Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/2830
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dc.contributor.authorPaul, Sourabh-
dc.contributor.authorPati, Umesh C-
dc.date.accessioned2017-12-28T05:55:05Z-
dc.date.available2017-12-28T05:55:05Z-
dc.date.issued2017-12-
dc.identifier.citation14th IEEE India Council International Conference (INDICON) 2017, IIT Roorkee, Roorkee, India, 15 - 17 December, 2017en_US
dc.identifier.urihttp://hdl.handle.net/2080/2830-
dc.descriptionCopyright of this document belongs to proceedings publisher.en_US
dc.description.abstractAn Improved Anisotropic Gaussian-Scale Invariant Feature Transform (IAG-SIFT) algorithm is proposed to register the Synthetic Aperture Radar (SAR) images. The standard SIFT algorithm generates isotropic Gaussian scale space which blurs lots of details in the image. The Anisotropic Scale Space (ASS) can preserve more details than the isotropic one. However, in many SAR registration methods, the gradient calculation of the ASS is performed by using the simple differential equation which is not appropriate for SAR images. As the SAR images contain multiplicative speckle noise, simple difference operation is not suitable for gradient calculation. It can reduce the number of correct matches in SAR image registration. So, in this paper, a Gaussian-Gamma-Shaped Bi-Window (GGS-BW) is used for ratio based gradient computation which is very effective for SAR images. The proposed IAG-SIFT method significantly improves the matching performance between the SAR images. The Experimental results show the effectiveness of proposed IAGSIFT algorithm in SAR image registration.en_US
dc.subjectSynthetic Aperture Radar (SAR)en_US
dc.subjectImproved Anisotropic Gaussian-Scale Invariant Feature Transform (IAGSIFT)en_US
dc.subjectGaussian-Gamma-Shaped Bi-Window (GGS-BW)en_US
dc.titleSAR Image Registration Using An Improved Anisotropic Gaussian-SIFT Algorithmen_US
dc.typeArticleen_US
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