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    • 39-Issue 1
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    Progressive Refinement Imaging

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    Date
    2020
    Author
    Kluge, M.
    Weyrich, T.
    Kolb, A.
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    Abstract
    This paper presents a novel technique for progressive online integration of uncalibrated image sequences with substantial geometric and/or photometric discrepancies into a single, geometrically and photometrically consistent image. Our approach can handle large sets of images, acquired from a nearly planar or infinitely distant scene at different resolutions in object domain and under variable local or global illumination conditions. It allows for efficient user guidance as its progressive nature provides a valid and consistent reconstruction at any moment during the online refinement process.Our approach avoids global optimization techniques, as commonly used in the field of image refinement, and progressively incorporates new imagery into a dynamically extendable and memory‐efficient Laplacian pyramid. Our image registration process includes a coarse homography and a local refinement stage using optical flow. Photometric consistency is achieved by retaining the photometric intensities given in a reference image, while it is being refined. Globally blurred imagery and local geometric inconsistencies due to, e.g. motion are detected and removed prior to image fusion.We demonstrate the quality and robustness of our approach using several image and video sequences, including handheld acquisition with mobile phones and zooming sequences with consumer cameras.
    BibTeX
    @article {10.1111:cgf.13808,
    journal = {Computer Graphics Forum},
    title = {{Progressive Refinement Imaging}},
    author = {Kluge, M. and Weyrich, T. and Kolb, A.},
    year = {2020},
    publisher = {© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13808}
    }
    URI
    https://doi.org/10.1111/cgf.13808
    https://diglib.eg.org:443/handle/10.1111/cgf13808
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA