用于PACS系统的医学图象量化编码的算法  

A Medical Image Quantization Method Suited for PACS

作　　者：李晴辉[1] 彭承琳[1] 侯文生[1] 罗小刚[1] 

机构地区：[1]重庆大学生物工程学院,重庆400044

出　　处：《重庆大学学报（自然科学版）》2002年第3期78-80,84,共4页Journal of Chongqing University

基　　金：国家级火炬计划项目 (2 0 0 1EB0 0 0 0 0 2 )

摘　　要：图象压缩是PACS系统的重要研究部分。作者研究了二维图象小波分解后系数的统计分布与拉普拉斯分布有很好的一致性 ;同时 ,由于不同幅度的小波系数在图象重构中权重的不同 ,在系数压缩编码时对不同权重的系数采用不同的压缩精度。由此 ,作者提出了一种适用于PACS系统的图象量化编码算法 ,该算法以各小波子带图象小波系数的重要统计特征———样本标准差为量化阈值选择依据 ,精确编码图象重构中权重较大的系数 ,还利用了人眼的频率视觉特性。实验表明 ,本算法具有计算简单、不同编码精度时被量化系数可预见的特点 。Image compression is very important in picture archiving and communication system(PACS). The author studied the statistical distribution of image wavelet subimage coefficients and concluded that the distribution of wavelet subimage coefficients is similar to that of Laplasian distribution. On the other hand, in image reconstruction, the coefficient with different amplitude owns different weight, and different accuracy can be applied to different coefficients according to their different weight. Then, the author has designed a image quantization encoding scheme for PACS. In this scheme, they selected the sample-standard-deviation of coefficients in every subimage as the quantization threshold, and accurately encoded those coefficients with higher weight. Also, this algorithm utilized the visual character of human. The test has proved that the main advantages of this method are the simplicity in computing and predictable encoded coefficients, and a high compression efficiency can obtain too.

关 键 词：PACS 医学图象 量化编码 算法 图象存储 通信系统 小波变换 图象压缩 医学影像诊断技术 

分 类 号：R445[医药卫生—影像医学与核医学]