Fog image reconstruction using target and atmospheric polarization information

Combining the difference between target polarization information and atmospheric polarization information, an image reconstruction method based on the polarization information of target and atmosphere was proposed. Int this method, firstly, the atmospheric light image and target light image are separated from the light intensity image, the atmospheric light polarization information and target light polarization information are analyzed respectively, and the polarization defogging model is constructed. Secondly, the Gaussian filtering method fused with image gradient information is used to estimate the atmospheric light intensity and target light intensity, the atmospheric light polarization degree and target light polarization degree are calculated respectively.Then, the threshold segmentation method of 3σ rule is used to estimate the atmospheric light intensity at the infinite distance in the atmospheric light image space and finally the target image can be reconstructed. Field experiments were carried out under different weather conditions.The experimental results show that the method proposed can recover the target information well in fog, rain and snow weathers, and the entropy of reconstructed image increases by about 40%, the standard deviation of gray level increases by about 90% and the average gradient and edge strength increase by 3 times.