For most traditional defogging algorithms,there are problems such as color imbalance and low visibility after processing images.In this paper,a bilateral filtering transmittance optimization algorithm based on fog line priori is proposed.Firstly,the pixels are clustered into fog lines in RGB space,and the adaptive module is introduced to predict the atmospheric light value.Secondly,the transmittance of the image is preliminarily optimized according to the combination of atmospheric scattering model with context regularization.At the same time,the transmittance is corrected based on the minimum channel,which makes the transmittance map smoother and prevents the transmittance difference between adjacent depth-of-field areas from being too large.Then,the transmittance is optimized for the second time through bilateral filtering to make it more accurate.Moreover,the atmospheric light value and transmittance are input into the atmospheric scattering model for defogging to obtain a clear image.Finally,the defogged image is color-enhanced to improve the color authenticity and brightness of the image.The experimental results show that this method improves the subjective visual effect to the human eye.This method has significant advantages in the objective evaluation indicators such as Structural Similarity (SSIM),Peak Signal-to-Noise Ratio (PSNR),corner detection number,Universal Quality Index (UQI),Natural Image Quality Evaluator (NIQE) and processing time.