基于快速逐次逼近量化的零树编码图像压缩算法

A Zerotree Coding Image Compression Algorithm Based on Fast Successive Approximation Quantization

提出一种基于快速逐次逼近量化的零树编码图像压缩算法。该算法通过以下三项措施提高EZW算法的编码效率:(1)引进子带峰值的概念建立逐次逼近量化的快速算法;(2)对小波边缘子带进行有效处理以消除编码冗余;(3)建立了5个上下文内容模型对重要位符号进行编码。实验结果表明,该算法是一种高效的图像压缩算法,在压缩性能方面优于经典的EZW和SPIH T算法。

The paper proposes a zerotree coding image compression algorithm based on fast successive approximation quantization.The algorithm improves the coding efficiency of EZW.It establishes fast successive approximation quantization by introducing the conception of subband peak,and disposes marginal subband effectively.More,it codes sign of important coefficient with the five ambient context model.The experiment shows that it is an effective image compression algorithm,and its compression performance is superior to EZW and SPIHT algorithms.