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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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|
|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|
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