基于改进的SPIHT整数提升小波变换的图像压缩  

Image Compression Based on Integer Lifting Wavelet Transform and Improved SPIHT

作　　者：龚劬[1] 阮华[1] 

机构地区：[1]重庆大学数理学院,重庆400030

出　　处：《计算机仿真》2009年第3期195-197,共3页Computer Simulation

摘　　要：针对传统小波变换过程复杂的缺点和SPIHT算法编码过程重复运算、存储量大以及未考虑人眼视觉特性的不足,提出了基于改进的SPIHT整数提升小波变换的图像压缩算法,首先选用9-7整数提升小波对图像进行分解,然后对低频子带的重要系数采用特殊处理,对高频子带改变扫描方式来获得最大系数和按频率优先的原则输出系数。同时引用最小输出位、最大值表思想,具有节省索引的时间、节省内存、计算速度快,编码、解码简单的特点。实验结果表明了该算法在相同的比特率下(特别在低比特率下)得到的重构图像的PSNR值高于原算法且缩短编解码时间,是一种有效的快速图像压缩算法。In view of the problems of complicated convolution process of wavelet transform, repeated calculations, a large number of memories, and unconsidered human visual special of SPIHT algorithm, a new image compression algorithm based on integer lifting wavelet transform and improved SPIHT is proposed. At first, image is decomposed by using 9 - 7 tap integer lifting wavelet. Secondly low frequency sub - image significant wavelet coefficients are specially treated. Scanning mode of high frequency ones are changed to obtain the biggest coefficient and according to the frequency - priority to export the coefficients. Meanwhile, due to introducing the idea of minimum exported bit and max value table, the algorithm has the advantages of saving time of index, economical memory, fast computation and simple encoding（ or decoding）. Experiments demonstrate that the PSNR value is higher and time of encoding （or decoding） is less than that of the original SPIHT at the same bit rate（specially at low bit rate）. It is an effective fast image compression method.

关 键 词：多级树集合分裂算法 整数提升小波 图像压缩 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论]