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Cited by 1,076

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Iterative Methods for Total Variation Denoising

Vogel, C. R., Oman, M. E.·1996·SIAM Journal on Scientific Computing

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.

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Metadata

Authors
Vogel, C. R., & Oman, M. E.
Venue
SIAM Journal on Scientific Computing
Published
1996-01
Volume
17
Issue
1
Pages
227-238
ISSN
  • 1064-8275 (ISSN-L)
  • 1095-7197
OpenAlex
W2167400582
Cited by
1,076
References
1
FWCI
26.84
Type
journal article
Language
en
Open access
closed

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