基于不规则区域分割及灰度排序分类的分形压缩算法

基本分形压缩分类算法多以单一特征分类且需要庞大的匹配搜索运算。首次将PCNN分割引入分形压缩,提出一种基于不规则区域分割及图像灰度排序分类的分形压缩算法。算法首先对原图像进行不规则区域分割,然后利用所得二值图像的灰度值与原图像的灰度值两个特征对图像块进行联合分类,以缩小搜索匹配的范围,提高压缩速度。实验结果表明,所提算法在保证解码质量的前提下,大幅度减少了编码时间。

An algorithm of fractal compression based on irregular region segmentation and gray sort classification

Most basic fractal compression classification algorithms are classified by a single feature, and they all involve a huge amount of machine operation in the matching search. An algorithm of fractal compression based on irregular region segmentation and gray sort classification was put forward. In order to reduce the search range, the image blocks were classified according to the gray scale values of the binary images between the original image and the one obtained by dividing the original image with the method of irregular region segmentation. Experiment results show that the algorithm can significantly reduce the coding time without sacrificing the quality of decoding.