Blind determination of quality of JPEG compressed images

Human observers can easily assess the quality of a distorted image even without examining the original image as a reference. In contrast, proper formulation of the problem so that the task of quality assessment of an image can be performed automatically, is a complex task and hence, designing objective No-Reference (NR) quality measurement algorithms is indeed very difficult. Existing approaches identify the degradation from among a set of degradations commonly experienced during image transmission and handling. However, apart from the inadequacy of being unable to indicate the amount of degradation they tend to reflect the overall degradation rather than being sensitive to one kind of degradation. The problem of correctly assessing the level of degradation is crucial since the choice of an appropriate restoration technique is heavily dependent on this. Further, in practical situations, the problem is compounded by the presence of other degradations acting as confounding factors such as noise. The uniqueness of the proposed approach is that it is designed to work well in situations where JPEG compressed images have been subjected to noise. Its performance has been tested through simulations on a large number of images from several popular databases. Results have also been compared with those obtained from subjective tests on the same images.