|Table of Contents|

Non-blind deconvolution method for blurred image contaminated by Poisson noise

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2016年04期
Page:
404-
Research Field:
Publishing date:

Info

Title:
Non-blind deconvolution method for blurred image contaminated by Poisson noise
Author(s):
Dong WendeYang XinminDuan RanGuo XiaohongLin DanQin Shuxin
The 28th Research Institute of China Electronic Technology Group Corporation,Nanjing 210007,China
Keywords:
Poisson noise non-blind deconvolution Gaussian scale mixture fields of experts regularization
PACS:
TP391
DOI:
10.14177/j.cnki.32-1397n.2016.40.04.005
Abstract:
This paper proposes a non-blind image deconvolution method for restoring blurred image contaminated by Poisson noise.This method is constructed based on the Poisson noise model and introduces the Gaussian Scale Mixture Fields of Experts(GSM FoE)for regularization.The problem is solved with the alternating direction method of multipliers(ADMM).Experimental results show that the proposed method can effectively restore blurred image contaminated by Poisson noise and achieve results of high quality.

References:

[1] Viallefont-Robinet F.Edge method for on-orbit defocus assessment[J].Opt Express,2010,18(20):20845-20851.
[2]Viallefont-Robinet F,Léger D.Improvement of the edge method for on-orbit MTF measurement[J].Opt Express,2010,18(4):3531-3545.
[3]肖宿.非盲图像复原综述[J].电脑知识与技术,2013(7):1642-1644.
Xiao Su.Overview of non-blind image restoration[J].Computer Knowledge and Technology,2013(7):1642-1644.
[4]袁小华,高秀梅,夏其英,等.改进的有参超分辨率图像盲恢复[J].南京理工大学学报,2006,30(3):343-347.
Yuan Xiaohua,Gao Xiumei,Xia Qiying,et al.Improved parametric blind super-resolution image restoration[J].Journal of Nanjing University of Science and Technology,2006,30(3):343-347.
[5]陈新兵,杨世植,乔延利.基于马尔可夫随机场的快速乘性迭代盲去卷积[J].光电工程,2009,36(2):96-99.
Chen Xinbing,Yang Shizhi,Qiao Yanli.Fast multiplicative iterative blind deconvolution based on Markov random field[J].Opto-Electronic Engineering,2009,36(2):96-99.
[6]李伟红,董亚莉,唐述.多范数混合约束的正则化图像盲复原[J].光学精密工程,2013,21(5):1357-1364.
Li Weihong,Dong Yali,Tang Shu.Regularized blind image restoration based on multi-norm hybrid constraints[J].Optics & Precision Engineering,2013,21(5):1357-1364.
[7]王国栋,徐洁,潘振宽,等.基于归一化超拉普拉斯先验项的运动模糊图像盲复原[J].光学精密工程,2013,21(5):1340-1348.
Wang Guodong,Xu Jie,Pan Zhenkuan,et al.Blind image restoration based on normalized hyper Laplacian prior term[J].Optics & Precision Engineering,2013,21(5):1340-1348.
[8]Bardsley J M,Laobeul N.Tikhonov regularized Poisson likelihood estimation:theoretical justification and a computational method[J].Inverse Problems in Science and Engineering,2008,16(2):199-215.
[9]Tikhonov A N,Goncharsky A,Stepanov V,et al.Numerical methods for the solution of ill-posed problems[M].Dordrecht:Kluwer Academic Publi-shers,1995.
[10]Bioucas-Dias J M,Figueiredo M A T,Oliveira J P.Total variation-based image deconvolution:a majorization-minimization approach[C]//Proceedings of IEEE International Conference on Acoustics,Speech and Signal Processing.New York:IEEE,2006:861-864.
[11]Wang Yilun,Yang Junfeng,Yin Wotao,et al.A new alternating minimization algorithm for total variation image reconstruction[J].SIAM Journal on Imaging Sciences,2008,1(3):248-272.
[12]Tao Shuyin,Dong Wende,Feng Huajun,et al.Non-blind image deconvolution using natural image gradient prior[J].Optik,2013,124(24):6599-6605.
[13]Levin A,Fergus R,Durand F,et al.Image and depth from a conventional camera with a coded aperture[J].ACM Trans on Graphics,2007,26(3):Article No.70.
[14]Richardson W H.Bayesian-based iterative method of image restoration[J].J Opt Soc Am,1972,62(1):55-59.
[15]Lucy L B.An iterative technique for the rectification of observed distributions[J].Astronomical Journal,1974,79(6):745-754.
[16]Dempster A P,Laird N M,Rubin D B.Maximum likelihood from incomplete data via the EM algorithm[J].Journal of the Royal Statistical Society,Series B(Methodological),1977,39(1):1-38.
[17]Bertero M,Boccacci P,Desidera G,et al.Image deblurring with Poisson data:from cells to galaxies[J].Inverse Problems,2009,25(12):1-26.
[18]Green P J.On use of the EM for penalized likelihood estimation[J].Journal of the Royal Statistical Society,Series B(Methodological),1990,52(3):443-452.
[19]Green P J.Bayesian reconstructions from emission tomography data using a modified EM algorithm[J].IEEE Transactions on Medical Imaging,1990,9(1):84-93.
[20]Dey N,Blanc-Feraud L,Zimmer C,et al.Richardson-Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution[J].Microscopy Research and Technique,2006,69(4):260-266.
[21]Xu Z,Lam E Y.Maximum a posteriori blind image deconvolution with Huber-Markov random-field regulari-zation[J].Opt Lett,2009,34(9):1453-1455.
[22]Weiss Y,Freeman W T.What makes a good model of natural images?[C]//Proceedings of IEEE Con-ference on Computer Vision and Pattern Recognition.New York:IEEE,2007:1-8.
[23]Figueiredo M A T,Bioucas-Dias J M.Restoration of Poissonian images using alternating direction optimi-zation[J].IEEE Transactions on Image Processing,2010,19(12):3133-3145.
[24]Krishnan D,Fergus R.Fast image deconvolution using hyper-Laplacian priors[J].Advances in Neural Information Processing Systems,2009,22:1-9.

Memo

Memo:
-
Last Update: 2016-06-30