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Information reconstruction in the cloud removing area based on multi- temporal CHRIS images

机译:基于多时态CHRIS图像的除云区信息重构

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摘要

Thick cloud cover is a very common problem in remote sensing images. Cloud and shadow should be removed, which causes some dark holes in remote sensing images. It is difficult to predict the real value of one pixel covered by thick cloud. Multi-temporal information extracted can be used in the information reconstruction in the cloud covering area. In this study, one new method which is different from the filter processing and spatial interpolation processing is applied in information reconstruction based on multi-temporal CHRIS images. First, the threshold method and MLC are combined to completely identify the area of cloud and shadow. Then this paper utilizes the class information extracted from multi-temporal images and the statistical relationship of the reflectance at the same band in different temporal image. In the end, the whole cloud covering areas in one CHRIS image are repaired and filled by the predicted reflectance values. From the reconstruction result in the cloud covering area, it is concluded that the method in this paper is rather effective to repair the information in the thick cloud covered area based on multi-temporal images.
机译:厚厚的云层是遥感影像中非常普遍的问题。应去除云和阴影,这会在遥感影像中造成一些黑洞。很难预测被厚云覆盖的一个像素的实际值。提取的多时相信息可用于云覆盖区域中的信息重建。在这项研究中,一种不同于滤波处理和空间插值处理的新方法被应用于基于多时态CHRIS图像的信息重建。首先,将阈值方法和MLC相结合以完全识别云和阴影区域。然后利用从多时相图像中提取的类别信息,以及在不同时域图像中相同波段的反射率的统计关系。最后,修复了一张CHRIS图像中的整个云覆盖区域,并通过预测的反射率值进行了填充。从云覆盖区域的重建结果可以得出结论,本文的方法基于多时相图像对厚云覆盖区域的信息进行修复是相当有效的。

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