激光与光电子学进展, 2017, 54 (4): 041002, 网络出版: 2017-04-19   

基于Retinex理论和暗通道先验的夜间图像去雾算法 下载: 1224次

Nighttime Image Defogging Based on the Theory of Retinex and Dark Channel Prior
作者单位
天津大学电子信息工程学院, 天津 300072
摘要
夜间图像去雾对夜间场景中的视频监控、目标识别等有重要应用价值。目前夜间图像去雾研究较少,且处理结果存在失真度高、细节模糊、稳健性差等缺点。针对以上情况,结合大气散射模型和夜间雾天图像成像特点,提出基于Retinex理论和暗通道先验的去雾算法。首先,根据Retinex理论求得夜间场景的有雾入射光图像和有雾反射光图像;其次,利用暗通道先验得到场景的无雾反射光图像;然后,分别根据夜间雾天图像和有雾反射光图像求得光源位置和景深,利用相机成像机理求得场景点与各光源的距离之和,进而求得无雾入射光图像;最后,利用Retinex理论复原得到夜间无雾图像。实验结果表明,本文算法不仅能彻底去雾,提高图像对比度,更能大幅度降低去雾过程中的颜色失真。
Abstract
Nighttime image defogging is critical for various applications, such as nighttime video surveillance, and target identification. The existing defogging algorithms for nighttime image have many shortcomings, such as high image distortion, fuzzy detail and poor robustness. In order to solve these problems, a new nighttime image defogging algorithm based on the theory of Retinex and dark channel prior is proposed combining with the characteristics of atmospheric scattering model and nighttime image of fog. Firstly, the incidence image affected by haze and the reflection image affected by haze are obtained based on the theory of Retinex. Then, the clear reflection image is obtained by the dark channel prior. After that, the position of the source and the depth of field are obtained according to the nighttime image of fog and the reflection image affected by haze. The sum of the distances between the spot and the source is obtained by using the camera imaging mechanism, and then the fog-free incident light image is obtained. Finally, the theory of Retinex is used to restore the nighttime clear image. Experimental results show that the proposed algorithm not only defogs completely and enhances the image contrast, but also reduces the color distortion greatly.

杨爱萍, 白煌煌. 基于Retinex理论和暗通道先验的夜间图像去雾算法[J]. 激光与光电子学进展, 2017, 54(4): 041002. Yang Aiping, Bai Huanghuang. Nighttime Image Defogging Based on the Theory of Retinex and Dark Channel Prior[J]. Laser & Optoelectronics Progress, 2017, 54(4): 041002.

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