为了提高基于互联网的图象编码的压缩比和多带宽适应性，提出了一种新的嵌入式零树图象编码方法，该方法首先在连续累进量化方法中使用单队列算法，从而不仅无需使用动态队列，而且率失真特性也得到改善；其次设计了一种基于空间树递归扫描的零树编码快速算法，因而完全解决了重复扫描问题；最后基于编码符号的频带内邻域相关性，为自适应算术编码定义一种新的Markov模型，实验结果表明，该算法在保持高粒度多码率特性的同时，压缩效率较EZW算法有明显提高。

An improved embedded zerotree wavelet image coding algorithm is proposed in this paper. It is an improved vision of Shaprio's EZW algorithm. First, a single list scheme is used in successive-approximation Quantization(SAQ), dispensing with double dynamic list of EZW algorithm. The single list make the scan process more simple and faster, and lead to better rate-distortion characteristic. Second, a fast algorithm based on spatial orientation tree recursive scan for the zerotree coding is designed. The zerotree symbols of one quantization layer can be calculated with only one access per coefficient, solving the rescaning problem completely. At last, a new Markov model based on quantization symbol field relativity for adaptive arithmetic coding algorithm is used, for higher compression efficient. Experimental results show that it peroforms better than the EZW algorithm in coding efficiency, maintains the fine-granularity scalability.