From da6f9166f87d1e4860fe4b4535df130da7438196 Mon Sep 17 00:00:00 2001 From: Daniil Kazantsev <dkazanc@hotmail.com> Date: Tue, 3 Apr 2018 22:11:58 +0100 Subject: readme update2 --- Readme.md | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/Readme.md b/Readme.md index f55abbe..ef21ede 100644 --- a/Readme.md +++ b/Readme.md @@ -1,7 +1,7 @@ # CCPi-Regularisation Toolkit (CCPi-RUT) **Iterative image reconstruction (IIR) methods normally require regularisation to stabilise convergence and make the reconstruction problem more well-posed. -CCPi-RUT is released under Apache 2.0 license and consists of 2D/3D regularisation methods which frequently used for IIR. +CCPi-RUT software consist of 2D/3D regularisation modules which frequently used for IIR. The core modules are written in C-OMP and CUDA languages and wrappers for Matlab and Python are provided.** ## Prerequisites: @@ -11,13 +11,10 @@ The core modules are written in C-OMP and CUDA languages and wrappers for Matlab * C/C++ compilers * nvcc compilers -## Package Contents : +## 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] - -### Demos: - * --- + - 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: @@ -28,10 +25,13 @@ 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) + +### Acknowledgments: +CCPi-RUT 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 -### Acknowledgment: -CCPi-RUT is a product of the [CCPi project](https://pages.github.com/) -any questions/comments please e-mail to daniil.kazantsev@manchester.ac.uk -- cgit v1.2.3