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Hue-saturation-intensity and texture feature-based cloud detection algorithm for unmanned aerial vehicle images

机译:基于Hue饱和度和纹理特征的无人空中车辆图像的云检测算法

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摘要

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.
机译:大多数无人驾驶飞行器图像中有大量云覆盖区域,并导致图像中的信息丢失,并影响图像融合和目标识别的图像后处理。 在图像中找到云闭塞区域是图像处理的关键步骤。 基于云与地之间的颜色和质地特性的差异,提出了一种无人驾驶飞行器图像的云检测算法。 仿真结果表明,该算法优于精度率,假阳性率和κ系数的经典云检测算法。

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