为了解决传统分形压缩编码时间过长的问题，提出了一种基于小波分解的快速分形图象压缩算法.该算法利用小波分解后各频带间能量分布不均衡的特性，将集中图象主要能量的低频域看作是一种图象，进行传统分形编码 ;然后利用小波分解后不同分辨率子带图象之间的相似性，用低频域的全搜索代替传统算法中整个区域的全搜索，将在低频域得到的分形参数进行适当的比例变换得到整幅图象的分形码，解码时，进行同传统算法相同的迭代过程，所得解码图象即为原图的逼近图象.实验结果表明，该算法在压缩比不变，且基本不影响恢复图象质量的前提下，大大提高了编码速度，明显改善了分形图象压缩中编解码时间的不对称.

In order to reduce image coding time,a new fast fractal method based on wavelet decomposition is presented in this paper. This algorithm is mainly implemented in two fold. Firstly, according to the feature of wavelet decomposition whose energy is ununiformity distribution in subbands of whole wavelet transform image, the low frequency region, where most of energy concentrates, is regarded as a kind of image, and can be encoded with traditional fractal method. Secondly, owing to the similarity of subband image among different channels after wavelet decomposition, instead of global search mechanism we have introduced a local optimal solution to gain the whole image's fractal parameter by suitable scale transform of low frequency region's. The analysis and results show that the encoding speed is improved greatly in case of the fixed compression ratio, and the quality of the reconstructed image can be better retained. It's very evidently that the dissymmetry between the encoding and decoding process has been reformed drastically.