基于小波-Contourlet变换的图像压缩算法  

Image Compression Algorithm Using Wavelet-Based Contourlet Transform

作　　者：田秀伟[1,2] 郑喜凤[1] 丁铁夫[1] 

机构地区：[1]中国科学院长春光学精密机械与物理研究所,长春130033 [2]中国科学院研究生院,北京100039

出　　处：《数据采集与处理》2010年第4期437-441,共5页Journal of Data Acquisition and Processing

基　　金：中国科学院东北振兴科技行动计划重点项目基金(DBZX-2-017)资助项目

摘　　要：利用小波-Contourlet变换对图像分解具有多尺度和多方向性的特点,提出一种结合小波-Contourlet变换和无链表集合分裂嵌入块编码的图像压缩算法。小波-Contourlet通过方向滤波器组把小波分解的高频子带进一步分解为多个方向子带,从而更稀疏地表示图像的边缘和纹理。无链表集合分裂嵌入块算法充分利用系数子带内的相关性,具有复杂度低、编码效率高的优点。实验结果表明,与基于小波变换的SPIHT算法和SPECK算法相比,新算法对纹理丰富的图像有很好的压缩效果和视觉效果。As the wavelet-based Contourlet transform provides a multi-scale and directional decomposition for images, a new image coding scheme, called the CSPECK, is proposed. It is constructed by the wavelet-based Contourlet transform and listless set partitioning embedded block （LSK） algorithm. In the wavelet-based Contourlet transform, the high frequency subband decomposed by the wavelet transform is further decomposed into multiple directional subbands by a directional filter bank, so as to explain the edge and the texture of the image more sparsely. The LSK algorithm by sets in the form of blocks of contiguous coefficients within subbands exhibits lower complexity and more efficient compression ratio. Experimental results demonstrate that the proposed method is efficient on coding images with textures and contours. Simulation results show that the new coding algorithm is visually superior to the wavelet SPI- HT and SPECK scheme in preserving details and textures on the coded images.

关 键 词：小波-CONTOURLET变换 方向滤波器组 图像编码 无链表集合分裂嵌入块编码 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]