A haze removal algorithm based on guided coefficient weighted and adaptive image enhancement method

Aiming at the dim and detail information loss problem that occurred in dark channel prior dehazing algorithm, a haze removal algorithm based on guided-coefficient-weighted and adaptive image enhancement method was proposed in this paper. Firstly, in order to efficiently refine the transmission, a sampling and guided-coefficient-weighted method was applied to correct the original guided filter algorithm. Then, the K-means clustering method was adopted to mark the bright and non-bright regions according to the original image. It was used to restrict the range of transmission and atmospheric light, thus the noise can be suppression effectively and the atmospheric light can be well optimized. Finally, the image was restored by the atmospheric scattering model and optimized by the adaptive linear contrast enhancement method. Experimental results demonstrated that the proposed method can not only overcome the problem of image distortion and detail information loss, but also more efficient than conventional dehazing methods.