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A Fast Blind Spatially-Varying Motion Deblurring Algorithm with Camera Poses Estimation

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Computer Vision – ACCV 2016 (ACCV 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10113))

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Abstract

Most existing non-uniform deblurring algorithms model the blurry image as a weighted summation of several sharp images which are warped by one latent image with different homographies. These algorithms usually suffer from high computational cost due to the huge number of homographies to be considered. In order to solve this problem, we introduce a novel single image deblurring algorithm to remove the spatially-varying blur. Since the real motion blur kernel is very sparse, in this paper we first estimate a feasible active set of homographies which may hold large weights in the blur kernel and then compute the corresponding weights on these homographies to reconstruct the blur kernel. Since the size of the active set is quite small, the deblurring algorithm will become much faster. Experiment results show that the proposed algorithm can effectively and efficiently remove the non-uniform blur caused by camera shake.

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Author information

Authors and Affiliations

  1. Research Center for Smart Vehicles, Toyota Technological Institute, Nagoya, Japan

    Yuquan Xu & Seiichi Mita

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Silong Peng

Authors
  1. Yuquan Xu
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  2. Seiichi Mita
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  3. Silong Peng
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Corresponding author

Correspondence to Yuquan Xu .

Editor information

Editors and Affiliations

  1. National Tsing Hua University, Hsinchu, Taiwan

    Shang-Hong Lai

  2. Graz University of Technology, Graz, Austria

    Vincent Lepetit

  3. Drexel University, Philadelphia, Pennsylvania, USA

    Ko Nishino

  4. The University of Tokyo , Tokyo, Japan

    Yoichi Sato

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Xu, Y., Mita, S., Peng, S. (2017). A Fast Blind Spatially-Varying Motion Deblurring Algorithm with Camera Poses Estimation. In: Lai, SH., Lepetit, V., Nishino, K., Sato, Y. (eds) Computer Vision – ACCV 2016. ACCV 2016. Lecture Notes in Computer Science(), vol 10113. Springer, Cham. https://doi.org/10.1007/978-3-319-54187-7_11

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  • DOI: https://doi.org/10.1007/978-3-319-54187-7_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-54186-0

  • Online ISBN: 978-3-319-54187-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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