In combination of the perceiving characteristics of human eyes for salient objects and moving targets, a video quality evaluation method based on time-weighted processing is proposed. Firstly, the quality score of single frame is obtained by using the classical structural similarity algorithm, and then the quality score of each group of pictures (GoP) is weighted to obtain the GoP mass score according to the influence of different types of frame distortions on the video quality in the video. Finally, all GoPs are time-weighted with saliency and temporal perceptual information, and the weights of both are equalized to get the final objective video quality evaluation value. The proposed metric is tested on the LIVE video database. The experimental results show that this method has good consistency with the subjective evaluation results, and the evaluation results are better than the existing classical models.