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Erschienen in:
2018 | OriginalPaper | Buchkapitel
An Improved Cloud Detection Method of Optical Remote Sensing Image
verfasst von : Yang Gao, Hao-tian Zhou, Liang Chen
Erschienen in: Signal and Information Processing, Networking and Computers
Verlag: Springer Singapore
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Abstract
The effect of cloud cover on the quality of remote sensing data becomes an unavoidable problem when dealing with a large amount of remote sensing data obtained from satellite sensors. As an important meteorological element, cloud plays a vital role in all areas of atmospheric science. In this paper, we propose a cloud detection method based on multi-feature hierarchical judgement. First, the gray histogram of the object to be interpreted is extracted and the histogram is intercepted to remove the singular value. Then, five types of feature are employed in feature extraction. After that, the objects to be interpreted is divided into single type and mixed type, and mixed type can be further divided into certain mixed type and uncertain type. Finally, threshold method and support vector machine(SVM) are employed to classify these types. Experiment has shown good performance of the proposed method.