结合人类视觉生理结构，以对比度感知特性作为人类视觉系统(HVS)中的主要研究议题，讨论了HVS模型中的设计要点，并在小波变换的多分辨率分析的基础上将包含CSF特点的HVS应用在图象的内部去相关变换和量化过程中，得到一个新的基于人类视觉特点的医学图象压缩模型．通过对CT、MRI图象进行实验表明，在相同的客观条件控制下，该方法能够取得较好的主观视觉质量．在视觉无损即保留几乎所有医学相关信息的条件下，压缩率可以达到16：1，一些应用场合可以达到80：1。

With the promotion and application of digital imaging technology in the medical domain, the amount of medical images grows rapidly. However, the commonly used compression methods cannot acquire satisfying results. Recently, some researchers proposed human vision system (HVS) in the research of image compression. It can visually remove the information in most degree that human vision cannot preserve. In this paper, according to the existed and stated experiments and conclusions, the physical and anatomic structure of human vision is combined and the contrast sensitivity function (CSF) is introduced as the main research issue in HVS, and then the main designing points of HVS model are presented. On the basis of multi-resolution analyses of wavelet transform, the paper applies HVS including the CSF characteristics to the inner correlation-removed transform and quantization in image and proposes a new HVS-based medical image compression model. The experiments are done on the medical images including CT and MRI. The results show that under common objective conditions, the method used in the paper can achieve better subjective visual quality. The compression ratio can reach 16 : 1 if the visually lossless effect is required, i.e. , almost all relevant medical information is reserved. In some occasions, the ratio even reaches 80 : 1.