分形图像编码中的特征差值分类法

基于分形的图像编码方法具有高压缩比、分辨率无关性、快速解码等优越性质。编码时间过长是分形图像压缩的主要缺点之一，对定义域和值域的分类匹配搜索能够有效地加速编码过程，是解决上问题的重要手段之一。在简单介绍当前常用的分类算法的基础上，基于分形编码的收缩特性提出一种特征差值分类算法，该方法原理简单，实现方便，灵活性强，能够和多种其它算法相结合，有效地排除不符合收缩特性的“伪匹配”，快速找到最优的匹配，节约编码时间，且在解码图像质量上获得了非常好的效果。

A FEATURE DIFFERENCE ALGORITHM IN FRACTAL IMAGE CODING

Fractal image compression has received much attention for its desirable properties like resolution independence, fast decoding and high compression ratio. Despite the advances made, the long computing times in the encoding phase still remain the main drawback of this technique. So far, several methods have been proposed in order to speed up fractal image coding. In this paper, some commonly used speed up algorithms are introduced briefly, and a new algorithm is put forward, which uses notation of feature difference based on the contraction characteristics of transformations in fractal image coding. The algorithm can be simply realized in corporation with many other speedup methods and efficiently exclude pseudo matched blocks in D R matching and searching process. Experimental result shows that the algorithm not only speedups the coding process but also greatly improves the quality of decoded image.