期刊文献+

两种改进的图像复原算法在COSM中的应用

Two improved image restoration methods applied in COSM
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摘要 对模糊的成像结果进行图像复原,采用高斯函数作为点扩展函数,应用于三维逆滤波和维纳滤波算法中,改进了这两种算法。实验结果证明,改进后的维纳滤波算法复原三维序列的结果比改进后逆滤波算法得到的结果更好。此外,提出三维维纳增量滤波算法以及加快其收敛速度的方法。 Image restoration was applied in these result. This paper used Gaussian function as point spread function, applying in inverse filtering algorithm and Wiener filtering algorithm and improving them. It proves the effect of the improved Wiener filtering algorithms is better than inverse filtering improved algorithm. In addition, it proposed improved Wiener incremental filtering algorithm through theory.
出处 《计算机应用研究》 CSCD 北大核心 2008年第4期1081-1083,共3页 Application Research of Computers
基金 国家自然科学基金资助项目(60372079)
关键词 逆滤波 维纳滤波 增量维纳滤波 点扩展函数 inverse filtering Wiener filtering incremental Wiener filtering point spread function
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参考文献8

  • 1滕奇志,陶青川,赵佳,何小海.基于深度变化成像模型的图像估计[J].计算机工程与应用,2005,41(4):32-34. 被引量:6
  • 2Gonzalez R C,Woods R E.数字图像处理[M].2版.阮秋绮,阮宇智,译.北京:电子工业出版社,2003.
  • 3JENG F, WOODS J. Inhomogeneous Gaussian image restoration, part1 :theory[ J]. IEEE Trans on Acoust, Speech, Signal Proc, 1984,32:592-599.
  • 4XIN Yu, ZOU Cai-rong,YANG Lu-xi. Improved recursive inverse filtering method for blind image restoration [ C ]//Proc of the 6th International Conference on Volumel. 2002:37-40.
  • 5LEUNG C M, LU W S. A modified Wiener filter for the restoration of blurred image[J]. IEEE Pac Rim'93,1993,1 (5) :166-169.
  • 6ZOU Mou-yan,UNBEHAUEN R. A few new algorithms of 2DBlinddeconvolution[ J]. Optical Engineering ,1995,34(10) :2945-1956.
  • 7LIU Ju,YAN Hua,SUN Jiang-de, et al. Super-resolution image restoration by cobining incremental Wiener filter and space-adapative regularization [ C ]//Proc of IEEE Int Conf Neutal Networks & Signal Processing. Nanjiang : [ s. n. ], 2003 : 14-17.
  • 8AUTOQUANT. IMAGING, INC. Manual and tutorials [ EB/OL ]. [ 2006 ]. http ://www. aqi. com.

二级参考文献10

  • 1D L Snyder,M I Miller.Random Point Processes in Time and Space [M].New York:Spfinger-Verlag, 1991.
  • 2Kenneth R Castleman.Digital image processing[M].Prentice-Hall International, 1996.
  • 3C Preza,J A Conchello.Image estimation accounting for point-spread function depth variation in three-dimensional fluorescence microscopy [C].In:3D and Multidimensional Microscopy :Image Acquisition and Processing X,Proc SPIE ,2003 ;4964:27.
  • 4C Preza,J A Conchello.Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy. Optical Society of America, 2003.
  • 5A D Dempster,N M Laird,D B Rubin.Maximum Likelihood From Incomplete Data via the EM Algorithm[J].J Royal Statistical Society, B, 1977 ; 39:1~37.
  • 6T J Holmes.Expectation-maximization restoration of band limited, truncated point-process intensities with application in microscopy[J]. J Opt Soc Am,1989;A6(7):1006-1014.
  • 7A K Katsaggelos,K T Lay.Image identification and image restoration based on the expectation-maximization algorithm[J].Opt Eng,1990;29 (5) :436~445.
  • 8T J Holmes.Maximum-likelihood image restoration adapted for non- coherent optical imaging[J].Journal of the Optical Society of America A, 1988;5(5) ,666-673.
  • 9R L Langendijk,A M Tekalp,J Biemond.Maximum likelihood image and blur identification:A unifying approach[J].Opt Eng, 1990;29(5): 422-435.
  • 10T J Holmes et al.Light microscopic images reconstructed by maximum likelihood deconvolution.2nd ed,J B Pawley ed.Handbook of Biological an Confocal Microscopy,New York:Plenum, 1995.

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