There are a large number of cloud-covered areas in most unmanned aerial vehicle images and lead to the loss of information in the image and affect image post procession such as image fusion and target identification. Finding the cloud-occluded area in an image is a key step in image processing. Based on the differences of color and texture characteristics between cloud and ground, a cloud detection algorithm for the unmanned aerial vehicle images is proposed. Simulation results show that the proposed algorithm is better than the classical cloud detection algorithms in accuracy rate, false-positive rate, and kappa coefficient.

中文翻译：

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基于色调-饱和度-强度和纹理特征的无人机图像云检测算法

大多数无人机图像中存在大量云层覆盖区域，导致图像中信息丢失，影响图像融合、目标识别等图像后处理。寻找图像中的云遮挡区域是图像处理的关键步骤。基于云与地面颜色和纹理特征的差异，提出了一种无人机图像云检测算法。仿真结果表明，该算法在准确率、误报率、kappa系数等方面均优于经典的云检测算法。