Reduced-reference video quality metric based on edge information

In multimedia transmission, it is important to rely on an objective quality metric which accurately represents the subjective quality of processed images and video sequences. Reduced-reference metrics make use of side-information that is transmitted to the receiver for estimating the quality of the received sequence with low complexity. In this paper, novel Edge-based Dissimilarity Reduced-Reference video quality metric (EDIRR) is proposed. The metric is evaluated by finding the dissimilarity between the edge information of original and distorted sequences. The edge degradation can be detected in this manner as perceived video quality is highly associated with edge structural. In this paper, the aim is to construct a novel RR video quality metric based on edge dissimilarity for video quality assessment. The proposed metric is derived from the motivation that human perception understands an image mainly according to its low-level features, specifically the edges, which are a measure of the significance of a local structure. From the results obtained, there is a moderate positive correlation between the proposed metric score with the subjective scores in the overall observation but with correlation for tested sequences with a lower DMOS. EDIRR, with LCC of 0.938, outperforms PSNR and VIFP on wireless distortion induced sequences and the proposed metric, with LCC of 0.988, performs on a par with PSNR, SSIM and VIFP for H.264 compressions distortions.