机构地区:[1]Laboratoire des Sciences et Technologies de la Communication et de lInformation (LSTCI), Institut National Polytechnique Houphout Boigny (INPHB), Yamoussoukro, Cte dIvoire [2]Institut National Polytechnique Houphout Boigny (INPHB), Yamoussoukro, Cte dIvoire [3]UFR Mathmatique-Informatique, Ecole Doctorale Sciences-Technologie et Agriculture Durable (ED STAD), Universit Felix Houphout-Boigny (UFHB), Abidjan, Cte dIvoire [4]Ecole de Gomatique et du Territoire (EGT), Abidjan, Cte dIvoire [5]LARIS, SFR MATHSTIC, Universit dAngers, Angers, France
出 处:《Open Journal of Applied Sciences》2024年第7期1944-1962,共19页应用科学(英文)
摘 要: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.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
分 类 号:TN9[电子电信—信息与通信工程]
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