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  • Robust Registration of Multispectral Satellite Images Based on Structural and Geometrical Similarity

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    Awrangjeb505950-Accepted.pdf (800.0Kb)
    File version
    Version of Record (VoR)
    Author(s)
    Lv, G
    Chi, Q
    Awrangjeb, M
    Li, J
    Griffith University Author(s)
    Awrangjeb, Mohammad
    Year published
    2021
    Metadata
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    Abstract
    Accurate registration of multispectral satellite images is a challenging task due to the significant and nonlinear radiometric differences between these data. To address this problem, this letter explores the strategy of geometrical similarity between triplets of feature points, and it is combined with the structural similarity between images in a feature-based image registration framework. The underlying principle is that the structural and geometrical similarities generally preserve across the images being registered. In this feature-based image registration framework, a set of control points (CPs) are first detected. Then, ...
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    Accurate registration of multispectral satellite images is a challenging task due to the significant and nonlinear radiometric differences between these data. To address this problem, this letter explores the strategy of geometrical similarity between triplets of feature points, and it is combined with the structural similarity between images in a feature-based image registration framework. The underlying principle is that the structural and geometrical similarities generally preserve across the images being registered. In this feature-based image registration framework, a set of control points (CPs) are first detected. Then, the geometric similarity between triplets of CPs is defined, followed by a ranking operation of these triplets of CPs. The highly ranked triplets are used to estimate a spatial transformation between images. Finally, initial matches obtained by a benchmark registration technique are refined by the estimated transformation. The experimental results demonstrate the great effectiveness of the proposed technique for registering multispectral satellite images.
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    Journal Title
    IEEE Geoscience and Remote Sensing Letters
    DOI
    https://doi.org/10.1109/LGRS.2021.3093502
    Copyright Statement
    © 2021 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.
    Note
    This publication has been entered as an advanced online version in Griffith Research Online.
    Subject
    Artificial intelligence
    Electrical engineering
    Geomatic engineering
    Publication URI
    http://hdl.handle.net/10072/406567
    Collection
    • Journal articles

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