Adaptive image defogging algorithm combined with lab space and single-scale Retinex

Aiming at the small transmittance estimate and the Halo effect caused by the sudden change in the depth of field of the dark channel prior algorithm in the large sky area, an image defogging algorithm combined with lab space and single-scale retinex was proposed. Firstly, the RGB image was transferred to the lab space to extract the luminance component, and the edge information of this was extracted by the Canny operator to enrich the details of the restored image. Secondly, the single-scale retinex was used to perform a Gaussian adaptive filtering of the non-edge region to estimate the optimized luminance component, and the “false” defogging image as well as the rough transmittance was obtained. Then, the cross-bilateral filtering was used to eliminate the Halo effect by optimizing the transmittance. Finally, the defogging image was recovered on the basis of the atmospheric scattering model. The experimental results show that the image recovered by this method is clear and smooth overall, and also has a good recovery effect on images with large sky areas.