Studying Of The Method For Image Quality Assessment Model Via HVS

Attending by printing industry, the term of Image Quality come into being early in nature. With the technology of image compression and CODEC booming, and in order to control the transmission of their bit-stream, the term of image quality is given a kind of new degree and challenge. Today the research of Image Quality Assessment has also become one of the basis technologies in the realm of images and information. Taking into account the way humans perceive visual information can be greatly beneficial for this task. To achieve this, it is necessary to understand and model the human visual system, which is also the principal goal of this thesis.In light of this development, optimizing the performance of digital imaging systems with respect to the capture, display,'storage and transmission of visual information is one of the most important challenges in this domain. For instance, quality assessment tools predict subjective ratings, image compression schemes reduce the visibility of introduced artifacts, watermarking schemes hide information more effectively in images, printer half-toning patterns are perceptually optimized and colors rendered more accurately. In all these applications, the limitations of the Human Visual System (HVS) can be exploited to improve the performance from a visual quality point of view. To do this, it is necessary to build computational models of the HVS.This paper analyzed the characters of HVS at first, that included the visual nonlinear, multi-channel and masking effect as well, then constituted a kind of mathematic model to simulate the course that the human visual system proceeds the image information. In the model, original images and distorted images are transformed respectively to the perceptual field, that is, both of them arc processed by the basic visual nonlinear firstly, and with that enter a band pass filter created by the modulate transform function. During the processing of the multi-channel in the HVS model, according to the characteristic of masking, the function of band pass filter is divided into five bands by the varying spatial frequency of initial image. Finally the value comes into being that we gained from the vision pathways, and then given a group of images which have different characters, compared with the Mean Opinion Score (MOS) and the value obtained form all kinds of model above. The result from experiments indicates the fine agreement between the PE and the MOS. At the end of this paper, planning the action I needed to do next and prospecting the future of Image Quality Assessment.