In this paper, we propose a full-reference video quality assessment model, which describe the video structure information based on quaternion singular value decomposition (QSVD). In addition, we fully consider the characteristics of HVS, combined the luminance characteristics, texture detail and spatial location information as a weight. Finally, we enhance the importance of chrominance and consider the blocking effect. The algorithm is tested on the video quality expert group (VQEG) Phase I FR-TV test data set. Experiment results show that new model has good correlation with perceived video quality.
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