Multisensor image registration is necessary in many applications of remote sensing imagery, the crucial problem is how to establish the correspondence between the features extracted from the reference and input image. Generally, most existing methods only use feature similarity or intensity similarity. In this paper, a coarse-to-refined method, which combines modified scale invariant feature transform (SIFT) feature similarity in coarse matching and cluster reward algorithm(CRA) in refined matching, is developed. To achieve refined registration, two transformation models are used. The experimental results demonstrate that the proposed method is effective and achieves subpixel registration accuracy.


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    Title :

    A Coarse-to-Refined Matching Method for Multisensor Remote Sensing Image Registration


    Contributors:
    Yan Guo, (author) / Ye Zhang, (author) / Yanfeng Gu, (author) / Weizhi Zhong, (author)


    Publication date :

    2008-12-01


    Size :

    792388 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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