An Algorithm of Image Dehazing Using Near-Infrared

Cheng Peng; Lan Shiyong; Li Xinsheng; Wu Yuezhou

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An Algorithm of Image Dehazing Using Near-Infrared

更新时间：2023-11-14

- An Algorithm of Image Dehazing Using Near-Infrared
- Advanced Engineering Sciences Vol. 45, Issue Z2, Pages: 155-159(2013)
- 作者机构：
  
  1. 四川大学视觉合成图形图像技术国防重点学科实验室
  2. 四川大学计算机学院
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013，
  
  Published Online：11 March 2013，
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程鹏,兰时勇,李新胜,吴岳洲.基于近红外的图像去雾方法[J].工程科学与技术,2013,45(Z2):155-159.

Cheng Peng, Lan Shiyong, Li Xinsheng, et al. An Algorithm of Image Dehazing Using Near-Infrared. [J]. Advanced Engineering Sciences 45(Z2):155-159(2013)
程鹏,兰时勇,李新胜,吴岳洲.基于近红外的图像去雾方法[J].工程科学与技术,2013,45(Z2):155-159. DOI：

Cheng Peng, Lan Shiyong, Li Xinsheng, et al. An Algorithm of Image Dehazing Using Near-Infrared. [J]. Advanced Engineering Sciences 45(Z2):155-159(2013) DOI：

摘要

中文摘要: 针对雾天可见光图像降质现象，提出一种简单、有效的自动去雾算法。算法充分利用了近红外透雾能力强，可见光图像色彩亮度好的特点。首先利用暗原色先验估计出雾浓度分布，然后根据此分布计算出归一化暗原色图像亮度分布系数，并对其进行双边滤波处理，最后利用该系数将近红外与可见光图像进行融合。实验结果表明，该算法能有效地改善雾天图像质量，且具有广泛的应用前景。

Abstract

Abstract:This paper proposed a novel method for automatic haze removal. The algorithm made the best use of advantages of both NIR and visible light image. First

it estimated the haze density distribution by using dark channel prior. Based on this

then

calculated the normalized luminance distribution coefficient of dark channel image via bilateral filtering. Finally

fusing near-infrared(NIR) and visible light image together. Experiments show that the algorithm can effectively improve the quality of the degraded image and it has broad application prospects.

关键词

近红外图像融合图像去雾滤波

Keywords

near-infraredimage fusionimage dehazingfiltering

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