薄雾
散射
水下
极化(电化学)
旋光法
透射率
光学
极化度
计算机科学
图像复原
光散射
物理
漫射天空辐射
计算机视觉
人工智能
图像(数学)
地质学
图像处理
化学
气象学
物理化学
海洋学
作者
Zhao Dong,Daifu Zheng,Yantang Huang,Zhiping Zeng,Canhua Xu,Tingdi Liao
标识
DOI:10.1038/s41598-022-05852-1
摘要
Abstract Existing polarization-based defogging algorithms rely on the polarization degree or polarization angle and are not effective enough in scenes with little polarized light. In this article, a method of image restoration for both haze and underwater scattering environment is proposed. It bases on the general assumption that gray variance and average gradient of a clear image are larger than those of an image in a scattering medium. Firstly, based on the assumption, polarimetric images with the maximum variance ( I best ) and minimum variance ( I worst ) are calculated from the captured four polarization images. Secondly, the transmittance is estimated and used to remove the scattering light from background medium of I best and I worst . Thirdly, two images are fused to form a clear image and the color is also restored. Experimental results show that the proposed method obtains clear restored images both in haze and underwater scattering media. Because it does not rely on the polarization degree or polarization angle, it is more universal and suitable for scenes with little polarized light.
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