The convergence of a central-difference discretization of rudin-osher-fatemi model for image denoising

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

Volumn 5567 LNCS, Issue , 2009, Pages 514-526

  Lai, Ming Jun ^a   Lucier, Bradley ^b   Wang, Jingyue ^a  

^a UNIVERSITY OF GEORGIA   (United States)

^b PURDUE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTINUOUS INPUT; DISCRETE SPACES; DISCRETIZATIONS; ERROR BOUND; IMAGE DE-NOISING; INPUT DATAS; ROF MODEL; TOTAL VARIATION;

COMPUTER VISION;

INPUT OUTPUT PROGRAMS;

EID: 69049096382     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-02256-2_43     Document Type: Conference Paper

References (13)

1. Acar, R., Vogel, C.R.: Analysis of bounded variation penalty methods for ill-posed problems. Inverse Problems 10, 1217-1229 (1994)
2. Carter, J.L.: Dual Methods for Total Variation-Based Image Restoration, Ph.D. thesis, U.C.L.A (2001)
3. Chambolle, A.: An algorithm for total variation minimization and applications. Journal of Mathematical Imaging and Vision 20(1-2), 89-97 (2004)
4. Chambolle, A., Lions, P.-L.: Image recovery via total variation minimization and related problems. Numer. Math. 76(2), 167-188 (1997)
5. Chambolle, A., Levine, S., Lucier, B.: ROF image smoothing: some computational comments, draft (2008)
6. Chan, T.F., Golub, G.H., Mulet, P.: A nonlinear primal-dual method for total variation-based image restoration. SIAM J. Sci. Comput. 20(6), 1964-1977 (1999)
7. Dal Maso, G.: An Introduction to Γ-Convergence. Birkhauser, Boston (1993)
8. DeVore, R., Lorentz, G.: Constructive Approximation. Springer, Heidelberg (1993)
9. Evans, L., Gariepy, R.: Measure theory and fine properties of functions. CRC Press, Boca Raton (1992)
10. Rudin, L., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Physica D 60, 259-268 (1992)
11. Lions, P.-L., Osher, S.J., Rudin, L.: Denoising and deblurring using constrained nonlinear partial differential equations, Tech. Rep., Cognitech Inc., Santa Monica, CA, submit to SINUM
12. Wang, J., Lucier, B.: Error bounds for numerical methods for the ROF image smoothing model (2008) (in preparation)
13. Wang, J.: Error Bounds for Numerical Methods for the ROF Image Smoothing Model, Ph.D. thesis, Purdue (2008)