A hybrid and hierarchical approach to aerial image registration

    Authors

    D. J. Xu;T. Kasparis

    Comments

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    Abbreviated Journal Title

    Int. J. Pattern Recognit. Artif. Intell.

    Keywords

    image registration; optical flow; phase correlation; Gaussian/Laplacian; pyramid; INVARIANT MOMENTS; ALGORITHM; Computer Science, Artificial Intelligence

    Abstract

    This paper proposes a hybrid approach to image registration for inferring the a. ne transformation that best matches a pair of partially overlapping aerial images. The image registration is formulated as a two-stage hybrid approach combining both phase correlation method (PCME) and optical flow equation (OFE) based estimation algorithm in a coarse-to-fine manner. With PCME applied at the highest level of decomposition, the initial a. ne parameter model could be first estimated. Subsequently, the OFE-based estimation algorithm is incorporated into the proposed hybrid approach using a multi-resolution mechanism. PCME is characterized by its insensitivity to large geometric transform between images, which can effectively guide the OFE-based registration. For image pairs under salient brightness variations, we propose a nonlinear image representation that emphasizes common intensity information, suppresses the non-common information between an image pair, and is suitable for the proposed coarse-to-fine hierarchical iterative processing. Experimental results demonstrate the accuracy and efficiency of our proposed approach using different types of aerial images.

    Journal Title

    International Journal of Pattern Recognition and Artificial Intelligence

    Volume

    21

    Issue/Number

    3

    Publication Date

    1-1-2007

    Document Type

    Article

    Language

    English

    First Page

    573

    Last Page

    590

    WOS Identifier

    WOS:000251175500008

    ISSN

    0218-0014

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