基于改进逐次逼近量化与复杂关联模型的零树图像编码算法

Image Coding Based on Improved SAQ and Complex Context Modeling

提出一种基于改进逐次逼近量化与复杂关联模型的零树图像编码算法 ,该算法通过以下 4项措施提高EZW算法的工作效率 :(1)对最低频子带进行单独编码 ;(2 )定义多阈值以完善逐次逼近量化过程 ;(3)修改嵌入编码策略以消除编码冗余 ;(4)采纳关联模型以提高算术编码效率 .实验结果表明 ,该算法是一种高效的图像压缩算法 ,其编解码速度、图像复原质量等关键技术指标均优于 EZW和

An improved version of EZW algorithm is presented. Unlike traditional EZW, the lowest frequency subband is coded separately from other highpass subbands, the SAQ process is improved by using multi threshold, the embedded coding strategy is modified and the complex context modeling is adopted in our compression algorithm. The experiment results show that the new image compression scheme performs better than that of EZW and SPIHT in the aspects of recovery image quality and encoding/decoding rate.