Wavelength-Dependent Image Defogging Method Based on Mie Scattering of Fog Droplets

Lurui Yang, Kai Liu, Yongqing Huang, X. Duan, Qi Wang, Xiaoxia Du, Xiaodong Chen
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Abstract

In this paper, we present an image defogging method based on the physical process of fog altering the light passing through it, in order to restore information in degraded photos from an optical standpoint. To calculate the fog scattering components quantitatively for different wavelength ranges, we integrate the fog droplet distribution functions with Mie scattering theory. To simulate a real fog scene, the method calculates the environmental visibility by first using a droplet distribution function to determine the corresponding fog droplet size, then calculating the Mie scattering efficiency factors using the obtained droplet size, and finally determining the light attenuation coefficient in different color channels. Experiments reveal that this wavelength-dependent strategy achieves outstanding information entropy and a high proportion of visible edges while also having advantages in retrieving items concealed by dense fog.
基于雾滴Mie散射的波长相关图像去雾方法
本文提出了一种基于雾的物理过程改变通过雾的光的图像去雾方法,以期从光学角度恢复退化照片中的信息。为了定量计算不同波长范围的雾滴散射分量,我们将雾滴分布函数与Mie散射理论相结合。为了模拟真实的雾景,该方法首先利用雾滴分布函数确定相应的雾滴大小,然后利用得到的雾滴大小计算Mie散射效率因子,最后确定不同颜色通道的光衰减系数,以此计算环境能见度。实验表明,这种波长相关的策略在获取被浓雾掩盖的物品时具有优势,同时获得了突出的信息熵和较高的可见边缘比例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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