文章基本信息

标题：A content awareness module for predictive lossless image compression to achieve high throughput data sharing over the network storage
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作者：Asif Rajput ; Jianqiang Li ; Faheem Akhtar 等
期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2022
卷号：18
期号：3
页码：1-9
DOI：10.1177/15501329221083168
语种：English
出版社：Hindawi Publishing Corporation
摘要：The idea of applying integer Reversible Colour Transform to increase compression ratios in lossless image compression is a well-established and widely used practice. Although various colour transformations have been introduced and investigated in the past two decades, the process of determining the best colour scheme in a reasonable time remains an open challenge. For instance, the overhead time (i.e. to determine a suitable colour transformation) of the traditional colour selector mechanism can take up to 50% of the actual compression time. To avoid such high overhead, usually, one pre-specified transformation is applied regardless of the nature of the image and/or correlation of the colour components. We propose a robust selection mechanism capable of reducing the overhead time to 20% of the actual compression time. It is postulated that implementing the proposed selection mechanism within the actual compression scheme such as JPEG-LS can further reduce the overhead time to 10%. In addition, the proposed scheme can also be extended to facilitate network-based compression–decompression mechanism over distributed systems.
关键词：Reversible colour transformation;lossless image processing;image coding;awareness computing;image compression