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Cloud Detection Method in GaoFen-2 Multi-spectral Imagery

机译:高分二号多光谱图像云检测方法

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Cloud cover is one of the major factors which affect the application of GaoFen-2 imagery. Cloud detection in GaoFen-2 imagery is fairly difficult due to the lack of enough infrared bands. This paper presents a cloud detection method for GaoFen-2 multi-spectral imagery based on the radiation transmission model. The scattering coefficient of remote sensing image is estimated by using radiation transmission, and then the cloud mask was obtained by combining the geometric and texture features in high-resolution remote sensing images. Experiments on GaoFen-2 multi-spectral images show that the accuracy of cloud detection is above 94.70%. The method proposed in this paper can effectively reduce the influence of highlighted buildings during cloud detection and achieve a high accuracy for GaoFen-2 imagery cloud detection with less bands. In addition, this paper provides an alternative distinction method for the quantitative researches of thick and thin clouds in optical satellite imagery.
机译:云量是影响高分2号影像应用的主要因素之一。由于缺少足够的红外波段,在高分2影像中进行云检测相当困难。提出了一种基于辐射传输模型的高分2号多光谱图像云检测方法。利用辐射透射估计遥感图像的散射系数,然后结合高分辨率遥感图像中的几何和纹理特征获得云掩模。高分2号多光谱图像实验表明,云探测的准确率达到94.70%以上。本文提出的方法可以有效减少高亮建筑物在云检测过程中的影响,并能以较少的频段实现高分2图像云检测的高精度。此外,本文为光学卫星图像中厚云和薄云的定量研究提供了一种替代的区分方法。

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