Image dehazing based on side window box filtering and transmittance correction

Aiming at the problems of color oversaturation phenomenon and inaccurate image initial transmittance estimation in the haze line prior dehazing algorithm, an image dehazing algorithm based on side window box filtering and transmittance correction was proposed. In order to solve the problem of missing edge detailed information caused by inaccurate initial transmittance estimation, firstly the method of the non-local total generalized variation (TGV) regularization was used to estimate the initial transmittance, and the second-order non-local TGV regularized device was used as the regular term to ensure the outliers caused by the noise and ambiguity between image color and depth had robustness. Then, the initial transmittance was optimized by using the edge window filtering algorithm, in this way the texture information and edge information in the image were preserved. Finally, the original image without haze was restored by using the atmospheric scattering model and the multi-angle optimized transmittance. The experimental results show that the proposed algorithm can solve the color oversaturation of the image and the edge detailed texture information loss, and there is no hue shift and halo effect. In the qualitative evaluation, the restored image has a good visual effect, and in the quantitative evaluation, the evaluation indexes of the image after dehazing based on the proposed algorithm are higher than that based on the haze line prior algorithm.