A Multi-scale Fusion Defogging Algorithm Based on Dark Channel Priors
At the problems of contrast reduction,tone darkening and overexposure when the traditional dark channel prior (DCP)algorithm is used for image defogging,a multi-scale fusion defogging algorithm based on dark channel prior is proposed in this paper. Firstly,the algorithm uses the image enhancement to enhance the dark part details and then uses the threshold segmenta⁃ tion method to separate the similar white background areas. Then,for large white background and other areas,the brightest channel inverse defogging processing and the dark channel guided defogging processing are respectively carried out. The two parts of the im⁃ age after defogging are initially fused,which effectively improves the unapplicability of dark channel priors in large scale highlight⁃ ed areas. Finally,the Laplacian Pyramid multi-exposure fusion method is used to conduct multi-scale pixel-level fusion of the above two images after defogging,the initial fusion image and the image with fog after guiding dark channel processing,to obtain the final defogging effect. The simulation results show that the proposed algorithm can effectively eliminate the distortion caused by the traditional DCP algorithm when processing the large range and high brightness sky area,improve the target edge details,and re⁃ store the real color of the image scene.
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