基于暗通道先验的图像去雾方法研究
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摘要
针对多发性的雾霾天气下获得的图像质量退化问题,雾天退化图像的去雾复原技术引起广泛关注。在充分分析雾天图像特点的前提下,研究暗通道先验算法在图像去雾中的应用并借助Matlab平台实现仿真验证。首先将采集到的雾天图像载入系统,然后使用暗通道先验算法处理图像。实验结果证明,该方法具有良好的去雾效果,处理后的图像不仅更加清晰,同时增强了细节信息,提升了图像的利用价值。
For the problem of image quality degradation obtained from multiple haze days,the defogging and restoration technology of degraded images in fog has attracted extensive attention. On the premise of fully analyzing the image characteristics of fog, the application of dark channel prior algorithm in image defogging is studied, and the simulation verification is realized with the help of Matlab platform. Firstly, the collected foggy images are loaded into the system, and then the dark channel prior algorithm is used to process the images. The experimental results show that this method has better fog removal effect and clearer image, but also enhances the detail information and improves the utilization value of the image.
For the problem of image quality degradation obtained from multiple haze days,the defogging and restoration technology of degraded images in fog has attracted extensive attention. On the premise of fully analyzing the image characteristics of fog, the application of dark channel prior algorithm in image defogging is studied, and the simulation verification is realized with the help of Matlab platform. Firstly, the collected foggy images are loaded into the system, and then the dark channel prior algorithm is used to process the images. The experimental results show that this method has better fog removal effect and clearer image, but also enhances the detail information and improves the utilization value of the image.
引文
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[2]彭耀旺.图像去雾技术的研究[D].成都:电子科技大学,2015.
[3]林笑君,梁凤梅.基于Retinex的一种图像去雾算法[J]电视技术,2013(17):047.
[4]舒婷.基于物理模型与非物理模型的图像去雾霾算法[D].张家界:吉首大学,2015.
[5]Fan G,Zi-Xing C,Bin X,et al.Review and prospect of image dehazing techniques[J].Journal of Computer Applications,2010,30(9):2417-2421.
[6]HE K,SUN J,TANG X.Single image haze remova using dark channel prior[C].Proceedings of IEEE Conference on computer vision and Pattern Recognition,Miami,FL,USA:IEEE Computer Society,2009:1956-1963.
[7]王奕权.图像去雾与图像增强算法研究[D].南京:南京邮电大学,2015.