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杨森, 冯全, 杨梅, 李妙祺. 彩色叶片图像去尘算法[J]. 计算机辅助设计与图形学学报, 2016, 28(8): 1224-1231.
引用本文: 杨森, 冯全, 杨梅, 李妙祺. 彩色叶片图像去尘算法[J]. 计算机辅助设计与图形学学报, 2016, 28(8): 1224-1231.
Yang Sen, Feng Quan, Yang Mei, Li Miaoqi. An Algorithm of Dust Removal for Color Leaves Image[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(8): 1224-1231.
Citation: Yang Sen, Feng Quan, Yang Mei, Li Miaoqi. An Algorithm of Dust Removal for Color Leaves Image[J]. Journal of Computer-Aided Design & Computer Graphics, 2016, 28(8): 1224-1231.

彩色叶片图像去尘算法

An Algorithm of Dust Removal for Color Leaves Image

  • 摘要: 针对户外降尘造成叶片图像中颜色失真、细节信息模糊的问题,提出一种基于光学模型的单幅图像的自动去尘算法.首先根据光线在尘土层和空气中的传播方式建立了一种退化模型;然后结合光学反射成像模型和暗元色原理估计出环境光强及传输量2个模型参数;最后在该退化模型的基础上实现叶片图像尘土的快速去除,并用有尘土层的标准色卡和葡萄叶片图像检验算法的有效性.实验结果表明,文中算法对2种图像均有较好的去尘效果,复原后图像的H和S分量与无尘图像的偏离程度得到了明显改善,重现了图像的颜色和清晰度,获得了满意的视觉效果;该算法对不同天气和照明条件、不同品种的葡萄叶片图像均有较好的颜色恢复效果.

     

    Abstract: In order to tackle color distortion and appearance blur of leaf images caused by atmospheric dust, in this paper, an automatic algorithm is proposed of dust removal for a single image, based on an optical model. We construct an image degradation model according to the transmission way of light in the dust layer and atmosphere. The two model parameters, the atmospheric light and transmission map, are then estimated by the optical reflectance imaging model and dark channel prior. Based on the model, we can remove the effect of dust on the image quickly. The images of dusty Color Checker Chart and grape leaves are employed to check the effectiveness of the algorithm. The experimental results show that the high-quality dust-free images can be recovered, with the deviations between the H and S components of them and those of the clean images being significantly reduced. And the algorithm is applicable to the images under various conditions, i.e., weather, illumination and grape varieties.

     

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