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| author | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-04-03 22:23:56 +0100 |
|---|---|---|
| committer | Daniil Kazantsev <dkazanc@hotmail.com> | 2018-04-03 22:23:56 +0100 |
| commit | e4bd8ffc01807967a3553bce96cc5d04e09325a9 (patch) | |
| tree | 2d52e23ce9932d73c1d5e3e590389ac39005636d | |
| parent | da6f9166f87d1e4860fe4b4535df130da7438196 (diff) | |
| download | regularization-e4bd8ffc01807967a3553bce96cc5d04e09325a9.tar.gz regularization-e4bd8ffc01807967a3553bce96cc5d04e09325a9.tar.bz2 regularization-e4bd8ffc01807967a3553bce96cc5d04e09325a9.tar.xz regularization-e4bd8ffc01807967a3553bce96cc5d04e09325a9.zip | |
readme update3
| -rw-r--r-- | Readme.md | 14 |
1 files changed, 7 insertions, 7 deletions
@@ -8,13 +8,13 @@ The core modules are written in C-OMP and CUDA languages and wrappers for Matlab * MATLAB (www.mathworks.com/products/matlab/) * Python (ver. 3.5); Cython - * C/C++ compilers - * nvcc compilers + * C compilers + * nvcc (CUDA SDK) compilers ## Package modules (regularisers): - - 1. Rudin-Osher-Fatemi Total Variation (explicit PDE minimisation scheme) [2D/3D GPU/CPU] (1) - - 2. Fast-Gradient-Projection Total Variation [2D/3D GPU/CPU] (2) +1. * Rudin-Osher-Fatemi Total Variation (explicit PDE minimisation scheme) [2D/3D GPU/CPU] (1) +2. * Fast-Gradient-Projection Total Variation [2D/3D GPU/CPU] (2) ### Installation: @@ -25,9 +25,9 @@ The core modules are written in C-OMP and CUDA languages and wrappers for Matlab #### Matlab ### 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. +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. ### License: [Apache License, Version 2.0](http://www.apache.org/licenses/LICENSE-2.0) |