为了提高IFS自适应图象压缩编码方法对不同图象的适应能力，在按人类视觉对比灵敏度分类的基础上，提出了一种进行分形图象IFS自适应压缩编码的新算法，同时定义了广义置信度的概念，并根据MSE误差曲线的广义置信度，确定了基于四叉树结构的分块分形编码过程中的匹配误差门奶。这种自适应门限编码算法不仅克服了传统固定门限IFS编码算法不能很地适应不同复杂程度输入图象的缺点，而且还提高了编码的效率。实验结果证明，此算法不仅可以自动地适应不同的输入图象，而且解码图象的视觉效果良好。

The paper presents a new adaptive fractal image IFS encoding algorithm based on classification. The classification is according to the contrast sensitivity of human visual system(HVS). It also gives the concept of generalized creditability (GC) and uses GC of between a certain range block and its domain blocks to determine the matching threshold in quadtree partitioning in partitioned fractal IFS encoding. This adaptive algorithm avoids the problem which is caused by the conventional algorithm based on prefixed threshold: The conventional algorithm can not adapt to input images with different complexity. The adaptive algorithm takes good advantage of the statistical characteristics in them, and calculates the threshold according to the variance of the input range block. In this way, the adaptive algorithm improves the encoding efficiency and makes the IFS image encoding more practical. Experimental results show that this new algorithm can adapt to different input images automatically while the decoded images are still satisfying. It also compares the adaptive algorithm with the conventional fixed threshold algorithm.