Visual quality analysis for images degraded by different types of noise

Modern visual quality metrics take into account different peculiarities of the Human Visual System (HVS). One of them is described by the Weber-Fechner law and deals with the different sensitivity to distortions in image fragments with different local mean values (intensity, brightness). We analyze how this property can be incorporated into a metric PSNR-HVS-M. It is shown that some improvement of its performance can be provided. Then, visual quality of color images corrupted by three types of i.i.d. noise (pure additive, pure multiplicative, and signal dependent, Poisson) is analyzed. Experiments with a group of observers are carried out for distorted color images created on the basis of TID2008 database. Several modern HVS-metrics are considered. It is shown that even the best metrics are unable to assess visual quality of distorted images adequately enough. The reasons for this deal with the observer's attention to certain objects in the test images, i.e., with semantic aspects of vision, which are worth taking into account in design of HVS-metrics.