Liang Jian, Ju Haijuan, Ren Liyong, Yang Liming, Liang Rongguang
State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an 710119, China.
James C. Wyant College of Optical Sciences, University of Arizona, 1630 E University Blvd, Tucson, AZ 85721, USA.
Sensors (Basel). 2020 Mar 20;20(6):1729. doi: 10.3390/s20061729.
Polarimetric dehazing methods can significantly enhance the quality of hazy images. However, current methods are not robust enough under different imaging conditions. In this paper, we propose a generalized polarimetric dehazing method based on low-pass filtering in the frequency domain. This method can accurately estimate the polarized state of the scattering light automatically without adjusting bias parameters. Experimental results show the effectiveness and robustness of our proposed method in different hazy weather and scattering underwater environments with different densities. Furthermore, computational efficiency is enhanced more than 70% compared to the polarimetric dehazing method we proposed previously.
偏振去雾方法可以显著提高模糊图像的质量。然而，目前的方法在不同的成像条件下不够鲁棒。在本文中，我们提出了一种基于频域低通滤波的广义偏振去雾方法。该方法无需调整偏置参数即可自动准确估计散射光的偏振状态。实验结果表明，我们提出的方法在不同的雾霾天气和不同密度的水下散射环境中具有有效性和鲁棒性。此外，与我们之前提出的偏振去雾方法相比，计算效率提高了70%以上。
