Huo Chun-Lei, Cheng Jian, Lu Han-Qing, Zhou Zhi-Xin. Object-level change detection based on multiscale fusion. Acta Automatica Sinica, 2008, 34(3): 251-257(霍春雷, 程健, 卢汉清, 周志鑫. 基于多尺度融合的对象级变化检测新方法. 自动化学报, 2008, 34(3): 251-257)
[2]
Aubert G, Aujol J. A nonconvex model to remove multiplicative noise. In: Proceedings of the 1st International Conference on Scale Space and Variational Methods in Computer Vision. Ischia, Italy: Springer, 2007. 68-79
[3]
Jin Z M, Yang X P. Analysis of a new variation model for multiplicative noise removal. Journal of Mathematical Analysis and Applications, 2010, 362(2): 415-426
[4]
Rudin L I, Osher S, Fatemi E. Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena, 1992, 60(1-4): 259-268
[5]
Rudin L, Lions P L, Osher S. Multiplicative denoising and deblurring: theory and algorithms. Geometric Level Set Methods in Imaging, Vision and Graphics. New York: Springer, 2003. 103-119
[6]
Li Y Y, Santosa F. A computational algorithm for minimizing total variation in image restoration. IEEE Transactions on Image Processing, 1996, 5(6): 987-995
[7]
Nikolova M. Analysis of the recovery of edges in images and signals by minimizing nonconvex regularized least-squares. Multiscale Modelling and Simulation, 2005, 4(3): 960-991
[8]
Nikolova M, Ng M K, Tam C P. Fast nonconvex nonsmooth minimization methods for image restoration and reconstruction. IEEE Transactions on Image Processing, 2010, 19(12): 3073-3088
[9]
Rodriguez P, Wohlberg B. An iteratively reweighted norm algorithm for total variation regularization. In: Proceedings of the 40th Asilomar Conference on Signals, Systems and Computers. Pacific Grove, USA: IEEE, 2006. 892-896
[10]
Candes E J, Wakin M, Boyd S P. Enhancing sparsity by reweighted L1 minimization. Journal of Fourier Analysis and Applications, 2008, 14(5): 877-905
[11]
Foucart S, Lai M J. Sparsest solutions of underdetermined linear systems via L_{q}-minimization for 0 < q ≤ 1. Applied and Computational Harmonic Analysis, 2009, 26(3): 395-407
[12]
Wu Liang, Hu Yun-An. A survey of automatic road extraction from remote sensing images. Acta Automatica Sinica, 2010, 36(7): 912-922(吴亮, 胡云安. 遥感图像自动道路提取方法综述. 自动化学报, 2010, 36(7): 912-922)
[13]
Aubert G, Aujol J. A variational approach to removing multiplicative noise. SIAM Journal on Applied Mathematics, 2008, 68(4): 925-946
[14]
Huang Y M, Ng M K, Wen Y W. A new total variation method for multiplicative noise removal. SIAM Journal on Imaging Sciences, 2009, 2(1): 20-40
[15]
Feng Xiang-Chu, Wang Wei-Wei. Variaitional and Partial Differential Equation Method in Image Processing. Beijing: Science Press, 2009(冯象初, 王卫卫. 图像处理的变分和偏微分方程方法. 北京: 科学出版社, 2009)
[16]
Geman S, Geman D. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1984, 6(6): 721-741
[17]
Lin Y Q, Lee D D. Bayesian L1-norm sparse learning. In: International Conference on Acoustics, Speech, and Signal Processing. Toulouse, France: IEEE, 2006. 605-608
[18]
Nikolova M, Ng M K, Zhang S, Ching W. Efficient reconstruction of piecewise constant images using nonsmooth nonconvex minimization. SIAM Journal on Image Science, 2008, 1(1): 2-25
[19]
Han Yu, Wang Wei-Wei, Feng Xiang-Chu. Iteratively reweighted method based nonrigid image registration. Acta Automatica Sinica, 2011, 37(9): 1059-1066(韩雨, 王卫卫, 冯象初. 基于迭代重加权的非刚性图像配准. 自动化学报, 2011, 37(9): 1059-1066)
[20]
Wohlberg B, Rodriguez P. An iteratively reweighted norm algorithm for minimization of total variation functionals. IEEE Signal Processing Letters, 2007, 14(12): 948-951
[21]
Daubechies I, DeVore R, Fornasier M, Gunturk C S. Iteratively reweighted least squares minimization for sparse recovery. Communications on Pure and Applied Mathematics, 2010, 63(1): 1-38
[22]
Wipf D, Nagarajan S. Iterative reweighted L1 and L2 methods for finding sparse solutions. IEEE Journal of Selected Topics in Signal Processing, 2010, 4(2): 317-329
