Mumford-Shah regularizer with spatial coherence

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4485 LNCS, Issue , 2007, Pages 545-555

  Erdem, Erkut ^a   Sanear Yilmaz, Aysun ^b   Tari, Sibel ^a  

^a MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^b ASELSAN INC   (Turkey)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION ALGORITHMS; COST FUNCTIONS; MATHEMATICAL MODELS;

BOUNDARY DETECTION; EDGE DIRECTION; SPATIAL COHERENCE; SPATIAL ORGANIZATIONS;

EDGE DETECTION;

EID: 37249046583     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-72823-8_47     Document Type: Conference Paper

References (19)

1. 1-norm of the gradient and their approximation. Interfaces and Free Boundaries, 1(1):17-37, 1999.
2. L. Ambrosio and V. Tortorelli. On the approximation of functionals depending on jumps by elliptic functionals via Γ-convergence. Commun. Pure Appl. Math., 43(8):999-1036, 1990.
3. L. Bar, N. Kiryati, and N. Sochen. Image deblurring in the presence of impulsive noise. Int. J. Comput. Vision, 70(3):279-298, 2006.
4. L. Bar, N. Sochen, and N. Kiryati. Image deblurring in the presence of salt-andpepper noise. In Scale-Space, pages 107-118, 2005.
5. M. J. Black and A. Rangarajan. On the unification of line processes, outlier rejection, and robust statistics with applications in early vision. Int. J. Comput. Vision, 19(1):57-91, 1996.
6. M. J. Black, G. Sapiro, D. H. Marimont, and D. Heeger. Robust anisotropic diffusion. IEEE Trans. Image Processing, 7(3):421-432, March 1998.
7. A. Braides. Approximation of Free-discontinuity Problems. Lecture Notes in Mathematics, Vol. 1694. Springer-Verlag, 1998.
8. T. Brox, A. Bruhn, N. Papenberg, and J. Weickert. High accuracy optical flow estimation based on a theory for warping. In ECCV (4), pages 25-36, 2004.
9. B. Burgeth, J. Weickert, and S. Tari. Minimally stochastic schemes for singular diffusion equations. In X.-C. Tai, K.-A. Lie, T. F. Chan, and S. Osher and, editors, Image Processing Based on Partial Differential Equations, Mathematics and Visualization, pages 325-339. Springer Berlin Heidelberg, 2006.
10. J. Canny. A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell., 8(6):679-698, 1986.
11. T. Chan and L. Vese. Variational image restoration and segmentation models and approximations. UCLA, CAM-report 97-47, September, 1997.
12. S. Geman and D. Geman. Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. IEEE Trans. Pattern Anal. Mach. Intell., 6: 721-639, 1984.
13. D. Mumford and J. Shah. Optimal approximations by piecewise smooth functions and associated variational problems. Commun. Pure Appl. Math., 42(5):577-685, 1989.
14. M. Nikolova. A variational approach to remove outliers and impulse noise. J. Math. Imaging Vis., 20(1-2):99-120, 2004.
15. O. Scherzer and J. Weickert. Relations between regularization and diffusion filtering. J. Math. Imaging Vis., 12(1):43-63, 2000.
16. J. Shah. Segmentation by nonlinear diffusion. In CVPR, pages 202-207, 1991.
17. J. Shah. A common framework for curve evolution, segmentation and anisotropic diffusion. In CVPR, pages 136-142, 1996.
18. S. Teboul, L. Blanc-Fraud, G. Aubert, and M. Barlaud. Variational approach for edge preserving regularization using coupled pde's. IEEE Trans. Image Processing, 7(3):387-397, March 1998.
19. J. Weickert. Coherence-enhancing diffusion filtering. Int. J. Comput. Vision, 31 (2-3):111-127, 1999.