基于四叉树的自适应门限分形图象IFS压缩方法

为了克服四叉树分块ＩＦＳ编码过程中，排列块与区域块的匹配误差不考虑输入图象特点这一缺点，提出了一种新的基于迭代函数系统（ＩＦＳ）进行静止灰度图象压缩的方法。该方法是根据当前排列块的方差来确定它与区域块的匹配门限。经分析证明，这种基于自适应门限的ＩＦＳ编码方法与人类视觉系统的特性基本相符，而且实验也证明，这一自适应门限的编码方法提高了ＩＦＳ图象压缩的适应性。

Fractal Image Compression Based on Adaptive Threshold IFS

In the conventional iterated function system(IFS) image compression, the threshold of distortion between range block and domain block is prefixed which does not take the statistics characteristics of current range block into account. Thus the encoding scheme can not adapt to different input images and sometimes the encoding performance relies on the skill of the operator. In order to avoid that problem, a new scheme to compress still grayscale image is presented. The difference between this new scheme and the conventional one is that the threshold in the new scheme is calculated from the variance of the range block. Therefore the encoding system can adapt to the given image. The threshold is analyzed and a conclusion is drawn that the threshold is a positive portion of the variance of current range block. Furthermore, this new encoding scheme is proved to be in accordance with features of human visual system. The adaptive encoding scheme improves the effectiveness of encoding. This new scheme also makes the IFS encoding algorithm more practical.