An Adaptive IFS Encoding Algorithm Based on the Classification According to HVS
基于视觉灵敏度分类的IFS自适应图象编码算法

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.