基于子块差特征的分形图像压缩编码技术

Fractal Image Compression Coding Technology Based on Sub-block Difference

分形图像压缩编码一直以高压缩比而著称,由于其编码时间较长而饱受诟病,因此改进采用子块差特征的分形图像编码算法。分割后的图像块依照图像显著度分为重要区域块与非重要区域块,并将各类图像块以子块特征排序。设定显著度阈值,当小于设定的阈值,则认为是非重要区域,否则为重要区域;匹配搜索过程中,在同类别的值域块库中进行匹配搜索,搜索满足设定的误差阈值范围码本块。

Fractal image compression coding has always been known for its high compression ratio, and has been criticized for its long coding time. Therefore, the fractal image coding algorithm using sub-block difference features has been improved. The segmented image blocks are divided into important area blocks and non-important area blocks according to the image saliency, and the various image blocks are sorted by sub-block features. When the salience threshold is set,when it is less than the set threshold, it is considered to be a non-important region, otherwise it is an important region;in the process of matching search, a matching search is carried out in the range block library of the same category to search for the code block that meets the set error threshold.