Efficient Method for High Quality Removal of Non-uniform Blur in Wavelet Domain

Tao Yue1,2, Jinli Suo1, Cao Xun2, Qionghai Dai1

1Deptartment of Automation, Tsinghua University

2School of Electronic Science and Technology, Nanjing University
Diagram of the non-uniform deconvolution in wavelet domain

Abstract

This paper presents a novel nonuniform deblurring approach which defines the blur model and calculates regularized nonuniform deconvolution in the wavelet domain to achieve high efficiency and high accuracy simultaneously. Targeting for high computation efficiency, we derive a wavelet-domain hierarchical blur model, which can be calculated efficiently by exploiting the sparsity property of natural images in the wavelet domain. Correspondingly, the blur model is incorporated into a multilayer framework and at each layer, spatially varying step sizes are introduced to further accelerate the convergence of the algorithm. In addition to the efficiency advantages, the proposed approach deals with intensely nonuniform blur with high accuracy due to the intrinsic tight support-ness of wavelet basis. We conduct a series of experiments and comparisons to validate the efficiency and effectiveness of our algorithm.

Results

Results of Our Wavelet Deconvolution Method

Bibtex

@inproceedings{yue2016wave,
  title={Efficient Method for High Quality Removal of Non-uniform Blur in Wavelet Domain},
  author={Yue, Tao and Suo, Jinli and Xun Cao and Dai, Qionghai},
  booktitle={IEEE Transactions on Circuits and Systems for Video Technology},
  year={2016},
  organization={IEEE}
}

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