An Automatic Cloud Detection Method for ZY-3 Satellite
Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-image...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Surveying and Mapping Press
2015-03-01
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| Series: | Acta Geodaetica et Cartographica Sinica |
| Subjects: | |
| Online Access: | http://html.rhhz.net/CHXB/html/2015-3-292.htm |
| Summary: | Automatic cloud detection for optical satellite remote sensing images is a significant step in the production system of satellite products. For the browse images cataloged by ZY-3 satellite, the tree discriminate structure is adopted to carry out cloud detection. The image was divided into sub-images and their features were extracted to perform classification between clouds and grounds. However, due to the high complexity of clouds and surfaces and the low resolution of browse images, the traditional classification algorithms based on image features are of great limitations. In view of the problem, a prior enhancement processing to original sub-images before classification was put forward in this paper to widen the texture difference between clouds and surfaces. Afterwards, with the secondary moment and first difference of the images, the feature vectors were extended in multi-scale space, and then the cloud proportion in the image was estimated through comprehensive analysis. The presented cloud detection algorithm has already been applied to the ZY-3 application system project, and the practical experiment results indicate that this algorithm is capable of promoting the accuracy of cloud detection significantly. |
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| ISSN: | 1001-1595 1001-1595 |