Research Papers

Swarm intelligence and fractals in dual-pol synthetic aperture radar image change detection

[+] Author Affiliations
Hossein Aghababaee

University of Tehran, College of Engineering, Department of Surveying and Engineering, Tehran, Iran

Yu-Chang Tzeng

National United University, Department of Electronic Engineering, Miao-Li, Taiwan

Jalal Amini

University of Tehran, College of Engineering, Department of Surveying and Engineering, Tehran, Iran

J. Appl. Remote Sens. 6(1), 063596 (Oct 09, 2012). doi:10.1117/1.JRS.6.063596
History: Received March 7, 2012; Revised September 11, 2012; Accepted September 17, 2012
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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.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Hossein Aghababaee ; Yu-Chang Tzeng and Jalal Amini
"Swarm intelligence and fractals in dual-pol synthetic aperture radar image change detection", J. Appl. Remote Sens. 6(1), 063596 (Oct 09, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063596


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