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Proceedings Paper

Remote sensing images recognition based on constrained independent component analysis via compressed sensing
Author(s): Jinhui Lan; Yiliang Zeng; Yifang Lu
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Paper Abstract

According to the feature of strong correlation of remote sensing image, a target recognition method based on Constrained Independent Component Analysis (CICA) via Compressed Sensing is put forward to realize the goal of remote sensing image recognition. By using abundance nonnegative restriction and the abundance sum-to-one constraint, an Adaptive Abundance Modeling (AAM) algorithm is proposed to ensure the reliability of the objective function. Then the CS feature space classifier based on Constrained Independent Component Analysis of sparse signal is established, so as to achieve recognition quickly. Experimental results show that the proposed algorithm can obtain more accurate results as high as 90%, and improve the timeliness effectively.

Paper Details

Date Published: 8 June 2012
PDF: 6 pages
Proc. SPIE 8365, Compressive Sensing, 83650X (8 June 2012); doi: 10.1117/12.918828
Show Author Affiliations
Jinhui Lan, Univ. of Science and Technology Beijing (China)
Yiliang Zeng, Univ. of Science and Technology Beijing (China)
Yifang Lu, Univ. of Science and Technology Beijing (China)


Published in SPIE Proceedings Vol. 8365:
Compressive Sensing
Fauzia Ahmad, Editor(s)

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