A Fractal Compression Algorithm Based on Collage Distance Fitting and Compensating
基于拼贴误差拟合（补偿）的分形压缩算法

In most of the fractal image compression algorithms, the most efficient method to speed up coding process and increase compression ratio is to adopt bigger collage distance. However this method will result in poor image. To overcome the disadvantage, this paper has presented a new fractal compression algorithm based on collage distance fitting and compensating. This algorithm has provided two kinds of different compression codes, which contain their own unique collage distance sets and different types of similar transforms. By applying different types of similar transforms to different range blocks, the collage distance has been compensated, and the image quality and compression speed have been improved. In the end, an experiment of 'Lena' image has provided the application and demonstration of this algorithm. Theoretical analysis and application in practice have indicated that the proposed algorithm can be regarded as a suitable alternative to ordinary fractal compression method for balancing between the distortion measure and compression ratio.