A Still Image Compression Method Based on Structural Similarity of Wavelet Transform Among Different Scales
一种基于小波变换各尺度相似性的 静止图象压缩方法

Wavelet transform has very good spatial frequencial localization characteristics which show itself mainly at three aspects: frequency compression feature, space compression feature and structural similarity of wavelet coefficients among different scales. All these characteristics are propitious to compress still images. But classical compression methods based on wavelet transform seldom make good use of the structural similarity of significant wavelet coefficients. This paper uses the idea of zero tree compression algorithm and Rinaldo's block predicting method for reference and presents a new still image compression method to eliminate the structural redundancy of significant wavelet coefficients on different scales. The experiment results are satisfactory and prove the validity of this method.