关键词: 视频质量评价, 人类视觉系统, 带通滤波, 衰减权函数

Abstract: For the videos that have fast changing motion scenes, the existing simulation of the human visual system is less effective in quality assessment. Due to the bandpass and masking features of the subjective testers, the objective evaluation model ignores the two temporal features of the Human Visual System (HVS), which leads to the deviation between the subjective and objective evaluation results. To improve the evluation performance of the rapidly changing videos, the visual threshold was determined by using the statistic learning method and the filtering of the HVS was built up. The masking of human eyes was emulated through a new attenuation-weight function. The experimental results demonstrate that the proposed method obtained the best performance when the lost packets rates was lower than 5 percent compared with the Peak Signal-to-Noise Ratio (PSNR) method, the constant-weight evaluation model and the rule evaluation model.With the filter function of the bandpass model, it improved the execution efficiency. In brief, the proposed method not only improves the evaluation performance but also reduces the computational complexity.

Key words: video quality metric, Human Visual System (HVS), bandpass filtering, attenuation-weight function