Aiming at the problem of color over-saturation and color cast in the process of defogging, an image defogging algorithm based on YUV color model and guided filtering is proposed. Firstly, the brightness component of the fog image is separated, and the atmospheric veil is refined by combining Laplace sharpening operator and guided filtering to obtain the accurate transmittance, and then the sky area is corrected. Secondly, the dense fog area is located according to the intensity information of the atmospheric veil, and the average value in this area is used as the estimation of airlight. Finally, the chromaticity component is compensated to restore the color saturation of the real scene. The experimental results show that the edge intensity and color fidelity of the image after defogging are greatly improved, and the objective evaluation parameters of information entropy, average gradient and standard deviation are better than the current mainstream algorithms. The proposed algorithm demonstrates that the effect of defogging is remarkable, which can meet the requirements of image visibility and detail clarity.