Polarization image defogging based on dark channel prior principle

WANG Chuning; ZHAO Kaichun

doi:10.37188/OPE.20233123.3474

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Polarization image defogging based on dark channel prior principle

Information Sciences | 更新时间：2023-12-13

- Polarization image defogging based on dark channel prior principle
- Optics and Precision Engineering Vol. 31, Issue 23, Pages: 3474-3481(2023)
- 作者机构：
  
  1.清华大学精密仪器系，北京 100084
- 作者简介：
- 基金信息：
- DOI：10.37188/OPE.20233123.3474
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王楚宁,赵开春.基于暗通道先验原理的偏振图像去雾[J].光学精密工程,2023,31(23):3474-3481.

WANG Chuning,ZHAO Kaichun.Polarization image defogging based on dark channel prior principle[J].Optics and Precision Engineering,2023,31(23):3474-3481.
王楚宁,赵开春.基于暗通道先验原理的偏振图像去雾[J].光学精密工程,2023,31(23):3474-3481. DOI： 10.37188/OPE.20233123.3474.

WANG Chuning,ZHAO Kaichun.Polarization image defogging based on dark channel prior principle[J].Optics and Precision Engineering,2023,31(23):3474-3481. DOI： 10.37188/OPE.20233123.3474.

摘要

雾霾天气下大气粒子对光的散射作用会导致成像质量下降，影响目标探测以及关键信息提取。针对目前偏振去雾算法存在的不足，提出一种基于偏振暗通道的去雾方法。通过4个不同角度的偏振光强解算偏振信息，从而得到任意角度的偏振光强，然后，结合暗通道先验原理定义偏振图像暗通道，从中获取无穷远处大气光强度信息，计算得到大气传输率，最后构建大气散射模型，得到去雾图像。实验结果表明：该方法处理后的去雾图像的灰度方差、平均梯度和图像熵几项评价指标均比原图像显著提高，灰度方差提升了25%，平均梯度提升了30%，图像熵提升了5%。该方法能够有效改善雾霾天气下的图像质量，提高图像清晰度，且图像的细节更为丰富。

Abstract

In hazy weather， the image quality is decreased owing to the scattering effect of atmospheric particles on light， which can affect target detection and key information extraction. In response to the shortcomings of current polarization defogging algorithms， this study proposes a defogging method based on polarization dark channel. First， polarization information is calculated through the polarized light intensity of four different angles， to obtain the polarized light intensity of any angle. Thereafter， based on the dark channel prior principle， the dark channel of the polarized image is defined. The atmospheric light intensity at infinity is obtained， and the atmospheric transmission rate is calculated. Finally， the atmospheric scattering model is constructed to obtain a defogging image. The experimental results demonstrate that the evaluation indicators of grayscale variance， average gradient， and image entropy of the defogged image processed by this method are significantly improved compared to those of the original image. The grayscale variance， average gradient， and image entropy are increased by 25%， 30%， and 5%， respectively. This method can effectively improve the quality and clarity of images in hazy weather and enrich image details.

关键词

偏振图像图像去雾暗通道先验原理

Keywords

polarization imageimage defoggingdark channelprior principle

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