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Open AccessArticle

A Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms

1
Department of Electrotechnics, University of Mascara, Mascara 29000, Algeria
2
RCAM Laboratory, College of Engineering, Djillali Liabes University, Sidi-Bel-Abbes 22000, Algeria
*
Author to whom correspondence should be addressed.
Sensors 2010, 10(9), 8553-8571; https://doi.org/10.3390/s100908553
Received: 15 June 2010 / Revised: 5 September 2010 / Accepted: 8 September 2010 / Published: 14 September 2010
(This article belongs to the Special Issue Image Sensors 2009)
Image registration is a fundamental task used in image processing to match two or more images taken at different times, from different sensors or from different viewpoints. The objective is to find in a huge search space of geometric transformations, an acceptable accurate solution in a reasonable time to provide better registered images. Exhaustive search is computationally expensive and the computational cost increases exponentially with the number of transformation parameters and the size of the data set. In this work, we present an efficient image registration algorithm that uses genetic algorithms within a multi-resolution framework based on the Non-Subsampled Contourlet Transform (NSCT). An adaptable genetic algorithm for registration is adopted in order to minimize the search space. This approach is used within a hybrid scheme applying the two techniques fitness sharing and elitism. Two NSCT based methods are proposed for registration. A comparative study is established between these methods and a wavelet based one. Because the NSCT is a shift-invariant multidirectional transform, the second method is adopted for its search speeding up property. Simulation results clearly show that both proposed techniques are really promising methods for image registration compared to the wavelet approach, while the second technique has led to the best performance results of all. Moreover, to demonstrate the effectiveness of these methods, these registration techniques have been successfully applied to register SPOT, IKONOS and Synthetic Aperture Radar (SAR) images. The algorithm has been shown to work perfectly well for multi-temporal satellite images as well, even in the presence of noise. View Full-Text
Keywords: genetic algorithms; image registration; multi-resolution analysis; nonsubsampled contourlet transform; wavelet transform genetic algorithms; image registration; multi-resolution analysis; nonsubsampled contourlet transform; wavelet transform
MDPI and ACS Style

Meskine, F.; Mezouar, M.C.E.; Taleb, N. A Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms. Sensors 2010, 10, 8553-8571. https://doi.org/10.3390/s100908553

AMA Style

Meskine F, Mezouar MCE, Taleb N. A Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms. Sensors. 2010; 10(9):8553-8571. https://doi.org/10.3390/s100908553

Chicago/Turabian Style

Meskine, Fatiha; Mezouar, Miloud Chikr El; Taleb, Nasreddine. 2010. "A Rigid Image Registration Based on the Nonsubsampled Contourlet Transform and Genetic Algorithms" Sensors 10, no. 9: 8553-8571. https://doi.org/10.3390/s100908553

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