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  • Multi-spectral remote sensing image registration via spatial relationship analysis on SIFT keypoints

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    85914_1.pdf (539.7Kb)
    Author(s)
    Hasan, Mahmudul
    Jia, Xiuping
    Robles-Kelly, Antonio
    Zhou, Jun
    Pickering, Mark R
    Griffith University Author(s)
    Zhou, Jun
    Year published
    2010
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    Abstract
    Multi-sensor image registration is a challenging task in remote sensing. Considering the fact that multi-sensor devices capture the images at different times, multi-spectral image registration is necessary for data fusion of the images. Several conventional methods for image registration suffer from poor performance due to their sensitivity to scale and intensity variation. The scale invariant feature transform (SIFT) is widely used for image registration and object recognition to address these problems. However, directly applying SIFT to remote sensing image registration often results in a very large number of feature points ...
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    Multi-sensor image registration is a challenging task in remote sensing. Considering the fact that multi-sensor devices capture the images at different times, multi-spectral image registration is necessary for data fusion of the images. Several conventional methods for image registration suffer from poor performance due to their sensitivity to scale and intensity variation. The scale invariant feature transform (SIFT) is widely used for image registration and object recognition to address these problems. However, directly applying SIFT to remote sensing image registration often results in a very large number of feature points or keypoints but a small number of matching points with a high false alarm rate. We argue that this is due to the fact that spatial information is not considered during the SIFT-based matching process. This paper proposes a method to improve SIFT-based matching by taking advantage of neighborhood information. The proposed method generates more correct matching points as the relative structure in different remote sensing images are almost static.
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    Conference Title
    2010 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
    DOI
    https://doi.org/10.1109/IGARSS.2010.5653482
    Copyright Statement
    © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
    Subject
    Image processing
    Publication URI
    http://hdl.handle.net/10072/51669
    Collection
    • Conference outputs

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