基于视觉特性的Contourlet域图像压缩编码算法

A New Image Coding Using Contourlet Transform and Human Visual System

为了有效克服小波变换难以准确捕获图像特征、而Contourlet变换存在冗余等不足,本文提出了一种基于视觉特性的Contourlet域图像压缩编码算法。该算法首先对原始图像进行小波分解,并对中高频小波子带进一步实施自适应方向分解;然后根据人眼视觉特性(HVS),对变换系数进行加权处理;再结合小波分解与方向分解特点,构造扩展的空间方向树结构;最后采用SPIHT编码思想完成图像的压缩。实验结果表明,本文提出的Contourlet域图像编码方法是一种高效的图像压缩算法,不仅其压缩效果明显优于SPIHT、WBCT等图像压缩方案(特别是低比特率下),而且具有比较强的通用性与适应性(SPIHT与WBCT对于Barbara之类纹理图像压缩效果较差,然而本文算法的压缩效果却较理想)。

The wavelets cannot efficiently take advantage smooth curves, while the overall contourlet transform is of the fact that the edges usually found in natural images are redundant. A new image coding using coutourlet transform and human visual system is proposed in this paper. Firstly, the wavelet transform is applied to original image, and the directional filter banks（DFB） are＇employed to middle and high frequency subbands. Then, the high frequency coefficients are weighed according to the human visual system. Thirdly, the new extended spatial orientation tree are constructed. Finally, the encoding scheme is realized by the idea of SPIHT. The experiment results show that the new image compression scheme performs better than that of the state-of-art image coders （SPIHT, WBCT） reported in the literature, especially for low bit-rate and texture image.