A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY

Identification of clouds in optical images is often a necessary step toward their use. However, aimed at the cloud detection methods used on GF-1 is relatively less. In order to meet the requirement of accurate cloud detection in GF-1 WFV imagery, a new method based on the combination of band operat...

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Main Authors: L. L. Jia, X. Q. Wang
Format: Article
Language:English
Published: Copernicus Publications 2017-09-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1197/2017/isprs-archives-XLII-2-W7-1197-2017.pdf
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author L. L. Jia
X. Q. Wang
author_facet L. L. Jia
X. Q. Wang
author_sort L. L. Jia
collection DOAJ
description Identification of clouds in optical images is often a necessary step toward their use. However, aimed at the cloud detection methods used on GF-1 is relatively less. In order to meet the requirement of accurate cloud detection in GF-1 WFV imagery, a new method based on the combination of band operation and spatial texture feature (BOTF) is proposed in this paper. First of all, the BOTF algorithm minimize interference of highlight surface and cloud regions by the band operation, and then distinguish between cloud area and non-cloud area with spatial texture feature. Finally, the cloud mask can be acquired by threshold segmentation method. The method was validated using scenes. The results indicate that the BOTF performs well under normal conditions, and the average overall accuracy of BOTF cloud detection is better than 90 %. The proposed method can meet the needs of routine work.
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spelling doaj.art-7ee0a41c2f73499caabdc91f76006c8e2022-12-21T17:42:49ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-09-01XLII-2-W71197120110.5194/isprs-archives-XLII-2-W7-1197-2017A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERYL. L. Jia0X. Q. Wang1Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Spatial Information Research Center of Fujian Province, Fuzhou University, ChinaKey Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education, Spatial Information Research Center of Fujian Province, Fuzhou University, ChinaIdentification of clouds in optical images is often a necessary step toward their use. However, aimed at the cloud detection methods used on GF-1 is relatively less. In order to meet the requirement of accurate cloud detection in GF-1 WFV imagery, a new method based on the combination of band operation and spatial texture feature (BOTF) is proposed in this paper. First of all, the BOTF algorithm minimize interference of highlight surface and cloud regions by the band operation, and then distinguish between cloud area and non-cloud area with spatial texture feature. Finally, the cloud mask can be acquired by threshold segmentation method. The method was validated using scenes. The results indicate that the BOTF performs well under normal conditions, and the average overall accuracy of BOTF cloud detection is better than 90 %. The proposed method can meet the needs of routine work.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1197/2017/isprs-archives-XLII-2-W7-1197-2017.pdf
spellingShingle L. L. Jia
X. Q. Wang
A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY
title_full A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY
title_fullStr A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY
title_full_unstemmed A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY
title_short A SIMPLE CLOUD DETECTION METHOD FOR GF-1 WFV IMAGERY
title_sort simple cloud detection method for gf 1 wfv imagery
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/1197/2017/isprs-archives-XLII-2-W7-1197-2017.pdf
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