应用人眼视觉特性的Contourlet域图像压缩编码算法

鉴于Contourlet变换存在冗余，小波变换不能准确捕获图像特征等不足，提高编码速度和改进视觉效果，提出了一种基于人眼视觉特性的混合域图像压缩编码算法。算法对原始图像进行小波分解，对中高频小波子带进一步实施自适应方向分解;根据人眼视觉特性（HVS），对不同子块变换系数进行加权处理;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;根据系数重要性，对低频系数采用新的排列结构，采用SPIHT编码思想完成图像压缩。实验结果表明，提出的混合域图像编码方法是一种高效的图像压缩算法，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）。

Image coding scheme based on contourlet transform and human visual system

For the overall contourlet transform is redundant and the wavelet transform cannot efficiently take advantage of the fact that the edges usually found in natural images are smooth curves.In this paper,a new image coding scheme is presented.The wavelet transform is applied to original image,and the directional filter banks（DFB） are employed to middle and high frequency subbands;The visual gains are achieved by exploiting HVS characteristics to weigh wavelet coefficients according to their perceptual importance;the new extended spatial orientation tree are constructed.The lower frequency exploit a new partitioning structure based on the importance of coefficients.The experiment results show that the modified image compression scheme provides higher perceptual quality and higher PSNR than SPIHT and WBCT,especially at low bit rates.