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Change detection from remote sensing images based on fractional integral and improved FLICM
Author(s): Fengping Wang; Weixing Wang; Ting Cao; Weiwei Chen
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Paper Abstract

This paper presents a new change detection method based on fractional integral and improved FLICM clustering. Firstly, the log-ratio operator is applied to obtain the difference image from two registered and corrected remote sensing images; and then, the fractional integral operator is introduced to de-nosing and preserve the edge and texture information of the difference image; Finally, the improved FLICM is carried out to get the change areas, which fully considering the pixel neighborhood information and the spatial distance information of the objective function. Experimental results show that the proposed algorithm has strong ability to suppress noise, and can obtain good detection results.

Paper Details

Date Published: 15 November 2017
PDF: 6 pages
Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060522 (15 November 2017); doi: 10.1117/12.2292656
Show Author Affiliations
Fengping Wang, Chang'an Univ. (China)
Weixing Wang, Chang'an Univ. (China)
Ting Cao, Chang'an Univ. (China)
Weiwei Chen, Chang'an Univ. (China)


Published in SPIE Proceedings Vol. 10605:
LIDAR Imaging Detection and Target Recognition 2017
Yueguang Lv; Weimin Bao; Weibiao Chen; Zelin Shi; Jianzhong Su; Jindong Fei; Wei Gong; Shensheng Han; Weiqi Jin; Jian Yang, Editor(s)

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