Merge pull request #73 from vais-ral/NLTV

Nonlocal TV method added (CPU version)

1 files changed, 8 insertions, 4 deletions

diff --git a/Readme.md b/Readme.md
index 50842b7..cc74dbc 100644
--- a/Readme.md
+++ b/Readme.md
@@ -27,6 +27,7 @@
 5. Linear and nonlinear diffusion (explicit PDE minimisation scheme) **2D/3D CPU/GPU** (Ref. *8*)
 6. Anisotropic Fourth-Order Diffusion (explicit PDE minimisation) **2D/3D CPU/GPU** (Ref. *9*)
 7. A joint ROF-LLT (Lysaker-Lundervold-Tai) model for higher-order regularisation **2D/3D CPU/GPU** (Ref. *10,11*)
+8. Nonlocal Total Variation regularisation (GS fixed point iteration) **2D/3D CPU/GPU** (Ref. *12*)
 
 ### Multi-channel (denoising):
 1. Fast-Gradient-Projection (FGP) Directional Total Variation **2D/3D CPU/GPU** (Ref. *3,4,2*)
@@ -60,18 +61,19 @@ Flags used during configuration
 | `Matlab_ROOT_DIR` | path | Matlab directory|
 |`PYTHON_EXECUTABLE` | path | /path/to/python/executable|
 
-Here an example of build on Linux:
+Here an example of build on Linux (see also `run.sh` for additional info):
 
 ```bash
 git clone https://github.com/vais-ral/CCPi-Regularisation-Toolkit.git
 mkdir build
 cd build
-cmake ../CCPi-Regularisation-Toolkit -DCONDA_BUILD=OFF -DBUILD_MATLAB_WRAPPER=ON -DBUILD_PYTHON_WRAPPER=ON -DBUILD_CUDA=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=<your favourite install directory>
+cmake .. -DCONDA_BUILD=OFF -DBUILD_MATLAB_WRAPPER=ON -DBUILD_PYTHON_WRAPPER=ON -DBUILD_CUDA=ON -DCMAKE_BUILD_TYPE=Release -DCMAKE_INSTALL_PREFIX=./install
 make install
+cd install/python
+export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:../lib
 ```
 
 
-
 ### Python
 #### Python binaries
 Python binaries are distributed via the [ccpi](https://anaconda.org/ccpi/ccpi-regulariser) conda channel. Currently we produce packages for Linux64, Python 2.7, 3.5 and 3.6, NumPy 1.12 and 1.13.
@@ -82,7 +84,7 @@ conda install ccpi-regulariser -c ccpi -c conda-forge
 
 #### Python (conda-build)
 ```
-	export CIL_VERSION=0.10.1
+	export CIL_VERSION=0.10.2
 	conda build Wrappers/Python/conda-recipe --numpy 1.12 --python 3.5 
 	conda install ccpi-regulariser=${CIL_VERSION} --use-local --force
 	cd demos/
@@ -149,6 +151,8 @@ addpath(/path/to/library);
 
 11. [Kazantsev, D., Guo, E., Phillion, A.B., Withers, P.J. and Lee, P.D., 2017. Model-based iterative reconstruction using higher-order regularization of dynamic synchrotron data. Measurement Science and Technology, 28(9), p.094004.](https://doi.org/10.1088/1361-6501/aa7fa8)
 
+12. [Abderrahim E., Lezoray O. and Bougleux S. 2008. Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing." IEEE Trans. Image Processing 17(7), pp. 1047-1060.](https://ieeexplore.ieee.org/document/4526700)
+
 ### References to Software:
 * If software is used, please refer to [11], however, the supporting publication is in progress.