Color correction assessment method based on machine learning

The invention relates to a color correction assessment method based on machine learning. The method comprises the following steps: S1, inputting a reference image and a target image (i.e. a distorted image), employing a full reference image quality assessment method based on image registration to carry out feature extraction on the target image, and obtaining a feature set F1; S2, employing an image redirection assessment method to carry out feature extraction on the target image, and obtaining a feature set F2; S3, integrating the feature set F1 and the feature set F2 to obtain a feature set F of a machine learning algorithm, and obtaining an objective assessment model through learning by the machine learning algorithm and a trisection cross validation method; and S4, employing the objective assessment model to objectively assess the target image, and obtaining a final quality assessment score of the target image. The method can effectively assess the color consistency of images and has high correlation and precision in accordance with subjective perception of users.