diff options
| author | Daniil Kazantsev <dkazanc3@googlemail.com> | 2018-04-16 15:29:57 +0100 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2018-04-16 15:29:57 +0100 |
| commit | 3d17b516f269921f5c8fb4eb54cec49f732e27d5 (patch) | |
| tree | b6dd09825750854bf6c87cee8e544c2278ac5586 /Readme.md | |
| parent | 7ae26b005c5f3d9ca0181ab1cf06b6ee8df5ed69 (diff) | |
| parent | 57727584760e6b1a980071587e1f1e8910c7d6a3 (diff) | |
| download | regularization-3d17b516f269921f5c8fb4eb54cec49f732e27d5.tar.gz regularization-3d17b516f269921f5c8fb4eb54cec49f732e27d5.tar.bz2 regularization-3d17b516f269921f5c8fb4eb54cec49f732e27d5.tar.xz regularization-3d17b516f269921f5c8fb4eb54cec49f732e27d5.zip | |
Merge pull request #50 from vais-ral/SB_TV
Split Bregman method
Diffstat (limited to 'Readme.md')
| -rw-r--r-- | Readme.md | 12 |
1 files changed, 6 insertions, 6 deletions
@@ -14,11 +14,12 @@ can also be used as image denoising iterative filters. The core modules are writ ## Package modules (regularisers): ### Single-channel -1. Rudin-Osher-Fatemi (ROF) Total Variation (explicit PDE minimisation scheme) [2D/3D GPU/CPU]; (Ref. 1) -2. Fast-Gradient-Projection (FGP) Total Variation [2D/3D GPU/CPU]; (Ref. 2) +1. Rudin-Osher-Fatemi (ROF) Total Variation (explicit PDE minimisation scheme) [2D/3D CPU/GPU]; (Ref. 1) +2. Fast-Gradient-Projection (FGP) Total Variation [2D/3D CPU/GPU]; (Ref. 2) +3. Split-Bregman (SB) Total Variation [2D/3D CPU/GPU]; (Ref. 4) ### Multi-channel -1. Fast-Gradient-Projection (FGP) Directional Total Variation [2D/3D GPU/CPU]; (Ref. 4,2) +1. Fast-Gradient-Projection (FGP) Directional Total Variation [2D/3D CPU/GPU]; (Ref. 3,2) ## Installation: @@ -43,12 +44,11 @@ can also be used as image denoising iterative filters. The core modules are writ ### References: 1. Rudin, L.I., Osher, S. and Fatemi, E., 1992. Nonlinear total variation based noise removal algorithms. Physica D: nonlinear phenomena, 60(1-4), pp.259-268. 2. Beck, A. and Teboulle, M., 2009. Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems. IEEE Transactions on Image Processing, 18(11), pp.2419-2434. -3. Lysaker, M., Lundervold, A. and Tai, X.C., 2003. Noise removal using fourth-order partial differential equation with applications to medical magnetic resonance images in space and time. IEEE Transactions on image processing, 12(12), pp.1579-1590. -4. Ehrhardt, M.J. and Betcke, M.M., 2016. Multicontrast MRI reconstruction with structure-guided total variation. SIAM Journal on Imaging Sciences, 9(3), pp.1084-1106. +3. Ehrhardt, M.J. and Betcke, M.M., 2016. Multicontrast MRI reconstruction with structure-guided total variation. SIAM Journal on Imaging Sciences, 9(3), pp.1084-1106. +4. Goldstein, T. and Osher, S., 2009. The split Bregman method for L1-regularized problems. SIAM journal on imaging sciences, 2(2), pp.323-343. ### License: [Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0) ### Acknowledgments: CCPi-RGL software is a product of the [CCPi](https://www.ccpi.ac.uk/) group and STFC SCD software developers. Any relevant questions/comments can be e-mailed to Daniil Kazantsev at dkazanc@hotmail.com - |