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In this work, we study the visual quality of streaming video and propose a fusion-based video quality assessment (FVQA) index to predict its quality. In the first step, video sequences are grouped according to their content complexity to reduce content diversity within each group. Then, at the second step, several existing video quality assessment methods are fused to provide the final video quality...
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...
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