New Lossless Compression Algorithms for Transport Images

IF 1 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
S. Fahmi, A. G. Davidchuk, E. Kostikova, Inland Shipping
{"title":"New Lossless Compression Algorithms for Transport Images","authors":"S. Fahmi, A. G. Davidchuk, E. Kostikova, Inland Shipping","doi":"10.17587/IT.27.299-305","DOIUrl":null,"url":null,"abstract":"The article considers the relevance of the development of lossless image compression and transmission algorithms and their application for creating transport video surveillance systems. A brief overview of lossless transport image compression methods is provided. We propose a method for compressing transport plots based on the pyramid-recursive method of splitting the source image into polygons of various shapes and sizes. We consider two new algorithms for implementing the proposed method that are fundamentally different from each other: with a transition to the spectral region and without a transition to the spectral region of the original signal to ensure lossless compression. The results of testing various well-known lossless compression algorithms are analyzed: series length, Huffman, and arithmetic encoding, and compared with the proposed algorithms. It is shown that the proposed algorithms are more efficient in terms of compression ratio (2—3 times) compared to the known ones, while the computational complexity increases approximately by more than 3-4 times.","PeriodicalId":43953,"journal":{"name":"IT-Information Technology","volume":null,"pages":null},"PeriodicalIF":1.0000,"publicationDate":"2021-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IT-Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17587/IT.27.299-305","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

Abstract

The article considers the relevance of the development of lossless image compression and transmission algorithms and their application for creating transport video surveillance systems. A brief overview of lossless transport image compression methods is provided. We propose a method for compressing transport plots based on the pyramid-recursive method of splitting the source image into polygons of various shapes and sizes. We consider two new algorithms for implementing the proposed method that are fundamentally different from each other: with a transition to the spectral region and without a transition to the spectral region of the original signal to ensure lossless compression. The results of testing various well-known lossless compression algorithms are analyzed: series length, Huffman, and arithmetic encoding, and compared with the proposed algorithms. It is shown that the proposed algorithms are more efficient in terms of compression ratio (2—3 times) compared to the known ones, while the computational complexity increases approximately by more than 3-4 times.
新的传输图像无损压缩算法
本文考虑了无损图像压缩和传输算法的发展及其在创建交通视频监控系统中的应用的相关性。简要概述了无损传输图像压缩方法。我们提出了一种基于金字塔递归方法的压缩传输图的方法,该方法将源图像分割成各种形状和大小的多边形。我们考虑了两种新的算法来实现所提出的方法,这两种算法在本质上是不同的:一种是向频谱区域过渡,另一种是不向原始信号的频谱区域过渡,以确保无损压缩。分析了各种著名的无损压缩算法的测试结果:序列长度、霍夫曼和算术编码,并与所提出的算法进行了比较。结果表明,本文提出的算法在压缩比方面比已知算法更高效(2-3倍),而计算复杂度大约增加了3-4倍以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
IT-Information Technology
IT-Information Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
3.80
自引率
0.00%
发文量
29
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信