基于Contourlet变换的自适应门限分形零树混合图像编码

Coding method of adaptive threshold fractal and zerotree based on contourlet transform

Contourlet变换的基函数分布于多尺度、多方向上,弥补了小波基函数方向性不足的缺陷。本文考虑了分形编码过程中子树与父树匹配误差门限对编码的影响,提出了一种基于Contourlet变换的自适应门限分形零树混合图像编码方法,给出了所提出方法的实验结果,并与基于小波变换的分形零树混合图像编码方法进行了比较。实验结果表明,在压缩比相同的情况下,本文方法的PSNR性能优于基于小波变换的分形零树混合图像编码方法,能很好地保留图像的纹理和轮廓。

The Contourlet transform is with rich set of basis images oriented at varying directions in multiple scales. It＇s better than wavelet at capturing the dominant features in natural images. The match threshold between range subtree and parent domain subtree directly decides the image compression efficiency. A coding method of adaptive threshold fractal and zerotree is proposed based on Contourlet transform. The experimental results show that with the same compression ratio, the proposed algorithm can get better image quality than the wavelet image compression algorithm based on fractal coding and zerotree,and commendably keeps the image＇s textures in a broad compression rate scale.