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.