This paper proposes a Video Quality Assessment （VQA） method based on video-content perception by analyzing the influence of video content， transmission delay， and encoding and decoding distortion characteristics on the VQA， combined with human visual system characteristics and its mathematical model. In this method， the video contents are described by the texture complexity， local contrast， temporal information of video frame image， and their visual perception. Thus， the video contents perception model can be built， which allows for investigating the influence of the video content and their visual perception on VQA. The relationship between the bit rate and video quality is discussed， whose relationship models are built， to study the impact of the bit rate of video-on-video quality. Subsequently， the VQA model that video quality degradation caused by transmission delay distortion is designed by combining the characteristics of video transmission delay. Finally， the convex optimization method is used to synthesize the above three aspects of models， and a no-reference VQA model considering the video contents， encoding and decoding distortion， transmission delay distortion， and human visual system characteristics， is proposed. The proposed VQA model was tested and verified using the videos from several established video databases and open-source video databases， and its performance was compared with that of 17 existing VQA models. The results showed that the precision Pearson linear and Spearman rank order correlation coefficients of the proposed VQA model reached a minimum of 0.8773 and 0.8336 and a maximum of 0.938 3 and 0.943 8， respectively. This shows that the model has good generalization performance and low complexity. Analyzing the overall efficiency of performance in terms of model accuracy， generalization performance， and complexity， the results show that the proposed model is an excellent VQA model.