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基于邊緣恢復(fù)和偽像消除的正則化圖像復(fù)原

吳顯金 王潤(rùn)生

吳顯金, 王潤(rùn)生. 基于邊緣恢復(fù)和偽像消除的正則化圖像復(fù)原[J]. 電子與信息學(xué)報(bào), 2006, 28(4): 577-581.
引用本文: 吳顯金, 王潤(rùn)生. 基于邊緣恢復(fù)和偽像消除的正則化圖像復(fù)原[J]. 電子與信息學(xué)報(bào), 2006, 28(4): 577-581.
Wu Xian-jin, Wang Run-sheng. Regularized Image Restoration Based on Edge Restoration and Artifacts Removing[J]. Journal of Electronics & Information Technology, 2006, 28(4): 577-581.
Citation: Wu Xian-jin, Wang Run-sheng. Regularized Image Restoration Based on Edge Restoration and Artifacts Removing[J]. Journal of Electronics & Information Technology, 2006, 28(4): 577-581.

基于邊緣恢復(fù)和偽像消除的正則化圖像復(fù)原

Regularized Image Restoration Based on Edge Restoration and Artifacts Removing

  • 摘要: 由于各種原因復(fù)原圖像不可避免地會(huì)存在一定程度的Gibbs效應(yīng)、顆粒噪聲及邊緣振鈴等偽像, 為此該文基于邊緣恢復(fù)和消除偽像提出一種新的正則化圖像復(fù)原方法。該方法在保留傳統(tǒng)的平滑正則化約束項(xiàng)前提下, 首先將降質(zhì)圖像劃分為邊緣區(qū)、紋理區(qū)和平坦區(qū), 然后以圖像復(fù)原后邊緣區(qū)局部方差的增加量構(gòu)建正則化約束項(xiàng)作為對(duì)邊緣恢復(fù)的約束, 而以平坦區(qū)局部方差的減少量構(gòu)建正則化約束項(xiàng)作為對(duì)偽像消除的約束。實(shí)驗(yàn)結(jié)果表明, 在增加上述兩個(gè)正則化約束項(xiàng)后其復(fù)原效果要明顯優(yōu)于傳統(tǒng)的正則化復(fù)原方法。
  • Banham M R, Katsaggelos A K. Digital image restoration. IEEE Signal Processing Magazine, 1997,14(3): 24-41.[2]You Y L, Kaveh M. Blind image restoration by anisotropic regularization[J].IEEE Trans. on Image Processing.1999, 8(3):396-[3]Geman D, Yang C. Nonlinear image recovery with half- quadratic regularization[J].IEEE Trans. on Image Processing.1995, 4(7):932-946[4]Chan T F, Wong C K. Total variation blind deconvolution[J].IEEE Trans. on Image Processing.1998, 7(3):370-375[5]楊朝霞, 逯峰, 田芊. 小波構(gòu)造變正則參數(shù)變分模型在帶噪圖像恢復(fù)中的應(yīng)用. 計(jì)算機(jī)輔助設(shè)計(jì)與圖形學(xué)學(xué)報(bào), 2004, 16(12): 1645-1650.[6]Kang M G, Katsaggelos A K. General choice of the regularization functional in regularized image restoration[J].IEEE Trans. on Image Processing.1995, 4(5):594-602[7]Wu X J, Wang R S, Wang C. Regularized image restoration based on adaptively selecting parameter and operator. In: The 17th IEEE International Conference on Pattern Recognition, Cambridge, United Kingdom, 2004, 3: 662-665.[8]Sezan M I, Tekalp A M. Adaptive image restoration with artifact suppression using the theory of convex projections[J].IEEE Trans. on Acoustics, Speech, and Signal Processing.1990, 38(1):181-185[9]Lagenduk R L, Biemond J, Boekee D E. Regularized iterative image restoration with ring reduction[J].IEEE Trans. on Acoustics, Speech, and Signal Procession.1988, 36(12):1874-1887[10]Aghdasi F, Ward R K. Reduction of boundary artifacts in image restoration[J].IEEE Trans. on Image Processing.1996, 5(4):611-[11]You Y L, Kaveh M. Ringing reduction in image restoration by orientation-selective regularization[J].IEEE Signal Processing Letters.1996, 3(2):29-31[12]鄒謀炎. 反卷積和信號(hào)復(fù)原[M]. 北京: 國(guó)防工業(yè)出版社, 2001, 第6章第4節(jié).
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出版歷程
  • 收稿日期:  2005-06-20
  • 修回日期:  2005-12-31
  • 刊出日期:  2006-04-19

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