W. Dong, L. Zhang, G. Shi, and X. Li, Nonlocally Centralized Sparse Representation for Image Restoration, IEEE Transactions on Image Processing, vol.22, issue.4, pp.1620-1630, 2013.
DOI : 10.1109/TIP.2012.2235847

W. Dong, L. Zhang, G. Shi, and X. Wu, Image Deblurring and Super-Resolution by Adaptive Sparse Domain Selection and Adaptive Regularization, IEEE Transactions on Image Processing, vol.20, issue.7, pp.1838-1857, 2011.
DOI : 10.1109/TIP.2011.2108306

J. Yang, J. Wright, T. Huang, and Y. Ma, Image Super-Resolution as Sparse Representation of Raw Image Patches, Proceedings IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), pp.1-8, 2008.

J. Yang, J. Wright, T. S. Huang, and Y. Ma, Image Super-Resolution Via Sparse Representation, IEEE Transactions on Image Processing, vol.19, issue.11, pp.2861-2873, 2010.
DOI : 10.1109/TIP.2010.2050625

M. Elad and M. Aharon, Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries, IEEE Transactions on Image Processing, vol.15, issue.12, pp.3736-3781, 2006.
DOI : 10.1109/TIP.2006.881969

W. Dong, X. Li, L. Zhang, and G. Shi, Sparsity-based image denoising via dictionary learning and structural clustering, CVPR 2011, pp.457-464, 2011.
DOI : 10.1109/CVPR.2011.5995478

D. L. Donoho, Compressed sensing, IEEE Transactions on Information Theory, vol.52, issue.4, pp.1289-1306, 2006.
DOI : 10.1109/TIT.2006.871582
URL : https://hal.archives-ouvertes.fr/inria-00369486

E. J. Candes and T. Tao, Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?, IEEE Transactions on Information Theory, vol.52, issue.12, pp.5406-5425, 2006.
DOI : 10.1109/TIT.2006.885507

E. J. Candès, J. Romberg, and T. Tao, Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information, IEEE Transactions on Information Theory, vol.52, issue.2, pp.489-509, 2006.
DOI : 10.1109/TIT.2005.862083

J. Ni, P. Turaga, V. M. Patel, and R. Chellappa, Example-Driven Manifold Priors for Image Deconvolution, IEEE Transactions on Image Processing, vol.20, issue.11, pp.3086-3096, 2011.
DOI : 10.1109/TIP.2011.2145386

J. Salmon, Z. Harmany, C. Deledalle, and R. Willett, Poisson Noise Reduction with Non-local PCA, Journal of Mathematical Imaging and Vision, vol.15, issue.2, pp.279-294, 2014.
DOI : 10.1007/s10851-013-0435-6
URL : https://hal.archives-ouvertes.fr/hal-00957837

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, Image denoising with block-matching and 3D filtering, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, pp.606-414, 2006.
DOI : 10.1117/12.643267

A. Danielyan, A. Foi, V. Katkovnik, and K. Egiazarian, Denoising of multispectral images via nonlocal groupwise spectrum-PCA, Conference on Colour in Graphics, Imaging, and Vision, pp.261-266, 2010.

A. B. Lee, K. S. Pedersen, and D. Mumford, The Nonlinear Statistics of High-Contrast Patches in Natural Images, International Journal of Computer Vision, vol.54, issue.1/2, pp.83-103, 2003.
DOI : 10.1023/A:1023705401078

G. Peyré, Manifold models for signals and images, Computer Vision and Image Understanding, vol.113, issue.2, pp.249-260, 2008.
DOI : 10.1016/j.cviu.2008.09.003

D. N. Kaslovsky and F. G. Meyer, Overcoming noise, avoiding curvature: Optimal scale selection for tangent plane recovery, 2012 IEEE Statistical Signal Processing Workshop (SSP), pp.892-895, 2012.
DOI : 10.1109/SSP.2012.6319851

H. Tyagi, E. Vural, and P. Frossard, Tangent space estimation for smooth embeddings of Riemannian manifolds, Information and Inference, vol.2, issue.1, pp.69-114, 2013.
DOI : 10.1093/imaiai/iat003

M. Donoser, Replicator Graph Clustering, Procedings of the British Machine Vision Conference 2013, pp.38-39
DOI : 10.5244/C.27.38

T. Peleg and M. Elad, A Statistical Prediction Model Based on Sparse Representations for Single Image Super-Resolution, IEEE Transactions on Image Processing, vol.23, issue.6, pp.2569-2582, 2014.
DOI : 10.1109/TIP.2014.2305844

J. Shi and J. Malik, Normalized cuts and image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.8, pp.888-905, 2000.

A. Y. Ng, M. I. Jordan, and Y. Weiss, On Spectral Clustering: Analysis and an algorithm, Proceedings Advances in Neural Information Processing Systems, pp.849-856, 2001.

M. Belkin and P. Niyogi, Laplacian Eigenmaps for Dimensionality Reduction and Data Representation, Neural Computation, vol.15, issue.6, pp.1373-1396, 2003.
DOI : 10.1126/science.290.5500.2319

N. Asgharbeygi and A. Maleki, Geodesic K-means clustering, 2008 19th International Conference on Pattern Recognition, pp.1-4, 2008.
DOI : 10.1109/ICPR.2008.4761241

E. Tu, L. Cao, J. Yang, and N. Kasabov, A novel graph-based kmeans for nonlinear manifold clustering and representative selection, Neurocomputing, vol.143, pp.1-14, 2014.

M. Breitenbach and G. Z. Grudic, Clustering through ranking on manifolds, Proceedings of the 22nd international conference on Machine learning , ICML '05, pp.73-80, 2005.
DOI : 10.1145/1102351.1102361

D. Zhou, O. Bousquet, T. N. Lal, J. Weston, and B. Schölkopf, Learning with Local and Global Consistency, Proceedings Advances in Neural Information Processing Systems 16 (NIPS), pp.321-328, 2004.

P. Turaga and R. Chellappa, Nearest-neighbor search algorithms on non-Euclidean manifolds for computer vision applications, Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP '10, pp.282-289, 2010.
DOI : 10.1145/1924559.1924597

R. Chaudhry and Y. Ivanov, Fast Approximate Nearest Neighbor Methods for Non-Euclidean Manifolds with Applications to Human Activity Analysis in Videos, Proceedings European Conference on Computer Vision (ECCV), pp.735-748, 2010.
DOI : 10.1007/978-3-642-15552-9_53

R. Souvenir and R. Piess, Manifold clustering, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, pp.648-653, 2005.
DOI : 10.1109/ICCV.2005.149

E. Elhamifar and R. Vidal, Sparse Manifold Clustering and Embedding, Proceedings Advances in Neural Information Processing Systems 24 (Nips), pp.55-63, 2011.

A. Goh and R. Vidal, Clustering and dimensionality reduction on Riemannian manifolds, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-7, 2008.
DOI : 10.1109/CVPR.2008.4587422

J. C. Bezdek, R. Ehrlich, and W. Full, FCM: The fuzzy c-means clustering algorithm, Computers & Geosciences, vol.10, issue.2-3, pp.191-203, 1984.
DOI : 10.1016/0098-3004(84)90020-7

J. Kim, K. H. Shim, and S. Choi, Soft Geodesic Kernel K-Means, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, pp.429-432, 2007.
DOI : 10.1109/ICASSP.2007.366264
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.99.130

G. Yu, G. Sapiro, and S. Mallat, Solving inverse problems with piecewise linear estimators: From gaussian mixture models to structured sparsity, IEEE Transactions on Image Processing, vol.21, issue.5, pp.2481-2499, 2012.

I. Daubechies, M. Defrise, and C. Mol, An iterative thresholding algorithm for linear inverse problems with a sparsity constraint, Communications on Pure and Applied Mathematics, vol.58, issue.11, pp.1413-1457, 2004.
DOI : 10.1002/cpa.20042

Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, Image Quality Assessment: From Error Visibility to Structural Similarity, IEEE Transactions on Image Processing, vol.13, issue.4, pp.600-612, 2004.
DOI : 10.1109/TIP.2003.819861

E. W. Dijkstra, A note on two problems in connexion with graphs, Numerische Mathematik, vol.4, issue.1, pp.269-271, 1959.
DOI : 10.1007/BF01386390

E. Vural and P. Frossard, Curvature analysis of pattern transformation manifolds, 2010 IEEE International Conference on Image Processing, pp.2689-2692
DOI : 10.1109/ICIP.2010.5651945

L. Zhang, L. Zhang, X. Mou, and D. Zhang, FSIM: A Feature Similarity Index for Image Quality Assessment, IEEE Transactions on Image Processing, vol.20, issue.8, pp.2378-2386, 2011.
DOI : 10.1109/TIP.2011.2109730

J. Portilla, Image restoration through l0 analysis-based sparse optimization in tight frames, 2009 16th IEEE International Conference on Image Processing (ICIP), pp.3909-3912, 2009.
DOI : 10.1109/ICIP.2009.5413975

J. C. Ferreira, E. Vural, and C. Guillemot, Geometry- Aware Neighborhood Search for Learning Local Models for Image Reconstruction, 2015.

V. Katkovnik, A. Foi, K. Egiazarian, and J. Astola, From Local Kernel to Nonlocal Multiple-Model Image Denoising, International Journal of Computer Vision, vol.11, issue.1, pp.1-32, 2010.
DOI : 10.1007/s11263-009-0272-7