Iterative Methods For Total Variation Denoising
Cached
Download Links
| Venue: | SIAM J. SCI. COMPUT |
| Citations: | 159 - 7 self |
BibTeX
@ARTICLE{Vogel_iterativemethods,
author = {C. R. Vogel and M. E. Oman},
title = {Iterative Methods For Total Variation Denoising},
journal = {SIAM J. SCI. COMPUT},
year = {},
volume = {17},
pages = {227--238}
}
Years of Citing Articles
Bookmark
 |
 |
 |
 |
 |
 |
OpenURL
Abstract
Total Variation (TV) methods are very effective for recovering "blocky", possibly discontinuous, images from noisy data. A fixed point algorithm for minimizing a TV-penalized least squares functional is presented and compared with existing minimization schemes. A variant of the cell-centered finite difference multigrid method of Ewing and Shen is implemented for solving the (large, sparse) linear subproblems. Numerical results are presented for one- and two-dimensional examples; in particular, the algorithm is applied to actual data obtained from confocal microscopy.
