM code represents information about the matching patterns at each level as a string of tokens, with each token string encoded by an arithmetic encoder. From the concatenated encoded token strings, the decoder can reconstruct the data string via several rounds of parallel substitutions. A O(1/log n) maximal redundancy/sample upper bound is established for the MPM code with respect to any class of finite state sources of uniformly bounded complexity. We also show that the MPM code is of linear complexity in terms of time and space requirements. The results of some MPM code compression experiments are reported.

关键词： arithmetic coding entropy lossless data compression redundancy universal codes

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Performance analysis of data compression algorithms for heterogeneous architecture through parallel approach

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JOURNAL OF SUPERCOMPUTING 2020年第4期76卷 2275-2288页

作者： Mahammad, Farooq Sunar Viswanatham, V. Madhu VIT Univ Sch Comp Sci & Engn Vellore Tamil Nadu India

Today, there is a huge demand for data compression due to the need to reduce the transmission time and increase the capacity of data storage. Data compression is a technique which represents an information, images, video files in a compressed or in a compact format. There are various data compression techniques which keep information as accurately as possible with the fewest number of bits and send it through communication channel. arithmetic algorithm, Lempel-Ziv 77 (LZ77) and run length encoding with a K-precision (K-RLE) algorithms are lossless data compression algorithms which have lower performance rate because of their processing complexity as well as execution time. This paper presents an efficient parallel approach to reduce execution time for compression algorithms. The proposed OpenMP is an efficient tool for programming within parallel shared-memory environments. Finally, it shows that performance parallel model experimented using Open Multi-Processing (OpenMP) Application Programming Interface through Intel Parallel studio on multicore architecture platform with spec of Core 2 duo-2.4 GHz, 1 Gb RAM machine of parallel approach for compression algorithms has been improved remarkably against sequential approach. The improvement in compression ratio through an efficient parallel approach leads to reduction on transmission cost, reduction in storage space and bandwidth without additional hardware infrastructure. An overall performance evaluation shows arithmetic data compression algorithm with 46% which is better than LZ77 of 44% as well as K-RLE of 37% data compression algorithms.

关键词： arithmetic coding Data compression K-RLE algorithm LZ77 algorithm Multicore architecture Parallel processing OpenMP

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Efficient compression of molecular dynamics trajectory files

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JOURNAL OF COMPUTATIONAL CHEMISTRY 2012年第27期33卷 2131-2141页

作者： Marais, Patrick Kenwood, Julian Smith, Keegan Carruthers Kuttel, Michelle M. Gain, James Univ Cape Town Dept Comp Sci ZA-7925 Cape Town South Africa

We investigate whether specific properties of molecular dynamics trajectory files can be exploited to achieve effective file compression. We explore two classes of lossy, quantized compression scheme: interframe predictors, which exploit temporal coherence between successive frames in a simulation, and more complex intraframe schemes, which compress each frame independently. Our interframe predictors are fast, memory-efficient and well suited to on-the-fly compression of massive simulation data sets, and significantly outperform the benchmark BZip2 application. Our schemes are configurable: atomic positional accuracy can be sacrificed to achieve greater compression. For high fidelity compression, our linear interframe predictor gives the best results at very little computational cost: at moderate levels of approximation (12-bit quantization, maximum error similar to 10-2 angstrom), we can compress a 12 fs trajectory file to 58% of its original size. For 200 fs time stepstypically used in fine grained water diffusion experimentswe can compress files to similar to 25% of their input size, still substantially better than BZip2. While compression performance degrades with high levels of quantization, the simulation error is typically much greater than the associated approximation error in such cases. (c) 2012 Wiley Periodicals, Inc.

关键词： Keywords: MD trajectory files compression arithmetic coding interframe prediction

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Encoding of alffine motion vectors

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IEEE TRANSACTIONS ON MULTIMEDIA 2007年第7期9卷 1346-1356页

作者： Kordasiewicz, Roman C. Gallant, Michael D. Shirani, Shahram LSI Log Corp Waterloo ON N2V 1C5 Canada McMaster Univ Dept Elect & Comp Engn Hamilton ON L8S 4K1 Canada

An affine motion model provides better motion representation than a translational motion model. Therefore, it is a good candidate for advanced video compression algorithms, requiring higher compression efficiency than current algorithms. One disadvantage of the affine motion model is the increased number of motion vector parameters, therefore increased motion vector bit rate. We develop and analyze several simulation based approaches of entropy coding for orthonormalized affine motion vector (AMV) coefficients, by considering various context-types and coders. In our work we expand the traditional idea of a context type by introducing four new context types. We compare our method of contexts-type and coder selection with context quantization. The best of our contexts-type and coder solutions produces 4% to 15% average AMV bit-rate reductions over the original VLC approach. For more difficult content AMV bit rate reduction up to 26% is reported.

关键词： terms-Affine motion estimation affine motion vectors arithmetic coding CABAC context determination video compresion VLC

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An arithmetic controller design for numerical control

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COMPUTERS & ELECTRICAL ENGINEERING 2013年第7期39卷 2045-2052页

作者： Yi, Shu-Chung Hsieh, Chin-Fa Natl Changhua Univ Educ Dept Comp Sci & Informat Engn Changhua 500 Taiwan Asia Univ Dept Comp Sci & Informat Engn Taichung Taiwan Univ Sci & Technol China Dept Elect Engn Taipei 11581 Taiwan

This paper provides an arithmetic controller comprising: an arithmetic logic unit having a plurality of arithmetic instructions, such as ADD (Addition), SUB (Subtraction), MUL (Multiplication), and DIV (Division) instructions. This arithmetic processor was implemented by a cell-based flow and supports the basic mathematical operations, and numerical control. All mathematical instructions are composed of three bytes. In the first byte, it contains the operation code and the address of the operand, while the operands are in the second and third bytes. While the processor architecture compared with the conventional CPU, the performance is speed up for the number reduction of instruction cycle. The number of instruction cycle is decreased to five T-states. All of these circuits were implemented by the TSMC 0.35 mu m cell library. A 20-pin I/O PAD was selected to package this processor. The experimental results are showed and discussions are made. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： PROGRAMMABLE controllers NUMERICAL analysis arithmetic coding MODULES (Algebra) ENERGY consumption ELECTRIC capacity

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LZW-CIE: a high-capacity linguistic steganography based on LZW char index encoding

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NEURAL COMPUTING & APPLICATIONS 2022年第21期34卷 19117-19145页

作者： Varol Arisoy, Merve Burdur Mehmet Akif Ersoy Univ Fac Technol Informat Syst Engn TR-15300 Burdur Turkey

With the effect of digitalization, the transfer of all text documents over the Internet rather than human transmission has increased, and this situation has revealed the idea that text documents can be used as a carrier that can safely store information. Realizing that methods such as word-line shifting, usage of spaces, replacement of the word with its synonym are fragile against steganalysis, led to new searches and it was determined that deep learning models were more resistant to detecting the presence of hidden words. In this study, the text generation based on the information that is wanted to be hidden without a carrier text, both at word and character level, was performed. arithmetic coding, perfect tree and Huffman coding methods were used as secret information embedding methods in text generation based on word level. In this part of the study, bidirectional LSTM architecture with attention mechanism was created as language model. In text generation based on character level, a new secret information embedding algorithm is created by combining the LZW compression algorithm with the Char Index (LZW-Char Index Encoding) method. The character-level model is created as a result of using the encoder-decoder architecture together with bidirectional LSTM and Bahdanau attention. The proposed method was evaluated from the perspectives of information embedding efficiency, information imperceptibility and hidden information capacity. As a result of the experiments, it was determined that the method exceeded the state-of-the-art performance and was more resistant to steganalysis.

关键词： Linguistic steganography LZW-CIE encoding arithmetic coding Huffman coding Fixed-length coding Automatic text generation

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A FAST AND EFFICIENT COMPRESSION METHOD FOR BINARY IMAGES

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SIGNAL PROCESSING-IMAGE COMMUNICATION 1994年第1期6卷 69-76页

作者： FRANTI, P Department of Computer Science University of Turku SF-20520 Turku Finland

The use of arithmetic coding for binary image compression achieves a high compression ratio while the running time remains rather slow. A composite modelling method presented in this paper reduces the size of the data to be coded by arithmetic coding. The method is to code the uniform areas with less computation and apply arithmetic coding to the areas with more variation.

关键词： IMAGE COMPRESSION BINARY IMAGES BLOCK coding arithmetic coding

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Accurate per-link loss tomography in dynamic sensor networks

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COMPUTER NETWORKS 2018年第Jul.5期139卷 81-91页

作者： Cao, Chenhong Gao, Yi Dong, Wei Bu, Jiajun Zhejiang Univ Coll Comp Sci Hangzhou Zhejiang Peoples R China

Wireless Sensor Networks (WSNs) have been successfully applied in many application areas. Understanding the wireless link performance is very helpful for both protocol designers and network managers to improve the network performance and prolong the network lifetime. Loss tomography is a popular approach to infer the per-link loss ratios from end-to-end delivery ratios. Previous studies, however, are usually targeted for networks with static or slowly changing routing paths. In this work, we propose Dophy, a Dynamic loss tomography approach specifically designed for dynamic WSNs where each node dynamically selects the forwarding nodes towards the sink. The key idea of Dophy is based on an observation that most existing protocols use retransmissions to achieve high data delivery ratio. Dophy employs arithmetic encoding to encode the number of retransmissions along the paths compactly. Dophy incorporates two mechanisms to optimize its performance. First, Dophy intelligently reduces the size of the symbol set by aggregating the number of retransmissions, reducing the encoding overhead significantly. Second, Dophy periodically updates the probability model to minimize the overall transmission overhead. We implement Dophy on the TinyOS platform and evaluate its performance extensively using large-scale simulations. Results show that Dophy achieves both high encoding efficiency and high estimation accuracy. Comparative studies show that Dophy significantly outperforms traditional loss tomography approaches in terms of accuracy. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Wireless sensor network Loss tomography arithmetic coding

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