Bayesian Filtering and Some Markovian Random Fields for Image Restoration

[1]  Mila Nikolova,et al.  Fast Nonconvex Nonsmooth Minimization Methods for Image Restoration and Reconstruction , 2010, IEEE Transactions on Image Processing.

[2]  Mariano Rivera,et al.  Half-quadratic cost functions for phase unwrapping. , 2004, Optics letters.

[3]  Gilles Fleury,et al.  Bootstrap methods for a measurement estimation problem , 2006, IEEE Transactions on Instrumentation and Measurement.

[4]  J. Besag On the Statistical Analysis of Dirty Pictures , 1986 .

[5]  Mila Nikolova,et al.  Analysis of Half-Quadratic Minimization Methods for Signal and Image Recovery , 2005, SIAM J. Sci. Comput..

[6]  Donald Geman,et al.  Constrained Restoration and the Recovery of Discontinuities , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Alison L. Gibbs,et al.  Convergence of Markov chain Monte Carlo algorithms with applications to image restoration , 2000 .

[8]  Jérôme Idier,et al.  A half-quadratic block-coordinate descent method for spectral estimation , 2002, Signal Process..

[9]  Frédo Durand,et al.  Image and depth from a conventional camera with a coded aperture , 2007, SIGGRAPH 2007.

[10]  Christian P. Robert,et al.  Monte Carlo Statistical Methods , 2005, Springer Texts in Statistics.

[11]  Bahram Javidi,et al.  Speckle removal using a maximum-likelihood technique with isoline gray-level regularization. , 2004, Journal of the Optical Society of America. A, Optics, image science, and vision.

[12]  Alain Herment,et al.  Unsupervised frequency tracking beyond the Nyquist frequency using Markov chains , 2002, IEEE Trans. Signal Process..

[13]  Jesús Villa,et al.  Phase recovery from a single fringe pattern using an orientational vector-field-regularized estimator. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[14]  Radford M. Neal Probabilistic Inference Using Markov Chain Monte Carlo Methods , 2011 .

[15]  Raymond H. Chan,et al.  The Equivalence of Half-Quadratic Minimization and the Gradient Linearization Iteration , 2007, IEEE Transactions on Image Processing.

[16]  Donald Geman,et al.  Nonlinear image recovery with half-quadratic regularization , 1995, IEEE Trans. Image Process..

[17]  Mila Nikolova,et al.  Analysis of the Recovery of Edges in Images and Signals by Minimizing Nonconvex Regularized Least-Squares , 2005, Multiscale Model. Simul..

[18]  Jérôme Idier,et al.  Convex half-quadratic criteria and interacting auxiliary variables for image restoration , 2001, IEEE Trans. Image Process..

[19]  M. Nikolova,et al.  Stability of the Minimizers of Least Squares with a Non-Convex Regularization. Part I: Local Behavior , 2006 .

[20]  Mila Nikolova,et al.  Algorithms for Finding Global Minimizers of Image Segmentation and Denoising Models , 2006, SIAM J. Appl. Math..

[21]  Frédéric Champagnat,et al.  A connection between half-quadratic criteria and EM algorithms , 2004, IEEE Signal Processing Letters.

[22]  Mariano Rivera,et al.  Robust phase demodulation of interferograms with open or closed fringes. , 2005, Journal of the Optical Society of America. A, Optics, image science, and vision.

[23]  Aggelos K. Katsaggelos,et al.  Digital image restoration , 2012, IEEE Signal Process. Mag..

[24]  Yves Goussard,et al.  On global and local convergence of half-quadratic algorithms , 2006, IEEE Trans. Image Process..

[25]  E. S. Chalhoub,et al.  Inverse problems in space science and technology , 2007 .

[26]  Ken D. Sauer,et al.  Bayesian estimation of transmission tomograms using segmentation based optimization , 1992 .

[27]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[28]  Jean-François Giovannelli,et al.  Regularized estimation of mixed spectra using a circular Gibbs-Markov model , 2001, IEEE Trans. Signal Process..

[29]  J. Besag Spatial Interaction and the Statistical Analysis of Lattice Systems , 1974 .