Statistical Approaches to Quality Assessment for Image Restoration

In this paper, we propose two novel (non- parametric) statistical measures of image and video quality. Both of these are based on the fundamental notion of singular value decomposition, applied to local pixel and higher order information derived from the data. These methods enable measurement of similarity between images, and the measurement of image quality without a reference. A possible derivative application of the latter statistical measure is to optimize parameters of the relevant restoration algorithms being applied.