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    Efficient and accurate set-based registration of time-separated aerial images

    Access Status
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    Authors
    Arandjelovic, O.
    Pham, DucSon
    Venkatesh, S.
    Date
    2015
    Type
    Journal Article
    
    Metadata
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    Citation
    Arandjelovic, O. and Pham, D. and Venkatesh, S. 2015. Efficient and accurate set-based registration of time-separated aerial images. Pattern Recognition. 48 (11): pp. 3466-3476.
    Source Title
    Pattern Recognition
    DOI
    10.1016/j.patcog.2015.04.011
    ISSN
    00313203
    School
    Department of Computing
    URI
    http://hdl.handle.net/20.500.11937/22651
    Collection
    • Curtin Research Publications
    Abstract

    This paper addresses the task of time-separated aerial image registration. The ability to solve this problem accurately and reliably is important for a variety of subsequent image understanding applications. The principal challenge lies in the extent and nature of transient appearance variation that a land area can undergo, such as that caused by the change under illumination conditions, seasonal variations, or the occlusion by non-persistent objects (people, cars). Our work introduces several major novelties (i) unlike previous work on aerial image registration, we approach the problem using a set-based paradigm; (ii) we show how image space local, pair-wise constraints can be used to enforce a globally good registration using a constraints graph structure; (iii) we show how a simple holistic representation derived from raw aerial images can be used as a basic building block of the constraints graph in a manner which achieves both high registration accuracy and speed; (iv) lastly, we introduce a new and, to the best of our knowledge, the only data corpus suitable for the evaluation of set-based aerial image registration algorithms. Using this data set, we demonstrate (i) that the proposed method outperforms the state-of-the-art for pair-wise registration already, achieving greater accuracy and reliability, while at the same time reducing the computational cost of the task and (ii) that the increase in the number of available images in a set consistently reduces the average registration error, with a major difference already for a single additional image.

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