Spatio-temporal ssim index for video quality assessment

Abstract

An ideal objective metric for video quality assessment (VQA) should achieve consistency between video distortion prediction and psychological perception of human visual system (HVS), and is important in many video processing applications. In general, both spatial distortion and temporal distortion should be carefully considered in the designing of VQA metrics. In this paper, we propose a novel spatio-temporal structural information based video quality metric. Motivated by the fact that pixels in natural videos are highly structured in both spatial domain and temporal domain, we propose to perform structural similarity evaluation in x-y, x-t and y-t dimensions respectively and pooled them adaptively based on local spatio-temporal activities. Experimental results on LIVE database show that such a conceptually simple and computationally efficient algorithm is competitive with state-of-the-art VQA metrics, and is very robust to various types of video distortions.