236
Litt´ erature
61. MacKay, D. : Chapter 20. An Example Inference Task : Clustering. Information
Theory, Inference and Learning Algorithms. Cambridge University Press (2003)
62. Maitre, H. : Le traitement des images. Herm` es Lavoisier (2003)
63. Mallat, S. : Une exploration des signaux en ondelettes. Editions de l’ ´
Ecole Polytechnique (2000)
64. Marr, D., Hildreth, E. : Theory of edge detection. Proceedings of the Royal Society of
London,Series B, Biological Sciences 207(1167), 187–217 (1980)
65. Masnou, S. : Filtrage et d´ esocclusion d’images par m´ ethodes d’ensembles de niveau.
Ph.D. thesis, Universit´ e Paris IX Dauphine, France (1998)
66. Masnou, S. : Disocclusion : a variational approach using level line. IEEE Trans. on
Image Proc. 11(2), 68–76 (2002)
67. Masnou, S., Morel, J.M. : Image restoration involving connectedness. In : Proc. of the
6 th Int. Workshop on Digital I.P. and Comp. Graphics, SPIE 3346. Vienna, Austria
(1998)
68. Masnou, S., Morel, J.M. : Level lines based disocclusion. In : Proc. of ICIP’98 (1998)
69. Meyer, Y. : Oscillating Patterns in Image Processing and Nonlinear Evolution Equations. University Lecture Series, Vol. 22, AMS (2001)
70. Mignotte, M. : Cours de traitement d’image URL http://www.iro.umontreal.ca/
~ mignotte/ift6150
71. Morel, J.M., Solimini, S. : Variational Methods in Image Segmentation. Birkhauser
(1995)
72. Mumford, D., Shah, J. : Optimal approximations by piecewise smooth functions and
associated variationnal problems. Communications on Pure and Applied Mathematics
XLVII(5), 577–685 (1989)
73. Najman, L., Talbot, H. : Morphologie Math´ ematique 1 : approches d´ eterministes.
Herm` es Lavoisier (2008)
74. Najman, L., Talbot, H. : Morphologie Math´ ematique 2 : estimation, choix et mise en
œuvre. Herm` es Lavoisier (2010)
75. Nesterov, Y. : Smooth minimization of non-smooth functions. Mathematic Programming, Ser. A 103(1), 127–152 (2005)
76. Osher, S., Fatemi, E., Rudin, L. : Nonlinear total variation based noise removal algorithms. Physica D 60, 259–268 (1992)
77. Osher, S., Sole, A., L., V. : Image decomposition and restoration using total variation
minimization and the h 1 norm. SIAM Journal on Multiscale Modeling and Simulation
1(3), 349–370 (2003)
78. Pallara, D., Ambrosio, L., Fusco, N. : Functions of bounded variations and free discontinuity problems. Oxford Mathematical Monograph (2000)
79. Perona, P. : Orientation diffusions. IEEE Trans. Image Processing 7(3), 457–467 (1998)
80. Perona, P., Malik, J. : Scale-space and edge detection using anisotropic diffusion. IEEE
Transactions on Pattern Analysis and Machine Intelligence 12(7), 629–639 (1990)
81. Peyr´ e, G. : Numerical tours URL www./numerical-tours.com
82. Richardson, W.H. : Bayesian-based iterative method of image restoration. JOSA 62(1),
55–59 (1972)
83. Rudin, W. : Analyse r´ eelle et complexe. Masson, Paris (1978)
84. Sainsaulieu, L. : Calcul scientifique. Sciences Sup. Dunod, Paris (2000)
85. Scherzer, O., Grasmair, M., Grossauer, H., Haltmeier, M., Lenzen, F. : Variational
Methods in Imaging. Springer
Litt´ erature
61. MacKay, D. : Chapter 20. An Example Inference Task : Clustering. Information
Theory, Inference and Learning Algorithms. Cambridge University Press (2003)
62. Maitre, H. : Le traitement des images. Herm` es Lavoisier (2003)
63. Mallat, S. : Une exploration des signaux en ondelettes. Editions de l’ ´
Ecole Polytechnique (2000)
64. Marr, D., Hildreth, E. : Theory of edge detection. Proceedings of the Royal Society of
London,Series B, Biological Sciences 207(1167), 187–217 (1980)
65. Masnou, S. : Filtrage et d´ esocclusion d’images par m´ ethodes d’ensembles de niveau.
Ph.D. thesis, Universit´ e Paris IX Dauphine, France (1998)
66. Masnou, S. : Disocclusion : a variational approach using level line. IEEE Trans. on
Image Proc. 11(2), 68–76 (2002)
67. Masnou, S., Morel, J.M. : Image restoration involving connectedness. In : Proc. of the
6 th Int. Workshop on Digital I.P. and Comp. Graphics, SPIE 3346. Vienna, Austria
(1998)
68. Masnou, S., Morel, J.M. : Level lines based disocclusion. In : Proc. of ICIP’98 (1998)
69. Meyer, Y. : Oscillating Patterns in Image Processing and Nonlinear Evolution Equations. University Lecture Series, Vol. 22, AMS (2001)
70. Mignotte, M. : Cours de traitement d’image URL http://www.iro.umontreal.ca/
~ mignotte/ift6150
71. Morel, J.M., Solimini, S. : Variational Methods in Image Segmentation. Birkhauser
(1995)
72. Mumford, D., Shah, J. : Optimal approximations by piecewise smooth functions and
associated variationnal problems. Communications on Pure and Applied Mathematics
XLVII(5), 577–685 (1989)
73. Najman, L., Talbot, H. : Morphologie Math´ ematique 1 : approches d´ eterministes.
Herm` es Lavoisier (2008)
74. Najman, L., Talbot, H. : Morphologie Math´ ematique 2 : estimation, choix et mise en
œuvre. Herm` es Lavoisier (2010)
75. Nesterov, Y. : Smooth minimization of non-smooth functions. Mathematic Programming, Ser. A 103(1), 127–152 (2005)
76. Osher, S., Fatemi, E., Rudin, L. : Nonlinear total variation based noise removal algorithms. Physica D 60, 259–268 (1992)
77. Osher, S., Sole, A., L., V. : Image decomposition and restoration using total variation
minimization and the h 1 norm. SIAM Journal on Multiscale Modeling and Simulation
1(3), 349–370 (2003)
78. Pallara, D., Ambrosio, L., Fusco, N. : Functions of bounded variations and free discontinuity problems. Oxford Mathematical Monograph (2000)
79. Perona, P. : Orientation diffusions. IEEE Trans. Image Processing 7(3), 457–467 (1998)
80. Perona, P., Malik, J. : Scale-space and edge detection using anisotropic diffusion. IEEE
Transactions on Pattern Analysis and Machine Intelligence 12(7), 629–639 (1990)
81. Peyr´ e, G. : Numerical tours URL www./numerical-tours.com
82. Richardson, W.H. : Bayesian-based iterative method of image restoration. JOSA 62(1),
55–59 (1972)
83. Rudin, W. : Analyse r´ eelle et complexe. Masson, Paris (1978)
84. Sainsaulieu, L. : Calcul scientifique. Sciences Sup. Dunod, Paris (2000)
85. Scherzer, O., Grasmair, M., Grossauer, H., Haltmeier, M., Lenzen, F. : Variational
Methods in Imaging. Springer