Robust inter-scale non-blind image motion deblurring

  • Authors:

  • Chao Wang;LiFeng Sun;ZhuoYuan Chen;ShiQiang Yang;JianWei Zhang

  • Affiliations:

  • Computer Science, Tsinghua Univ., Tsinghua National Laboratory for Information Science and Technology, Key Laboratory of Media and Networking, MOE-Microsoft, China;Computer Science, Tsinghua Univ., Tsinghua National Laboratory for Information Science and Technology, Key Laboratory of Media and Networking, MOE-Microsoft, China;Computer Science, Tsinghua Univ., Tsinghua National Laboratory for Information Science and Technology, Key Laboratory of Media and Networking, MOE-Microsoft, China;Computer Science, Tsinghua Univ., Tsinghua National Laboratory for Information Science and Technology, Key Laboratory of Media and Networking, MOE-Microsoft, China;Department Informatics, Hamburg Univ., Germany

  • Venue:
  • ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
  • Year:
  • 2009

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Abstract

Kernel estimate errors and image noise are major causes of visual artifacts in image motion deblurring. We propose an inter-scale non-blind image motion deblurring approach that significantly reduces those artifacts. We use Gaussian Scale Mixture Field of Experts (GSM FOE) model as image prior. The inter-scale smoothness constraint is adopted to suppress the ringing artifacts. In each scale, image details are recovered by the residual deconvolution and the cross bilateral filter (CBF). We further propose a std-controlled CBF to denoise the result. The experimental results aremuch better than those of previous methods.