A new distortion/content-dependent video quality index (DCVQI)
A new video quality index, called the distortion/content-dependent video quality index (DCVQI), is proposed in this paper. The distortion and content effects on video quality assessment are taken into account explicitly in the DCVQI. First, we classify distortions into two types (local and global distortions) with a distortion classification scheme. Then, for a given distortion type, we observe a linear relation model between the perceptual quality and SSIM for a given video clip, and the parameters of the linear model are determined by video contents. These parameters can be obtained through a machine learning process. It is shown by experimental results the proposed DCVQI offers a PLCC (Pearson Linear Correlation Coefficient) value of 0.869 when tested on the LIVE database, which outperforms all state-of-the-art video quality assessment methods, including MOVIE and STMAD.