Single image defogging method based on multi-teacher knowledge distillation

The invention discloses a single image defogging method based on multi-teacher knowledge distillation. The method comprises the following steps: 1, obtaining training set images; 2, establishing a student network model; 3, extracting features of the foggy training image; 4, establishing a total loss function; 5, training the student network model by the foggy training image; and 6, defogging a single image by using the trained student network model. According to the method, the student network model is guided and trained through the EPDN teacher network model and the PSD teacher network model, the feature extraction capability of the student network is effectively improved, the student network model realizes extraction of multi-scale information of the defogged image through encoding and decoding of four scales, the global and local features of the defogged image are effectively fused, and the robustness of the defogged image is improved. And the image defogging effect is improved. 本发明公开了一种基于多教师知识蒸馏的单幅图像去雾方法，