Full-reference image quality assessment by combining global and local distortion measures

Abstract

Full-reference image quality assessment (FR-IQA) techniques compare a reference and a distorted/test image and predict the perceptual quality of the test image in terms of an objective score. Evaluation of FR-IQA techniques is carried out by comparing the objective score with the image's subjective score obtained through human observer ratings. The goal of an observer is to rate the distortion present in the test images. The goal oriented tasks are processed by the human visual system (HVS) through top-down processing which actively searches for local distortions driven by the goal. Therefore local distortion measurement is important for the top-down processing. Simultaneous bottom-up processing also takes place signifying spontaneous visual functions in the HVS. To account for this, global perceptual features can be used. Therefore, we hypothesize that the objective score for an image can be derived from the combination of local and global distortion measures calculated from the reference and test images. We calculate the local distortion by measuring the local correlation differences from the gradient and contrast information. For global distortion, dissimilarity of the saliency maps computed from a bottom-up model of saliency is used. Experimental analysis conducted in six benchmark databases suggest the effectiveness of the proposed approach.