.png){kind=icon}
返回
Chain code lossless compression using move-to-front transform and adaptive run-length encoding
.png){kind=icon}
PRE
AI
DOI：10.1016/j.image.2013.09.002.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Chain codes are the most size-efficient representations of rasterised binary shapes and contours. This paper considers a new lossless chain code compression method based on move-to-front transform and an adaptive run-length encoding. The former reduces the information entropy of the chain code, whilst the latter compresses the entropy-reduced chain code by coding the repetitions of chain code symbols and their combinations using a variable-length model. In comparison to other state-of-the-art compression methods, the entropy-reduction is highly efficient, and the newly proposed method yields, on average, better compression. (C) 2013 Elsevier B.V. All rights reserved.
Keyword:
Chain code
Compression
Move-to-front transform
Run-length encoding
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
S
IF:
2.7
论文数:
2.8K
被引数:
4.2K
机构
引用论文
分享收藏Lossless compression of map contours by context tree modeling of chain codes.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏An efficient raster font compression for embedded systems一种用于嵌入式系统的高效光栅字体压缩PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏
分享收藏
查看更多内容