采用分形压缩算法来提高压缩速度和压缩比的一种有效途径是降低对拼贴误差的要求，然而这往往导致图象失真.为克服该问题，在经典分形压缩算法的基础上，提出了一种新的基于拼贴误差拟合 (补偿 )的分形压缩算法.该算法可以提供两种不同拼贴误差的分形编码，由于通过对不同区块使用与之相适应的相似变换类型，可以有效地补偿拼贴误差，从而可降低压缩图象的失真度.理论研究和实际应用表明，该算法为分形压缩图象所面临的失真度和压缩比的矛盾提供了一种有效的解决方案.

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.