Image quality metric could be utilized to optimize the image compression algorithm and improve the image quality. Perceptual quality metric

based on the foundation of human visual system (HVS)

can be used as a kind of closed connection between subjective assessments and objective assessments and reflects the human's visual sense to the image distortion. In recent years

the visual perception characteristics in relation to image quality closely has been researched thoroughly by means of some new progress in HVS

and a lot of perceptual quality metrics on the still image compression which all sound effectively have been proposed. An almost comprehensive survey of the different application of the visual perception characteristics in perceptual quality metric is presented in this paper

the important factors to predict the image quality accurately and robustly is given and the research achievement is summarized in this field. However

the development of computational HVS models is still in its infancy

and many issues remain to be investigated and solved. First of all

more psychophysical experiments need to be done with natural images for the modeling of more complex phenomena that occur in natural images. Secondly

more psychophysical experiments focus on measurements at the supra threshold also need to be done because quality metrics and compression are often applied above threshold. Finally

HVS models would be expressed by analysis functions with the aid of latest mathematic pay off in order that the general image quality metrics are developed.