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Proceedings Paper

Bio-inspired anomaly target detection of multi-spectral remote sensing data
Author(s): Min Li; Xuewu Zhang; Xinnan Fan; Zhuo Zhang
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Paper Abstract

Aimed to the limitation of present anomaly detection algorism under clutter background for multi-spectral remote sensing data, especially for the situations of dense spread target and exist different attributive of background objects, a bio-inspired anomaly detection algorithm was proposed. Simulate the information processing and fusion mechanism of fly multi-apertures vision system, multi-level background model was proposed to analysis and describe feature of clutter background. Then the threshold value can be chose adaptively according to the level of background model. The proposed algorithm didn’t need the prior knowledge about anomaly, and avoids the choosing of the background widow size. A fusion mechanism was proposed to fuse the different detection results with different level background model. Simulation experiment validated the effectiveness of proposed method.

Paper Details

Date Published: 26 October 2013
PDF: 7 pages
Proc. SPIE 8921, MIPPR 2013: Remote Sensing Image Processing, Geographic Information Systems, and Other Applications, 89210D (26 October 2013); doi: 10.1117/12.2031228
Show Author Affiliations
Min Li, Hohai Univ. (China)
Xuewu Zhang, Hohai Univ. (China)
Xinnan Fan, Hohai Univ. (China)
Zhuo Zhang, Hohai Univ. (China)


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

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