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Cloud automatic detection in high-resolution satellite images based on morphological features
Author(s): Xiang Liu; Jun Ping Shen; Yajun Huang
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Paper Abstract

Cloud cover is one of the main factors affecting the quality of remote sensing images, and cloud detection is the first problem to be solved in remote sensing data production. Therefore, cloud judgment becomes one of the primary tasks and key technologies of remote sensing image processing. The main detection objects include thin cloud, thick cloud and cloud shadow. The main interference factors include snow, Gobi, desert, reflective buildings and other highlights. Firstly, the high reflectance characteristics of clouds are used to analyze the distribution of near-infrared and red bands in multispectral remote sensing images to realize preliminary cloud detection. And then using the detected suspected cloud region, different morphological features to distinguish the cloud from other highlight features, and the higher cloud detection accuracy in high-resolution satellite images is achieved.

Paper Details

Date Published: 3 January 2020
PDF: 8 pages
Proc. SPIE 11373, Eleventh International Conference on Graphics and Image Processing (ICGIP 2019), 113730M (3 January 2020); doi: 10.1117/12.2557221
Show Author Affiliations
Xiang Liu, Beijing PIESAT Information Technology Co., Ltd. (China)
Jun Ping Shen, Beijing PIESAT Information Technology Co., Ltd. (China)
Yajun Huang, Beijing PIESAT Information Technology Co., Ltd (China)


Published in SPIE Proceedings Vol. 11373:
Eleventh International Conference on Graphics and Image Processing (ICGIP 2019)
Zhigeng Pan; Xun Wang, Editor(s)

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