Statistics of natural image distortions
Natural scene statistics (NSS) are an active area of research. Although there exist elegant models for NSS, the statistics of natural image distortions have received little attention. In this paper we study distorted image statistics (DIS) for natural scenes. We demonstrate that each distortion affects the statistics of natural images in a characteristic way and it is possible to parameterize this characteristic. We show that not only are DIS different for different distortions, but by such parametrization it is also possible to build a classifier that can classify a given image into a particular distortion category solely on the basis of DIS, with high accuracy. Applications of such categorization are of considerable scope and include DIS-based quality assessment and blind image distortion correction.