Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/8531
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dc.contributor.authorSenthilnath, J.-
dc.contributor.authorOmkar, S.N.-
dc.contributor.authorMani, V.-
dc.contributor.authorKalro, N.P.-
dc.contributor.authorDiwakar, P.G.-
dc.date.accessioned2020-03-30T10:22:24Z-
dc.date.available2020-03-30T10:22:24Z-
dc.date.issued2012-
dc.identifier.citationInternational Geoscience and Remote Sensing Symposium (IGARSS), 2012, Vol., , pp.1761-1764en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8531-
dc.description.abstractThis paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient. � 2012 IEEE.en_US
dc.titleMulti-objective Genetic Algorithm for efficient point matching in multi-sensor satellite imageen_US
dc.typeBook chapteren_US
Appears in Collections:2. Conference Papers

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