Quality Assessment for Image Coding Based on Matching Pursuit

Valuation of image coding relies on not only the efficiency of the coding, but also the quality of the coded image. We present a new objective quality assessment metric for image coding based on matching pursuit. First of all, we get the characteristics of the most important structure by projecting the reference image onto the base functions from a dictionary using matching pursuit. Secondly, we process the reference image and gain the structure information of the images in the order of importance, projecting the images onto the structural characteristics. Finally the objective quality score is given by comparing the differences of structure information between the reference and coded images. Experimental results show that the proposed approach is well consistent with the subjective quality score.