Spatiotemporal Masking for Objective Video Quality Assessment
Random background and object motion may mask some distortions in video sequence,the masked distortions are ignored by humans and they arent considered when humans assess video quality.The visual masking effect produces a gap between the subjective quality and predicted quality obtained by traditional video quality assessment(VQA)which measures all distortions to predict video quality.This paper proposed a novel spatiotemporal masking model(STMM)consists of spatial and temporal masking coefficients to narrow the gap.The spatial masking coefficient is computed by spatial randomness to count the error score between the subjective and objective score,and the temporal masking coefficient is combined by three parts that fused by eccentricity,magnitude of motion vectors and coherency of object motion to measure the degree of the masking effect.In addition,the proposed model is robust enough to integrate with several best known VQA metrics in the literature.The improvement achieved by utilizing the proposed model is evaluated in the LIVE database,MCL-V database and IVPL database.Experimental results show that the VQA metric based on STMM has a good consistency with the subjective perception and performs better than its original metric.
Video quality assessment Spatiotemporal masking effect Visibility of distortions
Ran He Wen Lu Yu Zhang Xinbo Gao Lihuo He
School of Electronic Engineering,Xidian University,Xian 710071,China
国际会议
广州
英文
309-321
2018-11-23（万方平台首次上网日期，不代表论文的发表时间）