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

Hossein Aghababaei, Y.C. Tzeng, Jalal Amini

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)


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.
Original languageEnglish
Article number063596
Pages (from-to)1-12
Number of pages12
JournalJournal of applied remote sensing
Issue number1
Publication statusPublished - Oct 2012
Externally publishedYes




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