关键词: 小波变换, 小波树, 峰值信噪比

Abstract: Image itself has the great amount of data, it makes the transportation efficiency very low. In order to meet the demand of current network applications, it is necessary to develop a good compression algorithm which can compress the image quickly with less distortion. The paper studies two existing compression algorithms based on wavelet transformation and finds out their features and their shortages. It classifies the different wavelet trees in different frequencies after the wavelet transformation and uses a certain algorithm to compress them so that the total compression effect can be improved and the complexity can be reduced as well. Experimental result proves that the improved image compression algorithm brings better effect and efficiency than those two algorithms. Classifying and compressing respectively is effective. It improves the compression effect and reduces the complexity of the algorithm.

Key words: wavelet transformation, wavelet tree, peak signal to noise ratio