自适应阈值的超变分正则化图像盲复原
[1] MICHAILOVICH O V. An iterative shrinkage approach to total variation image restoration[J]. IEEE Trans. Image Processing, 2011, 20(5): 1281-1299.
[2] 温博, 张启衡, 张建林. 应用自解卷积和增量Wiener滤波实现迭代盲图像复原[J]. 光学 精密工程, 2011, 19(12): 3049-3055.
[3] ZHANG J L, ZHANG Q H, HE G M. Blind decon-volution of a noisy degraded image[J]. Applied Optics, 2009, 48(12): 2350-2355.
[4] 郭永彩, 王婀娜, 高潮. 空间自适应和正则化技术的盲图像复原[J]. 光学 精密工程, 2008, 16(11):2263-2267.
[5] CHANTAS G,GALATSANOS N,MOLINA R,et al.. Variational Bayesian image restoration with a product of spatially weighted total variation image priors [J]. IEEE Trans. Image Processing, 2010, 19(2): 351- 362.
[6] CHAN T F,SHEN J H. Image Processing and Analysis Variational, PDE, Wavelet and Stochastic Methods [M]. Beijing: Science Press, 2009.
[7] RUDIN L,OSHER S, FATEMI E. Nonlinear total variation based noise removal algorithms [J]. Physica D, 1992, 60:259-268.
[8] 邹谋炎. 反卷积和信号复原[M]. 北京:国防工业出版社, 2001:242-257.
ZOU M Y. Deconvolution and Signal Recovery [M]. Beijing: National Defense Industry Press, 2001:242-257. (in Chinese)
[9] CHAN T F,SHEN J. Aspects of total variation regularized L1 function approximation [J]. SIAM J.Appl. Math, 2005, 65:1817-1837.
[10] CHAN T F,WONG C K. Total variation blind deconvolution [J]. IEEE Trans. Image Processing, 1998, 7(3): 370-375.
[11] LIAO H Y,NG M K. Blind deconvolution using generalized cross-validation approach to regularization parameter estimation[J]. IEEE Trans. Image Processing, 2011, 20(3): 670-680.
[12] OSHER S,BURGER M,GOLDFARB D, et al.. An iterated regularization method for total variation based image restoration[J]. Simulation, 2005, 4(2):460-489.
[13] AUBERT G, KORNPROBST P. Mathematical Problems in Image Processing Partial Differential Equations and the Calculus of Variations [M]. New York: Springer, 2006.
[14] WANG Y,YANG J, YIN W,et al.. A new alternating minimization algorithm for total variation image reconstruction [J]. SIAM J. Imag. Sci., 2008, 1(3):248-272.
[15] 徐综琦. 图像盲复原实用技术研究[D]. 长沙:国防科学技术大学,2006: 45-49.
XU Z Q. Research on the Practical Technique of Image Blind Restoration[D]. Changsha:National University of Defense Technology,2006,45-49. (in Chinese)
周箩鱼, 张葆, 杨扬. 自适应阈值的超变分正则化图像盲复原[J]. 光学 精密工程, 2012, 20(12): 2759. ZHOU Luo-yu, ZHANG Bao, YANG Yang. Image blind deblurring based on super total variation regularization with self adaptive threshold[J]. Optics and Precision Engineering, 2012, 20(12): 2759.