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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-04-12 10:25:21 +0100 |
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| committer | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-04-12 10:25:21 +0100 |
| commit | 58f5ce047b063d53906e38047b6ae744ccdbd4eb (patch) | |
| tree | 611d46727147c2473f81c35174a6c105e830e94c /Readme.md | |
| parent | aa99eb8a9bd47ecd6e4d3d1e8c9f0cfbefb4f7bb (diff) | |
| download | regularization-58f5ce047b063d53906e38047b6ae744ccdbd4eb.tar.gz regularization-58f5ce047b063d53906e38047b6ae744ccdbd4eb.tar.bz2 regularization-58f5ce047b063d53906e38047b6ae744ccdbd4eb.tar.xz regularization-58f5ce047b063d53906e38047b6ae744ccdbd4eb.zip | |
dTV method added
Diffstat (limited to 'Readme.md')
| -rw-r--r-- | Readme.md | 2 |
1 files changed, 2 insertions, 0 deletions
@@ -18,6 +18,7 @@ can also be used as image denoising iterative filters. The core modules are writ 2. Fast-Gradient-Projection (FGP) Total Variation [2D/3D GPU/CPU]; (Ref. 2) ### Multi-channel +1. Fast-Gradient-Projection (FGP) Directional Total Variation [2D/3D GPU/CPU]; (Ref. 4,2) ## Installation: @@ -43,6 +44,7 @@ can also be used as image denoising iterative filters. The core modules are writ 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. ### License: [Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0) |