一种改进的嵌入零树小波图像编码算法

AN ENHANCED IMAGE CODING ALGORITHM BASED ON EMBEDDED ZEROTREE WAVELET

基于逐次逼近量化与零树结构的嵌入零树小波编码（EZW）是一种优秀的图像压缩算法,然而该算法进行逐次逼近量化时需搜索扫描所有小波系数,从而必然导致扫描高频子带所产生的二进制符号流中存在大量冗余,这无疑会大大影响其编码效率.针对EZW编码算法存在的以上不足,提出了一种改进的嵌入零树小波图像编码算法,该算法能够通过定义多阈值、改进逐次逼近量化过程、修改嵌入编码策略、采纳复杂关联模型等措施,进一步提高EZW算法工作效率.实验结果表明:改进的EZW编码算法是一种高效的图像压缩算法,其压缩速度、图像复原质量等关键技术指标均明显优于EZW和S+P等编码算法（特别是在高压缩比下）.

The embedded zerotree wavelet compression (EZW) uses the zerotree structure of wavelet coefficients and successive approximation quantization (SAQ). The EZW compression scans iteratively whole wavelet coefficients during the successive approximation quantization process, which decreases the compression efficiency considerably. In this paper, an enhanced image coding algorithm based on embedded zerotree wavelet is presented, in which the multi-threshold is defined, the SAQ process is improved, the embedded coding strategy is modified, and the complex context modeling is adopted. The experiment results show that the new image compression scheme performs better than that of EZW and S + P in the aspects of compression ratio, image quality and coding efficiency.