Recent Advances and Challenges in Video Quality Assessment
LI Dingquan, JIANG Tingting and JIANG Ming
(Peking University, Beijing 100871, China)
Video quality assessment (VQA) plays a vital role in the field of video processing, including areas of video acquisition, video filtering in retrieval, video compression, video restoration, and video enhancement. Since VQA has gained much attention in recent years, this paper is to give an up-to-date review of VQA research, as well as to highlight current challenges in this filed. The subjective study and common VQA databases are first reviewed. Then, a survey on the objective VQA methods, including full-reference, reduced-reference, and no-reference VQA, is reported. The last but the most importantly, the key limitations of current research and several challenges in the field of VQA are discussed, which include the impact of video content, the memory effects, the computational efficiency, the personalized video quality prediction, and the quality assessment of newly emerged videos.
databases; perceptual optimization; personalization; video content; VQA