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Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

Senthilnath, J and Kalro, Naveen P and Benediktsson, JA (2014) Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery. In: APPLIED MATHEMATICS AND COMPUTATION, 236 . pp. 546-564.

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Official URL: http://dx.doi.org/10.1016/j.amc.2014.03.070

Abstract

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.

Item Type: Journal Article
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Additional Information: Copyright for this article belongs to the ELSEVIER SCIENCE INC, 360 PARK AVE SOUTH, NEW YORK, NY 10010-1710 USA
Keywords: Multi-sensor image registration; Multi-objective optimization; Genetic Algorithm
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering (Formerly, Aeronautical Engineering)
Date Deposited: 16 Jun 2014 10:29
Last Modified: 16 Jun 2014 10:29
URI: http://eprints.iisc.ernet.in/id/eprint/49242

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