Opto-Electronic Engineering, Volume. 48, Issue 6, 210040(2021)

Blind image restoration method regularized by hybrid gradient sparse prior

Xu Ningshan1,2, Wang Chen3, Ren Guoqiang1、*, and Huang Yongmei1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    References(22)

    [1] [1] Weiss Y, Freeman W T. What makes a good model of natural images?[C]//Proceedings of 2007 IEEE Conference on Computer Vision and Pattern Recognition, 2007: 1–8.

    [2] [2] Levin A, Weiss Y, Durand F, et al. Understanding and evaluating blind deconvolution algorithms[C]//Proceedings of 2009 IEEE Conference on Computer Vision and Pattern Recognition, 2009: 1964–1971.

    [3] [3] Fergus R, Singh B, Hertzmann A, et al. Removing camera shake from a single photograph[J]. ACM Trans Graph, 2006, 25(3): 787–794.

    [4] [4] Shan Q, Jia J Y, Agarwala A. High-quality motion deblurring from a single image[J]. ACM Trans Graph, 2008, 27(3): 1–10.

    [5] [5] Cho S, Lee S. Fast motion deblurring[J]. ACM Trans Graph, 2009, 28(5): 1–8.

    [6] [6] Levin A, Weiss Y, Durand F, et al. Efficient marginal likelihood optimization in blind deconvolution[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2011: 20–25.

    [7] [7] Xu L, Zheng S C, Jia J Y. Unnatural L0 sparse representation for natural image deblurring[C]//Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013: 1107–1114.

    [8] [8] Wang K, Shen Y, Xiao L, et al. Blind motion deblurring based on fused l0-l1 regularization[C]//Proceedings of the 8th International Conference on Image and Graphics, 2015: 1–10.

    [9] [9] Kotera J, ?roubek F, Milanfar P. Blind deconvolution using alternating maximum a posteriori estimation with heavy-tailed priors[C]//Proceedings of the 15th International Conference on Computer Analysis of Images and Patterns, 2013: 59–66.

    [12] [12] Tao X, Gao H Y, Shen X Y, et al. Scale-recurrent network for deep image deblurring[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018: 8174–8182.

    [13] [13] Yan R M, Shao L. Blind image blur estimation via deep learning[J]. IEEE Trans Image Process, 2016, 25(4): 1910–1921.

    [14] [14] Zhang J W, Pan J S, Ren J, et al. Dynamic scene deblurring using spatially variant recurrent neural networks[C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018: 2521–2529.

    [15] [15] Xu X Y, Pan J S, Zhang Y J, et al. Motion blur kernel estimation via deep learning[J]. IEEE Trans Image Process, 2018, 27(1): 194–205.

    [16] [16] Li Y L, Tofighi M, Geng J Y, et al. Efficient and interpretable deep blind image deblurring via algorithm unrolling[J]. IEEE Trans Comput Imaging, 2020, 6: 666–681.

    [17] [17] Lv X G, Song Y Z, Wang S X, et al. Image restoration with a high-order total variation minimization method[J]. Appl Math Mod, 2013, 37(16–17): 8210–8224.

    [20] [20] Krishnan D, Fergus R. Fast image deconvolution using hyper-laplacian priors[C]//Proceedings of the 22nd International Conference on Neural Information Processing Systems, 2009: 1033–1041.

    [21] [21] Perrone D, Favaro P. Total variation blind deconvolution: the devil is in the details[C]//Proceedings of 2014 IEEE Confe-rence on Computer Vision and Pattern Recognition, 2014: 2909–2916.

    [22] [22] Martin D, Fowlkes C, Tal D, et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics[C]//Proceedings of the Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2001: 416–423.

    [23] [23] Krishnan D, Tay T, Fergus R. Blind deconvolution using a normalized sparsity measure[C]//Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition, 2011: 233–240.

    [24] [24] Hosseini M S, Plataniotis K N. Convolutional deblurring for natural imaging[J]. IEEE Trans Image Process, 2019, 29: 250–264.

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    Xu Ningshan, Wang Chen, Ren Guoqiang, Huang Yongmei. Blind image restoration method regularized by hybrid gradient sparse prior[J]. Opto-Electronic Engineering, 2021, 48(6): 210040

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    Paper Information

    Category: Article

    Received: Jan. 27, 2021

    Accepted: --

    Published Online: Sep. 4, 2021

    The Author Email: Guoqiang Ren (renguoqiang@ioe.ac.cn)

    DOI:10.12086/oee.2021.210040

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