Abstract: In the foggy environment, the image quality is degraded due to scattering of light by atmospheric particles. For the image degradation under haze and other weather conditions, a global image polarization defogging method based on automatic parameter estimation was proposed.Using three polarization images of different angles, the degree of polarization of atmospheric light and atmospheric light at infinity was automatically estimated, and the image after defogging was obtained based on the atmospheric scattering model. The corresponding parameters were calculated from the three RGB color channels, making the algorithm suitable for the color field. Firstly, the dark channel method was used to estimate atmospheric light and transmission at infinity, and the transmission map was optimized by guided filtering. Then the global search method was used to estimate the degree of polarization of atmospheric light based on the non-correlation between atmospheric light and target light.Finally, clear target images were recovered from the atmospheric scattering model and enhanced using logarithmic transformation.This method can get clear defogging images under hazy weather, and in thick fog weather, the information entropy of defogged images is increased by about 21%, the average gradient is increased by about 2 times, and the standard deviation is increased by about 12%. Experimental results show that the proposed method can solve the problem of poor estimation parameters of artificial framing, improve the sharpness and contrast of the restored target image, and can be used for target detection and recognition of color images.