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    • 28-Issue 2
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    Deblurring by Matching

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    v28i2pp619-628.pdf (1.193Mb)
    Date
    2009
    Author
    Ancuti, Cosmin
    Ancuti, Codruta Orniana
    Bekaert, Philippe
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    Abstract
    Restoration of the photographs damaged by the camera shake is a challenging task that manifested increasing attention in the recent period. Despite of the important progress of the blind deconvolution techniques, due to the ill-posed nature of the problem, the finest details of the kernel blur cannot be recovered entirely. Moreover, the additional constraints and prior assumptions make these approaches to be relative limited.In this paper we introduce a novel technique that removes the undesired blur artifacts from photographs taken by hand-held digital cameras. Our approach is based on the observation that in general several consecutive photographs taken by the users share image regions that project the same scene content. Therefore, we took advantage of additional sharp photographs of the same scene. Based on several invariant local feature points, filtered from the given blurred/non-blurred images, our approach matches the keypoints and estimates the blur kernel using additional statistical constraints.We also present a simple deconvolution technique that preserves edges while minimizing the ringing artifacts in the restored latent image. The experimental results prove that our technique is able to infer accurately the blur kernel while reducing significantly the artifacts of the spoilt images.
    BibTeX
    @article {10.1111:j.1467-8659.2009.01402.x,
    journal = {Computer Graphics Forum},
    title = {{Deblurring by Matching}},
    author = {Ancuti, Cosmin and Ancuti, Codruta Orniana and Bekaert, Philippe},
    year = {2009},
    publisher = {The Eurographics Association and Blackwell Publishing Ltd},
    ISSN = {1467-8659},
    DOI = {10.1111/j.1467-8659.2009.01402.x}
    }
    URI
    http://dx.doi.org/10.1111/j.1467-8659.2009.01402.x
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    • 28-Issue 2
    • Full Papers 2009 - CGF 28-Issue 2

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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