File	Date	Author	Commit
images	2013-04-20	Camille Couprie	[8b867b] initial commit
meshes	2013-04-20	Camille Couprie	[8b867b] initial commit
trismooth	2013-04-20	Camille Couprie	[8b867b] initial commit
DCMF_FBF_smooth_meshes.m	2013-04-20	Camille Couprie	[8b867b] initial commit
README.txt	2013-04-20	Camille Couprie	[8b867b] initial commit
add_noise.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_FBF.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_FBF_arbitrary_graph.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_PPXA.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_PPXA_color.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_PPXA_fusion.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_PPXA_general.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_PPXA_patches.m	2013-04-20	Camille Couprie	[8b867b] initial commit
algo_patch.m	2013-04-20	Camille Couprie	[8b867b] initial commit
compute_edges.m	2013-04-20	Camille Couprie	[8b867b] initial commit
compute_fastNLWeights_mex.c	2013-04-20	Camille Couprie	[8b867b] initial commit
compute_psnr_and_snr.m	2013-04-20	Camille Couprie	[8b867b] initial commit
create_figures_journal.m	2013-04-20	Camille Couprie	[8b867b] initial commit
fast_projection.m	2013-04-20	Camille Couprie	[8b867b] initial commit
fast_split_convex_set.m	2013-04-20	Camille Couprie	[8b867b] initial commit
freqfilt2D2.m	2013-04-20	Camille Couprie	[8b867b] initial commit
gradient.m	2013-04-20	Camille Couprie	[8b867b] initial commit
incidence.m	2013-04-20	Camille Couprie	[8b867b] initial commit
licence.txt	2013-04-20	Camille Couprie	[8b867b] initial commit
projection_L1.m	2013-04-20	Camille Couprie	[8b867b] initial commit
projection_Linf.m	2013-04-20	Camille Couprie	[8b867b] initial commit
projection_arbitrary_graph.m	2013-04-20	Camille Couprie	[8b867b] initial commit
projection_arbitrary_graph_Linf.m	2013-04-20	Camille Couprie	[8b867b] initial commit
smooth_mesh.m	2013-04-20	Camille Couprie	[8b867b] initial commit
split_arbitrary_graph.m	2013-04-20	Camille Couprie	[8b867b] initial commit
split_convex_set.m	2013-04-20	Camille Couprie	[8b867b] initial commit

Read Me

/* (2013)

Author :
Camille Couprie (c.couprie@esiee.fr)

Contributors :
Jean-Christophe Pesquet (jean-christophe.pesquet@univ-paris-est.fr)
Hugues Talbot (h.talbot@esiee.fr)
Laurent Najman (l.najman@esiee.fr)
Leo Grady (leograd@yahoo.com)

This software contains some image processing algorithms whose purpose is to be
used primarily for research.

This software is governed by the CeCILL license under French law and
abiding by the rules of distribution of free software.  You can  use,
modify and/ or redistribute the software under the terms of the CeCILL
license as circulated by CEA, CNRS and INRIA at the following URL
"http://www.cecill.info".

As a counterpart to the access to the source code and  rights to copy,
modify and redistribute granted by the license, users are provided only
with a limited warranty  and the software's author,  the holder of the
economic rights,  and the successive licensors  have only  limited
liability.

In this respect, the user's attention is drawn to the risks associated
with loading,  using,  modifying and/or developing or reproducing the
software by the user in light of its specific status of free software,
that may mean  that it is complicated to manipulate,  and  that  also
therefore means  that it is reserved for developers  and  experienced
professionals having in-depth computer knowledge. Users are therefore
encouraged to load and test the software's suitability as regards their
requirements in conditions enabling the security of their systems and/or
data to be ensured and,  more generally, to use and operate it in the
same conditions as regards security.

The fact that you are presently reading this means that you have had
knowledge of the CeCILL license and that you accept its terms.
*/

Camille Couprie
18/04/2013

This package contains Matlab code implementing algorithms for image restoration using DCTV.

Paper:
Camille Couprie, Leo Grady, Laurent Najman, Jean-Christophe Pesquet, Hugues Talbot
"Constrained TV-based regularization on graphs"
SIAM Journal on Imaging Sciences, 2013.

Demo : run 'create_figures_journal.m'

Main procedures : 
algo_PPXA
algo_FBF
algo_PPXA_color
algo_PPXA_general
algo_PPXA_fusion
algo_patch
smooth_mesh

Data : 
- f = original image to denoise (dim : n)
- a scalar lambda 
- a max number of iterations

Outputs : 
- u = restored image (dim : n)

The test file 'create_figures_journal.m' contains all calls to recreate figures of the paper.

The algorithms are optimizing the energy described in [Couprie et al. ICASSP 2011, SIAM 2013] 
For image denoising, with assumption that noise is Gaussian, the optimized energy is  
min_u max_F   A'F'*u + (1/(2*lambda))*(u-f)'*(u-f);
subject to the constraint |A'|F.^2 <= g^2

A is the incidence matrix A(dim : n,m) of a graph (n vertices, m edges)
g : gradient of f (+ eps to be nonzero) (dim : n)