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基于低通滤波的偏振去雾方法用于去除浓雾

Low-pass filtering based polarimetric dehazing method for dense haze removal.

作者信息

Liang Jian, Ren Liyong, Liang Rongguang

出版信息

Opt Express. 2021 Aug 30;29(18):28178-28189. doi: 10.1364/OE.427629.

Abstract

Polarimetric dehazing method is very promising in enhancing the quality of images captured in the scattering media. However, it is found that the dehazing results calculated by hazy images are very sensitive to the noise, which may cause the method unstable or even invalid. To overcome this drawback and enhance the capability and stability of the polarimetric dehazing method, digital image processing algorithms or bias parameters need to be added into the method, however, they will make the algorithm complex and time consuming. In this paper, using low pass filter to suppress the noise of the hazy images, a novel polarimetric dehazing method is proposed to enhance the visibility of hazy images, especially for dense haze removal. Experimental results demonstrate that this method is totally automatic and very effective in dense haze processing. This method may have great potential usage in many applications, such as optical surveillance, underwater imaging, and bio-tissue imaging, etc.

摘要

偏振去雾方法在提高散射介质中拍摄图像的质量方面非常有前景。然而,发现由模糊图像计算出的去雾结果对噪声非常敏感,这可能导致该方法不稳定甚至无效。为了克服这一缺点并提高偏振去雾方法的性能和稳定性,需要在该方法中添加数字图像处理算法或偏差参数,然而,这会使算法变得复杂且耗时。本文通过使用低通滤波器抑制模糊图像的噪声,提出了一种新颖的偏振去雾方法来提高模糊图像的能见度,特别是用于去除浓雾。实验结果表明,该方法完全自动化,在浓雾处理中非常有效。该方法在许多应用中可能具有巨大的潜在用途,如光学监视、水下成像和生物组织成像等。

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