A Non Local Feature-Preserving Strategy for Image Denoising[J]. Chinese Journal of Electronics, 2012, 21(4): 651-656.
Citation: A Non Local Feature-Preserving Strategy for Image Denoising[J]. Chinese Journal of Electronics, 2012, 21(4): 651-656.

A Non Local Feature-Preserving Strategy for Image Denoising

  • Received Date: 2011-09-01
  • Rev Recd Date: 2011-10-01
  • Publish Date: 2012-10-25
  • In this paper, we propose a variational image denoising model by exploiting an adaptive featurepreserving strategy which is derived from the Non-local means (NL-means) denoising approach. The commonly used NL-means filter is not optimal for noisy images containing small features of interest since image noise always makes it difficult to estimate the correct coefficients for averaging, leading to over-smoothing and other artifacts. We address this problem by a non-local detail preserving constraint, which is performed by adding two terms in the Total variation (TV) model. One is a non local patch based regularization term that controls the amount of denoising to preserve textures, small details, or global information, the other is a new data fidelity term, which forces the gradients of desired image being close to the smoothed normal. The Euler-Lagrange equation is used to solve the problem. Experimental results show that the proposed method can alleviate the over-smoothing effect and other artifacts, while preserving the fine details.
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  • G. Gilboa, N. Sochen, Y.Y. Zeevi, “PDE-based denoising ofcomplex scenes using a spatially-varying delity term”, Proc.ICIP, Barcelona, Spain, Vol.1, pp.865-868, 2003.
    S. Osher, M. Burger, D. Goldfarb et al., “An iterative regularizationmethod for total variation based image restoration”,Multiscale Modelling and Simulation, Vol.4, No.2, pp.460-489,2005.
    E. Candès, L. Demanet, D. Donoho, L. Ying, “Fast discretecurvelet transforms”, Multiscale Modeling and Simulation,Vol.5, No.3, pp.861-899, 2006.
    A. Buades, B. Coll, J.M. Morel, “A review of image denoisingalgorithms, with a new one”, Multiscale Modeling and Simulation,Vol.4, No.2, pp.490-530, 2005.
    T. Brox, O. Kleinschmidt, D. Cremers, “Efficient nonlocalmeans for denoising of textural patterns”, IEEE Transactionson Image Processing, Vol.17, No.7, pp.1083-1092, 2008.
    V. Dore, M. Cheriet, “Robust NL-means filter with optimalpixel-wise smoothing parameter for statistical image denoising”,IEEE Trans. on Signal Processing, Vol.57, No.5, pp.1703-1716,2009.
    J. Boulanger, C. Kervrann, P. Bouthemy, P. Elbau, J.B.Sibarita, J. Salamero, “Patch-based nonlocal functional for denoisinguorescence microscopy image sequences”, IEEE Transactionson Medical Imaging, Vol.29, No.2, pp.442-454, 2010.
    L. Xiao, Lili Huang, Badrinath Roysam, “Image variational denoisingusing gradient fidelity on curvelet shrinkage”, EURASIPJournal on Advances in Signal Processing, Vol.2010, pp.1-17,2010.
    Lei Yang, Richard Parton, Graeme Ball, Zhen Qiu, Alan H.Greenaway, Ilan Davis, Weiping Lu, “An adaptive non-localmeans filter for denoising live-cell images and improving particledetection”, Journal of Structural Biology, Vol.172, No.3,pp.233-243, 2010.
    Wen Qiang Feng, Shu Min Li, Ke Long Zheng, “A non-localbilateral filter for image denoising”, 2010 International Conferenceon Apperceiving Computing and Intelligence Analysis(ICACIA), 17-19 Dec., pp.253-257, 2010.
    S. Kindermann, S. Osher, P.W. Jones, “Deblurring and denoisingof images by nonlocal functionals”, SIAM MMS, Vol.4, No.4,pp.1091-1115, 2005.
    G. Gilboa, S. Osher, “Nonlocal operators with applications toimage processing”, SIAM MMS, Vol.7, No.3, pp.1005-1028,2008.
    J. Gilles, Y. Meyer, “Properties of BV-G structures + texturesdecomposition models. application to road detection in satelliteimages”, IEEE Trans. Image Processing, Vol.19, No.11,pp.2793-2800, 2010.
    Y. Meyer, “Oscillating patterns in image processing and in somenonlinear evolution equations”, The Fifteenth Dean JacquelinesB. Lewis Memorial Lectures, American Mathematical Society,2001.
    X. Zhang, M. Burger, X. Bresson, S. Osher, “Bregmanized nonlocalregularization for deconvolution and sparse reconstruction”,CAM Report 09-03, 2009.
    M. Jung, L.A. Vese, “Nonlocal variational image deblurringmodels in the presence of gaussian or impulse noise”, SSVM2009, LNCS (5567), pp.402-413, 2009.
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