The UAV is easy to be affected by cloud when it is shooting to the ground. It shielding the ground infor-mation and reducing the image quality. It affecting the extraction of prior information and image pro-cessing. At present, there is no feasible and effective method for cloud concentration of cloud images. Therefore, This paper proposed a cloud concentration classification method based on the quality of cloud images. Based on the analysis of the structure of the image, 6 kinds of feature factors which are sensitive to the quality of the cloud images are extracted, and the feature vectors are constructed. And get the quality assessment model to obtain the quality score. Finally, the mean dif-ference of the Mahalanobis distance between the original image set and the test image is used to obtain the cloud images concentration. In view of the quality assessment model and the cloud concentration classification standard, the real-time test cloud images are used as the test database. The algorithm is veri-fied by three aspects: the subjective and objective consistency of image quality, the accuracy of cloud concentration classification, and the efficiency of algorithm. The experimental results show that the algo-rithm has higher accuracy, better subjective and objective consistency, and the classification of image cloud concentration level is more clear, and the algorithm runs more efficiently. The algorithm can meet the cloud UAV images quality assessment and cloud concentration classification.
Consistency by means of image fractal dimension of the surface fractal dimension is designed and implemented based on fractal theory of image quality assessment method. Classic SSIM algorithm based on research and analysis of the factors affecting the image quality, the quality factor of the fractal, built for the blurred image quality evaluation method. Experiments show that the method of subjective and objective evaluation of the relevance, scientific evaluation of fuzzy image quality.