The invention discloses a no-reference image quality evaluation method based on deep forest classification, comprising: step 1, image classification; step 2, extracting the color quality feature of the image; step 3, extracting the texture quality feature of the image; step 4, using In the deep forest classification model, the decision tree extracts different features, simulates the difference in perception of image quality by different people, and constructs a deep forest classification model to classify image quality, including multi-granularity scanning forest and cascading forest; step 5, based on image quality Features and their category labels, train the deep forest classification model, and obtain the probability that the test image belongs to different categories, that is, the statistical information of the subjective evaluation results of the image quality by different people; step 6, set the quality anchor, and combine the images belonging to different categories The probability of taking into account the differences in the subjective evaluation process to obtain the final image quality score; the no-reference image quality evaluation method described in the present invention uses a deep forest to simulate the difference in image quality cognition of different people, thereby giving an image The quality evaluation results have important theoretical significance and practical value.