.png){kind=icon}
返回
IMAGE-DATA COMPRESSION USING EDGE-OPTIMIZING ALGORITHM FOR WFA INFERENCE
.png){kind=icon}
PRE
AI
DOI：10.1016/0306-4573(94)90010-8.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Weighted finite automata (WFA) define real functions, in particular, grayness functions of graytone images. Earlier, the authors gave an automatic encoding (inference) algorithm that converts an arbitrary function (graytone image) into a WFA that can (approximately) regenerate it. The WFA obtained by this algorithm had (almost) minimal number of states, but a relatively large number of edges. Here we give an inference algorithm that produces a WFA with not necessarily minimal number of states, but with a relatively small number of edges. Then we discuss image-data compression results based on the new inference algorithm alone and in combination with wavelets. It is a simpler and more efficient method than the other known fractal compression methods. It produces better results than wavelets alone.
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
I
IF:
6.9
论文数:
5.2K
被引数:
1.4W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏
分享收藏 没有更多内容
没有更多内容