Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2419
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dc.contributor.authorPaul, S-
dc.contributor.authorDurgam, U K-
dc.contributor.authorPati, U C-
dc.date.accessioned2016-01-01T05:10:08Z-
dc.date.available2016-01-01T05:10:08Z-
dc.date.issued2015-12-
dc.identifier.citation2015 Third International Conference on Image Information Processing (ICIIP -2015), Waknaghat, Himachal Pradesh, India, 21 - 24 Dec 2015en_US
dc.identifier.urihttp://hdl.handle.net/2080/2419-
dc.descriptionCopyright belongs to proceeding publisheren_US
dc.description.abstractEnhanced Thematic Mapper is a eight-band multispectral sensor in LANDSAT satellite capable of providing high resolution images. These remote sensing images have a wide range of applications in agriculture, deforestation, land cover, volcanic flow activity monitoring etc. All these applications require very accurate image registration. But, automatic registration of these images is still a vital challenge as the images have significant translation, rotation, illumination and scaling differences. Scale invariant feature transform (SIFT) is capable of extracting invariant features from image pairs and it has its own descriptor to reliably match the corresponding features. In this paper, an automatic feature based image registration is proposed using scale invariant feature transform with a reliable matching technique to increase the number of correct matched features between image pairs. At first, SIFT based feature matching is implemented with cross matching process to remove the most of the outliers. Then, fine matched features are obtained by using RANSAC algorithm. Finally, simulation results represent the effectiveness of the proposed method.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectAutomatic image registrationen_US
dc.subjectScale invariant feature transformen_US
dc.subjectAffine transformationen_US
dc.subjectRandom sample consensusen_US
dc.titleLANDSAT Enhanced Thematic Mapper Plus Image Registration using SIFTen_US
dc.typeArticleen_US
Appears in Collections:Conference Papers

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