The Boosting lifting model was analyzed. A selection criterion for the ratio of the mean square error and the entropy of the image after the defogging, and the different kinds of different defogging algorithms were sort out. According to the set the threshold, the appropriate defogging algorithm was selected as the "extreme best intensifier" from the multiple defogging algorithm. By optimizing the learning rate, the weight of the "optimal enhancer"was updated.A linear combination to construct an optimal fog removal algorithm was exopted was adopted. Experiments show that the algorithm achieves the balance between image contrast and image loss after fog removal. The image contrast is enhanced, the image details are highlighted, and the loss of image information is reduced to the greatest extent.