Single-Image Blind Deblurring for Non-uniform Camera-Shake Blur

  • Yuquan Xu
  • Lu Wang
  • Xiyuan Hu
  • Silong Peng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7726)


In this paper we address the problem of estimating latent sharp image and unknown blur kernel from a single motion-blurred image. The blur results from camera shake and is spatially variant. Meanwhile, the blur kernel of motion has three degrees of freedom, i.e., translations and in-plane rotation. In order to solve this problem, we first analyzed the homography blur model for the non-uniform camera-shake blur. We simplified the model to 3-dimensional camera motion which can be accelerated by exploiting the fast Fourier transform to process subsequent image deconvolution. We then proposed an effective method to handle the blind image-deblurring problem by the image decomposition, which does not need to segment the image into local subregions under the assumption of spatially invariant blur. Experimental results on both synthetic and real blurred images show that the presented approach can successfully remove various kinds of blur.


Camera Motion Latent Image Motion Blur Blind Deconvolution Blur Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yuquan Xu
    • 1
  • Lu Wang
    • 1
  • Xiyuan Hu
    • 1
  • Silong Peng
    • 1
  1. 1.Institute of AutomationChinese Academy of SciencesBeijingP.R. China

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