光学与光电技术, 2014, 12 (6): 25, 网络出版: 2014-12-26  

引入泽尼克多项式的极大似然盲解卷积算法初值的优化选取

Optimization of Initial-Value Choosing in the Maximum-Likelihood Blind Deconvolution with PSF Parameterized by Zernike Polynomials
作者单位
国防科学技术大学光电科学与工程学院, 湖南 长沙 410073
摘要
为提高图像盲复原处理效果,提出了经验法、拟合高斯点扩散函数法,以及符合Kolmogorov谱函数的初值选取方法等三种初值选取方法。引入泽尼克多项式参量化表示点扩散函数,应用极大似然迭代盲解卷积算法对模拟模糊图以及木星观测图进行了复原处理。计算结果表明,符合Kolmogorov谱函数分布的初值方法以及拟合高斯点扩散函数方法得到的图像复原结果较好。
Abstract
To improve the quality of the image restored by blind deconvolution, three initial-value-choosing methods are proposed, namely the experimental method, the Gaussian point spread function fitting method and the Kolmogorov spectrum method. Zernike polynomials are introduced to parameterize the point spread function, and the maximum-likelihood iterative blind deconvolution algorithm is applied to restore the blurred SEASAT image and the observed image of Jupiter. Experimental results show that the images have better details when restored by applying the Kolmogorove spectrum method and the Gaussian point spread function method.
参考文献

[1] Charles L Matson, Kathy Borelli. Fast and optimal multiframe blind deconvolution algorithm for high-resolution ground-based imaging of space objects[J]. Applied Optics, 2009, 48(1): 75-92.

[2] Ayers, Dainty. Iterative blind deconvolution method and its applications[J]. Optical Letters, 1988, 13(7): 547-549.

[3] Deepa Kundur, Dimitrios Hatzinakos. Blind image deconvolution[J]. IEEE: Signal Processing Magazine, 1996: 43-64.

[4] Mireille Guillaume, Pierre Melon, Philippe Refregier. Maximum-likelihood estimation of an astronomical image from a sequence at low photon levels[J]. Journal of the Optical Society of America-A, 1998, 11: 2841-2848.

[5] B C McCallum. Blind deconvolution by simulated annealing[J]. Optics Communications, 1990, 75(2): 101-105.

[6] Stuart M Jefferies, Julian C Christou. Restoration of astronomical images by iterative blind deconvolution[J]. The Astronomical Journal, 1993, 45: 862-875.

[7] 邹谋炎. 反卷积和信号复原[M]. 北京: 国防工业出版社, 2001.

[8] Rafael C Gonzalez, Richard E Woods. 数字图像处理[M]. 2版. 北京: 电子工业出版社, 2003: 175.

[9] Yu-Li You, M. Kaveh. A regularization approach to joint blur identification and image restoration[J]. Transactions on Image Processing, 1996, 3: 416-428.

[10] Noll. Zernike polynomials and atmospheric turbulence[J]. J. Opt. Soc. Am., 1976, 66(3): 207-211.

[11] 周仁忠, 阎吉祥, 赵达尊, 等. 自适应光学[M]. 北京: 国防工业出版社, 1996.

[12] Roddier N A. Atmospheric wavefront simulation using Zernike polynomials[J]. Optical Engineering, 1990, 29(10): 1174-1180.

[13] Patrizio Campisi, Karen Eglazarian. Blind image deconvolution: theory and applications[M]. Boca Raton: CRC Press, 2007.

姜南李威, 黄宗福, 许洁平, 梁永辉. 引入泽尼克多项式的极大似然盲解卷积算法初值的优化选取[J]. 光学与光电技术, 2014, 12(6): 25. JIANG Nan-liwei, HUANG Zong-fu, XU Jie-ping, LIANG Yong-hui. Optimization of Initial-Value Choosing in the Maximum-Likelihood Blind Deconvolution with PSF Parameterized by Zernike Polynomials[J]. OPTICS & OPTOELECTRONIC TECHNOLOGY, 2014, 12(6): 25.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!