The invention provides a single image defogging method based on a generation confrontation network. The method includes the steps of 1, constructing a generator network model, inputting a training sample set subjected to fogging processing into the generator network model, and generating preliminary defogged images imitating fog-free images in a test sample set; 2, constructing a decider network model, inputting the preliminary defogged images into the decider network model, calculating a cost function, and performing the following steps that if a calculation result of the cost function is smaller than a preset defogging threshold value, the input images are judged as the fog-free images of the test sample set, and the generator network model is used as an optimal training model; otherwise, the input images are judged as the preliminary defogged images generated by the generator network model, tensorflow is used for training the generation confrontation network, and step 2 is repeatedly executed; 3, inputting a foggy image set into the optimal training model and outputting images after defogging. The method has the advantages of scientific design, high practicability, simple operation and a great defogging effect.