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Journal of Applied Remote Sensing

Swarm intelligence and fractals in dual-pol synthetic aperture radar image change detection
Author(s): Hossein Aghababaee; Yu-Chang Tzeng; Jalal Amini
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Paper Abstract

We present a novel systematic method for change detection in dual polarimetric (Dual-pol) synthetic aperture radar (SAR) images based on swarm intelligence techniques and fractal geometry. As the two main algorithms of swarm intelligence, ant colony optimization (ACO) and particle swarm optimization (PSO) have great potential in change detection. Additionally, fractal geometry appears to be a highly effective means of characterizing textural features in Dual-pol SAR images. The proposed method exploits fractal images to form a new difference image. Fractal images are computed based on wavelet multiresolution analysis. Moreover, by minimizing an optimal function value in the iteration process, the changes are detected by applying ACO and PSO to the difference image. Experimental results of detecting changes in Dual-pol SAR images reveal that the proposed method is a highly effective and efficient means of change detection in Dual-pol SAR images.

Paper Details

Date Published: 9 October 2012
PDF: 12 pages
J. Appl. Remote Sens. 6(1) 063596 doi: 10.1117/1.JRS.6.063596
Published in: Journal of Applied Remote Sensing Volume 6, Issue 1
Show Author Affiliations
Hossein Aghababaee, Univ. of Tehran (Iran, Islamic Republic of)
Yu-Chang Tzeng, National United Univ. (Taiwan)
Jalal Amini, Univ. of Tehran (Iran, Islamic Republic of)

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