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A Cloud Detection Algorithm Using Edge Detection and Information Entropy over Urban Area

机译:基于边缘检测和信息熵的城市云检测算法

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Aiming at detecting cloud interference over urban area, an algorithm in this research is proposed to detect urban cloud area combining extracting edge information with information entropy, focusing on distinguishing complex surface features accurately to retain intact surface information. Firstly, image edge sharpening is used. Secondly, Canny edge detector and closing operation are applied to extract and strengthen edge features. Thirdly, information entropy extraction is adopted to ensure cloud positional accuracy. Compared with traditional cloud detection methods, this algorithm protects the integrity of urban surface features efficiently, improving the segmentation accuracy. Test results prove the effectiveness of this algorithm.
机译:为了检测城市地区的云干扰,提出了一种算法,将边缘信息提取与信息熵相结合,重点在于准确区分复杂的表面特征,以保留完整的表面信息,从而对城市云区域进行检测。首先,使用图像边缘锐化。其次,使用Canny边缘检测器和闭合操作来提取和增强边缘特征。第三,采用信息熵提取来保证云的定位精度。与传统的云检测方法相比,该算法有效地保护了城市地表特征的完整性,提高了分割精度。测试结果证明了该算法的有效性。

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