A Wavelet Image Compression Algorithm Based on Fractal Coding and Zerotree
ZHANG Hong-ying, YANG Chang-sheng (Computer System Engineering Institute, Zhejiang University, Hangzhou 310027)
In order to achieve a high image compression ratio in fractal cloding, the ability of fractal coding to predict wavelet coefficients is anyalyzed and the traditional way of fractal coding is found to be not able to effectively predict the entire wavelet coefficients and leads to a not very good coding result. A hybrid image compression algorithm based on wavelet transforming using fractal coding and zerotree coding that can make up for this flaw effectively is presented in this paper. First, the image is discomposed into a series of subimages in different orientations and different resolutions by wavelet transform, then the subimages in the same orientations but different resolutions are formed into wavelet subtrees, just like zerotree,at last ,the wavelet subtrees are coded by the way of either fractal or zerotree coding according to the size of error when coding.. This algorithm made a effective use of the redundance within subimages as well as the self-similarities within subimages and the similarities cross scales compared with traditional fractal image coding based on wavelet transforming. The experimental with this algorithm presented in this paper also show that the proposed algorithm can obtain a good compression result in a broad compression rate scale.