期刊文献+

一种四阶P-Laplace图像盲复原方法 被引量:2

A Method for Fourth-Order P-Laplace Blind Image Restoration
下载PDF
导出
摘要 针对TV图像复原方法中产生的阶梯效应问题,结合传统的差值范数图像复原方法,提出一种四阶P-Laplace图像盲复原算法。该算法将四阶偏微分方程引入P-Laplace图像复原方法中,对图像的边缘和内部平滑区域做了分别处理以缓解TV复原方法中带来的阶梯效应,同时引入参数λ调节复原过程中的保真项,并对偏微分方程做单调灰度变化,进一步改善了图像复原效果,缓解了阶梯效应。实验结果证明,该算法对模糊图像有很好的复原效果,也适用于水下图像和雾天图像的图像复原。 In consideration of the staircase effect in TV image restoration,a method for P-Laplace blind image restoration was proposed,which was combined with the traditional difference norm image restoration method.The algorithm introduced the fourth-order partial differential equations into the P-Laplace image restoration.The image edge and smooth area within were processed separately,in order to alleviate the staircase effect from the TV recovery method.The parameterλwas introduced to regulate the fidelity term in the recovery process and monotone gray change was made in the partial differential equation.The image restoration result was further improved and the staircase effect was alleviated.The experimental results demonstrate that the algorithm has good results in blind image restoration.The algorithm also applies to the image restoration of underwater picture and fog image.
出处 《中国海洋大学学报(自然科学版)》 CAS CSCD 北大核心 2014年第9期110-115,共6页 Periodical of Ocean University of China
基金 水下图像的后向散射噪声抑制及其盲复原方法研究项目(60772058)资助
关键词 图像复原 TV复原 P-Laplace 四阶PDE 阶梯效应 image restoration TV restoration P-Laplace fourth-order PDE staircase effect
  • 相关文献

参考文献10

  • 1Kurdur D,Hatzinakos D.Blind image deconvolution[J].IEEE Signal Processing Magazine,1996,13(13):43-64.
  • 2Kurdur D,Hatzinakos D.Blind image restoration via recursive filtering using deterministic constraints[C].//Proceedings of the1996IEEE International Conference on Acoustics.Atlanta:Speech and Signal Processing,1996:2283-2286.
  • 3Rudin L I,0sher S,Fatima E.Nonlinear total variation based noise removal algorithms[J].Physica D,1992,60(1):259-268.
  • 4Chan T,Wong C.Total variation blind deconvolution[J].IEEE Transactions on Image Processing,1998,7(3):370-395.
  • 5Chan T,Wong C.Convergence of the alternating minimization algorithm for blind deconvolution[J].Linear Algebra and Its Application,2000,316(3):259-285.
  • 6You Y,Kaveh M.Blind image restoration by anisotropic regularization[J].IEEE Transactions on Image Processing,1999,8(3):396-407.
  • 7马少贤,江成顺.基于四阶偏微分方程的盲图像恢复模型[J].中国图象图形学报,2010,15(1):26-30. 被引量:20
  • 8You Y,Kaveh M.Fourth-order partial differential equations for noise removal[J].IEEE Transactions on Image Processing,2000,9(10):1723-1730.
  • 9Chan T,Marquina A,Mulet P.High-order total variation based image restoration[J].SIAM Journal on Scientific Computing,2000,22(2):503-516.
  • 10You Y,Kaveh M.Image enhancement using fourth order partial differential equations[C].//Proceedings of the Thirty-Second Asilomar Conference on Signals.Pacific Grove:Systems&Computers,1998:1677-1681.

二级参考文献11

  • 1张航,罗大庸.图像盲复原算法研究现状及其展望[J].中国图象图形学报(A辑),2004,9(10):1145-1152. 被引量:53
  • 2Kurdur D, Hatzinakos D. Blind image deconvolution [ J]. IEEE Signal Processing Magazing, 1996, 13 (3) : 43-64.
  • 3Kurdur D, Hatzinakos D. Blind image restoration via recursive filtering using deterministic constraints [ C ]//Proceedings of the 1996 IEEE International Conference on Acoustics, Speech and Signal Processing. Atlanta, GA, USA, 1996,4: 2283- 2286.
  • 4You Y, Kaveh M. A regularization approach to joint blur identification and image restoration [J]. IEEE Transactions on Image Processing, 1996,5 (3) : 416-428.
  • 5Chan T, Wong C. Total variation blind deeonvolutlon[J].IEEE Transactions on Image Processing, 1998,7(3 ) : 370-395.
  • 6Chan T, Wong C. Convergence of the alternating minimization algorithm for blind deconvolution [ J ]. Linear Algebra and Its Application, 2000,316 ( 3 ) : 259- 285.
  • 7Rudin L, Osher S, Fatimi E. Nonlinear total variation based noise removal algorithms [ J ]. Physica D, 1992,60 ( 4 ) : 259- 268.
  • 8You Y, Kaveh M. Fourth-order partial differential equations for noise removal[ J]. IEEE Transactions on Image Processing, 2000, 9(10): 1723-1730.
  • 9Chan T, Marqnina A, Mulet P. High-order total variation based image restoration [J]. SIAM Journal on Scientific Computing, 2000,22(2): 503-516.
  • 10You Y, Kaveh M. Image enhancement using fourth order partial differential equations [ C]//Proceedings of the Thirty-Second Asilomar Conference on Signals, Systems &Computers. Pacific Grove, CA, USA, 1998,2: 1677-1681.

共引文献19

同被引文献52

  • 1余瑞艳.求解l^1极小化问题的Bregman迭代算法[J].应用泛函分析学报,2012,14(4):365-369. 被引量:2
  • 2阮秋琦.数字图像处理[M].北京:电子工业出版社,2012.
  • 3AYERS G R,DAINTY J C.Iterative blind deconvolution method and its application[J].Optics Letters,1990,13(7):547-549.
  • 4YOU Y,KAREH M.A regularization approach to joint blur identification and image restoration [J].IEEE Transactions on Image Processing,1996,5(3):416-428.
  • 5CHAN T F,WONG C K.Total variation blind deconvolution [J].IEEE Transactions on Image Processing,1998,7(3):370-375.
  • 6FERGUS R,SINGH B,HERTZMANN A,et al..Removing camera shake from a single photograph[J].ACM Trans.On Graphics,2006,25(3):787-794.
  • 7KRISHNAN D,TAY T,FERGUS R.Blind deconvolution using a normalized sparsity measure[J].IEEE Computer Vision and Pattern Recognition,2011,233-240.
  • 8WU C L,TAI X C.Augmented Lagrangian method,dual methods,and split-bregman iteration for ROF,vectorial TV,and high order models[J].Siam Journal on Imaging Sciences,2010,3(3):300-339.
  • 9LI W,LI Q,GONG W,et al..Total variation blind deconvolution employing split Bregman iteration[J].Journal of Visual Communication & Image Representation,2012,23(3):409-417.
  • 10SHAO W,Z,ELAD M.Simple,accurate,and robust nonparametric blind super-resolution[EB/OL].(2015-03-11)[2015-05-21].http://arxiv.org/abs/1503.03187.

引证文献2

二级引证文献14

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部