Human visual system is not only highly sensitive to the structural information of the image, but also closely related to the color information. Image quality assessment methods based on structural similarity are mostly implemented without considering color. Aiming at this problem, a new image quality assessment method is proposed. The proposed method first extracts the value, hue and saturation of the color image according to the characteristics of the human visual system, and convolves the value component with the Scharr operator to extract the image value channel edge feature to obtain the edge feature of the intense-changing part of brightness, and simultaneously the hue and saturation are treated as the color feature. Secondly, the method extracts the edge feature of the grayedout image to obtain the edge feature of the slow-changing part of the brightness, and finally fuses the above features to obtain more complete image features so as to establish a color image quality assessment model. A large number of comparative experiments were performed on the LIVE database. The results show that the assessment results of the algorithm are generally more consistent with the subjective assessment results, compared with other widely used image quality assessment algorithms.
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