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In this paper, we propose a method to remove the imaging ambiguity caused by scattering in foggy days based on the utilization of generalized Gaussian function. We use the generalized Gaussian function to simulate the light transmission performance in foggy weather and then obtain its attenuation charateristics for further achieving image defogging results. We also propose a zonal dehazing method according to the distribution of fog in hazed image, thereby further improving the quality of the dehazing image. We use real fog data sets to quantitatively analyze and visualize the results. The simulation results show that the image information entropy and visible edge ratio obtained by the algorithm are improved, which verifies the effectiveness and superiority of the proposed algorithm.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Xiaoxia Du,Kai Liu,Yongqing Huang,Xiaofeng Duan, andQi Wang
"Image dehazing algorithm for image partition optimization based on generalized Gaussian function", Proc. SPIE 13089, Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023), 130890F (25 March 2024); https://doi.org/10.1117/12.3020748
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Xiaoxia Du, Kai Liu, Yongqing Huang, Xiaofeng Duan, Qi Wang, "Image dehazing algorithm for image partition optimization based on generalized Gaussian function," Proc. SPIE 13089, Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023), 130890F (25 March 2024); https://doi.org/10.1117/12.3020748