Research on distortion quality evaluation of computer network shared image based on visual sensitivity

Abstract

Shared image distortion will affect the user's experience, and then damage people's life and entertainment experience. In view of this, this research starts with the evaluation and classification of network shared image distortion quality, improves the shared image distortion quality evaluation algorithm combined with the sensitive characteristics of human vision, and verifies its performance superiority through comparative experiments. The results show that the performance of some improved reference quality evaluation algorithms reaches the highest values, which are 0.7923, 0.3224, 0.7931 and 0.8213, respectively. The improved non-reference quality evaluation algorithm achieves the highest values of positive indicators in the comparison of performance values, which are 0.487 and 0.287, respectively, while the lowest value of negative indicators is 0.902. It can be seen that the improved shared image quality evaluation algorithm conforms to the sensitive characteristics of human eyes, has high computational efficiency and has broad application prospects.