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Publications [#322685] of Guillermo Sapiro

Papers Published

  1. Delbracio, M; Sapiro, G, Burst deblurring: Removing camera shake through fourier burst accumulation, Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, vol. 07-12-June-2015 (October, 2015), pp. 2385-2393, IEEE, ISBN 9781467369640 [doi]
    (last updated on 2019/06/18)

    © 2015 IEEE. Numerous recent approaches attempt to remove image blur due to camera shake, either with one or multiple input images, by explicitly solving an inverse and inherently ill-posed deconvolution problem. If the photographer takes a burst of images, a modality available in virtually all modern digital cameras, we show that it is possible to combine them to get a clean sharp version. This is done without explicitly solving any blur estimation and subsequent inverse problem. The proposed algorithm is strikingly simple: it performs a weighted average in the Fourier domain, with weights depending on the Fourier spectrum magnitude. The method's rationale is that camera shake has a random nature and therefore each image in the burst is generally blurred differently. Experiments with real camera data show that the proposed Fourier Burst Accumulation algorithm achieves state-of-the-art results an order of magnitude faster, with simplicity for on-board implementation on camera phones.
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