• Optics and Precision Engineering
  • Vol. 22, Issue 9, 2572 (2014)
YAN Jing-wen1,*, PENG Hong1, LIU Lei2, JIN Guang3, and ZHONG Xing3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • show less
    DOI: 10.3788/ope.20142209.2572 Cite this Article
    YAN Jing-wen, PENG Hong, LIU Lei, JIN Guang, ZHONG Xing. Remote sensing image restoration based on zero-norm regularized kernel estimation[J]. Optics and Precision Engineering, 2014, 22(9): 2572 Copy Citation Text show less
    References

    [1] XU L, ZHENG S, JIA J Y. Unnatural l0 sparse representation for natural image deblurring [C]. Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, 2013:1107-1114.

    [2] WANG G D, XU J, PAN ZH K, et al..Blind image restoration based on normalized hyper laplacian prior term [J]. Opt. Precision Eng., 2013, 21(5): 1340-1348. (in Chinese)

    [3] XU Y. Single-Image blind deblurring for non-uniform camera-shake blur [C]. Computer Vision-ACCV 2012, Springer Berlin Heidelberg, 2013:336-348.

    [4] XU L, JIA J Y. Depth-aware motion deblurring[C]. 2012 IEEE International Conference on Computational Photography(ICCP), 2012: 1-8.

    [5] ZHAO W D, ZHAO J, HAN X ZH, et al.. Infrared image enhancement based on variational partial differential equations [J]. Chinese Journal of Liquid Crystals and Displays, 2014, 29(2): 281-285. (in Chinese)

    [6] CHO S. Registration based non-uniform motion deblurring [J]. Computer Graphics Forum, 2012,31(7):2183-2192.

    [7] LUCY L. An iterative technique for the rectification of observed distributions [J]. Astronomical Journal, 1974,76(6):745-754.

    [8] WIENER N. Extrapolation, Interpolation, and Smoothing of Stationary Time Series: with Engineering Applications [M]. MIT press, 1964.

    [9] KRISHNAN D, R FERGUS. Fast image deconvolution using hyper-Laplacian priors [J]. Advances in Neural Information Processing Systems, 2009, 22:1-9.

    [10] LI W H, DONG Y L, TANG SH. Regularized blind image restoration based on multi-norm hybrid constraints [J]. Opt. Precision Eng., 2013, 21(5): 1357-1364. (in Chinese)

    [11] FERGUS R. Removing camera shake from a single photograph [J]. ACM Transactions on Graphics (TOG), 2006,25(3):787-794.

    [12] XU L, JIA J Y. Two-phase kernel estimation for robust motion deblurring [C]. Computer Vision-ECCV 2010, 2010:157-170.

    [13] DONG X, LIN ZH X, GUO T L. Improved self-adaptive threshold wavelet denoising analysis based on LoG operator [J]. Chinese Journal of Liquid Crystals and Displays, 2014, 29(2): 275-280. (in Chinese)

    [14] CHO S, S LEE. Fast motion deblurring [J]. ACM Transactions on Graphics (TOG), 2009,28(5):145.

    [15] KRISHNAN D, T TAY, R FERGUS. Blind deconvolution using a normalized sparsity measure [C]. 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011:233-240.

    [16] GOLDSTEIM A, FATTAL R. Blur-kernel estimation from spectral irregularities [C]. European Conference on Computer Vision(ECCV),2012:622-635.

    [17] GUO H ZH, LU H Y, QU L X. Relation of line transfer period error and dynamic MTF of TDICCD in remote sensing camera [J]. Opt. Precision Eng., 2013, 21(8): 2195-2200. (in Chinese)

    CLP Journals

    [1] GUO Cong-zhou, QIN ZHi-yuan. Blind restoration of nature optical images based on non-convex high order total variation regularization[J]. Optics and Precision Engineering, 2015, 23(12): 3490

    [2] Yan Jingwen, Xie Tingting, Peng Hong, Liu Panhua. Motion Image Deblurring Based on L0 Norms Regularization Term[J]. Laser & Optoelectronics Progress, 2017, 54(2): 21005

    [3] GUO Cong-zhou, SHI Wen-jun, QIN ZHi-yuan, GENG Ze-xun. Non-convex sparsity regularization for wave back restoration of space object images[J]. Optics and Precision Engineering, 2016, 24(4): 902

    YAN Jing-wen, PENG Hong, LIU Lei, JIN Guang, ZHONG Xing. Remote sensing image restoration based on zero-norm regularized kernel estimation[J]. Optics and Precision Engineering, 2014, 22(9): 2572
    Download Citation