摘要
提出一种用确定性的广义有限自动机(GFA)对灰度图像进行压缩编码的方法。对一幅输入的数字化灰度图像,检测其中的自相似性,该图像可以被表示成一个广义有限自动机。解码算法可以非常高效的由确定的广义有限自动机复原图像,且结果图像没有很明显的方块效应。这种方法与传统的有限自动机方法相比具有状态数较少、压缩比高、压缩效果较好的优点。
In this paper it introduces an approach to compress and code gray image using deterministic Generalized Finite Automata （GFA）. By detecting the self-similarity inside an input digitized gray image, the GFA can be constructed to describe the image. The decoding algorithm can restore image from deterministic Generalized Finite Automata efficiently, and the regenerated images have no obvious blocking effect. This method has a smaller number of states than an equivalent classical finite automaton. Meanwhile it also has an advantage of higher compression without further degradation of quality.
出处
《计算机应用与软件》
CSCD
2009年第3期231-233,共3页
Computer Applications and Software
关键词
图像压缩
有限自动机
广义有限自动机
灰度图像
Image compression Finite automata（FA） Generalized finite automata（GFA） Gray image
