Aiming at detecting cloud interference over urban area, an algorithm in this research is proposed to detect urban cloud area combining extracting edge information with information entropy, focusing on distinguishing complex surface features accurately to retain intact surface information. Firstly, image edge sharpening is used. Secondly, Canny edge detector and closing operation are applied to extract and strengthen edge features. Thirdly, information entropy extraction is adopted to ensure cloud positional accuracy. Compared with traditional cloud detection methods, this algorithm protects the integrity of urban surface features efficiently, improving the segmentation accuracy. Test results prove the effectiveness of this algorithm.

Date Published: 26 October 2013
PDF: 8 pages
Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 892104 (26 October 2013); doi: 10.1117/12.2033522

Published in SPIE Proceedings Vol. 8921:
MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications
Jinwen Tian; Jie Ma, Editor(s)