Video Quality Assessment Metric Based on Spatio-temporal Motion Information

Abstract

Video quality assessment (VQA) plays an important role in video processing applications, e.g., compression, archiving, restoration, transmission and enhancement. Based on the video content, we design an effective and efficient objective video quality metric. Up to now, many efforts have been made to develop the VQA that take advantages of the various characteristics of human visual system (HVS). Several objective quality assessment metrics have been proposed for VQA, such as mean structural similarity (MSSIM), visual-structural similarity (V-SSIM), motion-based video Integrity evaluation (MOVIE) and so on. However, motion information is of great importance in image processing, which has not been effectively studied and applied in VQA. In our algorithm, it is effectively used. Firstly, the video sequences content is divided into two parts: foreground and background according to its special property. Then the new video quality metric by utilizing the motion vector is established. Finally, the proposed metric is tested on the VQEG FRTV Phase 1 database. From the experimental results, it is concluded that our metric out performs the other state-of-art algorithms.