C. Aguerrebere, Y. Gousseau, and G. Tartavel, Exemplarbased texture synthesis: the Efros-Leung algorithm, Image Processing On Line, vol.2013, pp.213-231, 2013.
DOI : 10.5201/ipol.2013.59
URL : https://doi.org/10.5201/ipol.2013.59

M. Aittala, T. Aila, and J. Lehtinen, Reflectance modeling by neural texture synthesis, ACM Transactions on Graphics, vol.35, issue.4, p.2016
DOI : 10.1145/1141911.1141987
URL : http://dl.acm.org/ft_gateway.cfm?id=2925917&type=pdf

M. Ashikhmin, Synthesizing natural textures, Proceedings of the 2001 symposium on Interactive 3D graphics , SI3D '01, pp.217-226, 2001.
DOI : 10.1145/364338.364405
URL : http://www.cs.utah.edu/~michael/ts/ts.pdf

M. Abdourrahmane, Z. Atto, O. Tan, M. Alata, and . Moreaud, Non-stationary texture synthesis from random field modeling, Image Processing (ICIP), 2014 IEEE International Conference on, pp.4266-4270, 2014.

R. James, E. H. Bergen, and . Adelson, Visual texture segmentation based on energy measures (a), Journal of the Optical Society of America A, vol.3, 1986.

G. Berger and R. Memisevic, Incorporating long-range consistency in cnn-based texture generation, Proceedings of the International Conference on Learning Representations (ICLR), 2017.

U. Bergmann, N. Jetchev, and R. Vollgraf, Learning texture manifolds with the periodic spatial gan. arXiv preprint, 2017.

C. Bordenave, Y. Gousseau, and F. Roueff, The dead leaves model: a general tessellation modeling occlusion, Advances in Applied Probability, pp.31-46, 2006.
DOI : 10.1239/aap/1143936138

T. Briand, J. Vacher, B. Galerne, and J. Rabin, The Heeger & Bergen Pyramid Based Texture Synthesis Algorithm, Image Processing On Line, vol.4, pp.276-299, 2014.
DOI : 10.5201/ipol.2014.79
URL : https://hal.archives-ouvertes.fr/hal-01435323

A. Buades, M. Lebrun, and J. Morel, Implementation of the " Non-Local Bayes " (NL-Bayes) Image Denoising Algorithm, Image Processing On Line, vol.2013, pp.1-42, 2013.

T. Caelli and B. Julesz, On perceptual analyzers underlying visual texture discrimination: Part I, Biological Cybernetics, vol.16, issue.3, pp.167-175, 1978.
DOI : 10.1007/BF00337138

T. Chang, C. C. , and J. Kuo, Texture analysis and classification with tree-structured wavelet transform, IEEE Transactions on Image Processing, vol.2, issue.4, pp.429-441, 1993.
DOI : 10.1109/83.242353

K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering, IEEE Transactions on Image Processing, vol.16, issue.8, pp.2080-2095, 2007.
DOI : 10.1109/TIP.2007.901238
URL : http://sp.cs.tut.fi/publications/archive/Dabov2007-Image.pdf

J. S. Bonet, Multiresolution sampling procedure for analysis and synthesis of texture images, Proceedings of the 24th annual conference on Computer graphics and interactive techniques , SIGGRAPH '97, pp.361-368, 1997.
DOI : 10.1145/258734.258882

J. Deng, W. Dong, R. Socher, L. Li, K. Li et al., Imagenet: A large-scale hierarchical image database, Computer Vision and Pattern Recognition CVPR 2009. IEEE Conference on, pp.248-255, 2009.

L. Emily, S. Denton, R. Chintala, and . Fergus, Deep generative image models using a laplacian pyramid of adversarial networks, Advances in neural information processing systems, pp.1486-1494, 2015.

A. Desolneux, L. Moisan, and S. Ronsin, A compact representation of random phase and Gaussian textures, 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012.
DOI : 10.1109/ICASSP.2012.6288148
URL : https://hal.archives-ouvertes.fr/hal-00662377

A. Dosovitskiy and T. Brox, Generating images with perceptual similarity metrics based on deep networks, Advances in Neural Information Processing Systems, pp.658-666, 2016.

A. Efros and T. K. Leung, Texture synthesis by non-parametric sampling, Proceedings of the Seventh IEEE International Conference on Computer Vision, pp.1033-1038, 1999.
DOI : 10.1109/ICCV.1999.790383

A. A. Efros and W. T. Freeman, Image quilting for texture synthesis and transfer, Proceedings of the 28th annual conference on Computer graphics and interactive techniques , SIGGRAPH '01, pp.341-346, 2001.
DOI : 10.1145/383259.383296

T. William, E. H. Freeman, and . Adelson, The design and use of steerable filters, IEEE Transactions on Pattern analysis and machine intelligence, vol.13, issue.9, pp.891-906, 1991.

B. Galerne, Y. Gousseau, and J. Morel, Micro-Texture Synthesis by Phase Randomization, Image Processing On Line, vol.1, 2011.
DOI : 10.5201/ipol.2011.ggm_rpn
URL : https://doi.org/10.5201/ipol.2011.ggm_rpn

B. Galerne, Y. Gousseau, and J. Morel, Random Phase Textures: Theory and Synthesis, IEEE Transactions on Image Processing, vol.20, issue.1, pp.257-267, 2011.
DOI : 10.1109/TIP.2010.2052822
URL : https://hal.archives-ouvertes.fr/hal-00418389

B. Galerne and A. Leclaire, An Algorithm for Gaussian Texture Inpainting, Image Processing On Line, vol.7, issue.7, pp.1-16, 2017.
DOI : 10.5201/ipol.2017.198
URL : https://doi.org/10.5201/ipol.2017.198

B. Galerne and A. Leclaire, Texture Inpainting Using Efficient Gaussian Conditional Simulation, SIAM Journal on Imaging Sciences, vol.10, issue.3, pp.1446-1474, 2017.
DOI : 10.1137/16M1109047
URL : https://hal.archives-ouvertes.fr/hal-01428428

B. Galerne, A. Leclaire, and L. Moisan, Microtexture inpainting through Gaussian conditional simulation, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp.1204-1208, 2016.
DOI : 10.1109/ICASSP.2016.7471867
URL : https://hal.archives-ouvertes.fr/hal-01214695

L. Gatys, A. S. Ecker, and M. Bethge, Texture synthesis using convolutional neural networks, Advances in Neural Information Processing Systems, pp.262-270, 2015.

L. Gatys, A. S. Ecker, and M. Bethge, Code to synthesise textures using convolutional neural networks as described in gatys et al. 2015. https://github, pp.2015-2016

L. Gatys, A. S. Ecker, and M. Bethge, Image Style Transfer Using Convolutional Neural Networks, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2414-2423, 2016.
DOI : 10.1109/CVPR.2016.265

I. Goodfellow, J. Pouget-abadie, M. Mirza, B. Xu, D. Warde-farley et al., Generative adversarial nets, Advances in neural information processing systems, pp.2672-2680, 2014.

U. Grenander, General Pattern Theory, 1993.

B. Guo, H. Shum, and Y. Xu, Chaos mosaic: Fast and memory efficient texture synthesis. Microsoft research paper MSR-TR, 2000.

J. David, J. R. Heeger, and . Bergen, Pyramid-based texture analysis/synthesis, Proceedings of the 22nd annual conference on Computer graphics and interactive techniques, pp.229-238, 1995.

A. Hertzmann, C. E. Jacobs, N. Oliver, B. Curless, and D. H. Salesin, Image analogies, Proceedings of the 28th annual conference on Computer graphics and interactive techniques , SIGGRAPH '01, pp.327-340, 2001.
DOI : 10.1145/383259.383295

C. D. Daniel-jiwoong-im, H. Kim, R. Jiang, and . Memisevic, Generating images with recurrent adversarial networks, 2016.

N. Jetchev, U. Bergmann, and R. Vollgraf, Texture synthesis with spatial generative adversarial networks. arXiv preprint, 2016.

N. Jetchev, U. Bergmann, and R. Vollgraf, Spatial generative adversarial networks. https://github.com/zalandoresearch/spatial_ gan, pp.2016-2017

B. Julesz, Visual pattern discrimination Information Theory, IRE Transactions on, vol.8, issue.2, pp.84-92, 1962.
DOI : 10.1109/tit.1962.1057698

B. Julesz, Textons, the elements of texture perception and their interactions, Nature, vol.32, issue.5802, pp.91-97, 1981.
DOI : 10.1098/rstb.1980.0091

B. Julesz, A theory of preattentive texture discrimination based on first-order statistics of textons, Biological Cybernetics, vol.31, issue.2, pp.131-138, 1981.
DOI : 10.1007/BF00335367

B. Julesz, Dialogues on Perception, 1995.

B. Julesz, E. N. Gilbert, L. A. Shepp, and H. L. Frisch, Inability of Humans to Discriminate between Visual Textures That Agree in Second-Order Statistics???Revisited, Perception, vol.10, issue.4, pp.391-405, 1973.
DOI : 10.1137/0110041

B. Julesz, E. N. Gilbert, and J. D. Victor, Visual discrimination of textures with identical third-order statistics, Biological Cybernetics, vol.10, issue.3, pp.137-140, 1978.
DOI : 10.1007/BF00336998

A. Kaspar, B. Neubert, D. Lischinski, M. Pauly, and J. Kopf, Self Tuning Texture Optimization, Computer Graphics Forum, pp.349-359, 2015.
DOI : 10.1145/882262.882266

A. Krizhevsky, I. Sutskever, and G. E. Hinton, ImageNet classification with deep convolutional neural networks, Advances in neural information processing systems, pp.1097-1105, 2012.
DOI : 10.1162/neco.2009.10-08-881
URL : http://dl.acm.org/ft_gateway.cfm?id=3065386&type=pdf

V. Kwatra, I. Essa, A. Bobick, and N. Kwatra, Texture optimization for example-based synthesis, ACM Transactions on Graphics, vol.24, issue.3, pp.795-802, 2005.
DOI : 10.1145/1073204.1073263

V. Kwatra, A. Schödl, I. Essa, G. Turk, and A. Bobick, Graphcut textures, ACM Transactions on Graphics, vol.22, issue.3, pp.277-286, 2003.
DOI : 10.1145/882262.882264

A. Laine and J. Fan, Texture classification by wavelet packet signatures, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.15, issue.11, pp.1186-1191, 1993.
DOI : 10.1109/34.244679
URL : http://medimage.bme.columbia.edu/publication.dir/papers.dir/IEEE_PAMI_93.pdf

M. Lebrun, A. Buades, and J. Morel, A Nonlocal Bayesian Image Denoising Algorithm, SIAM Journal on Imaging Sciences, vol.6, issue.3, pp.1665-1688, 2013.
DOI : 10.1137/120874989

S. Lefebvre and H. Hoppe, Parallel controllable texture synthesis, ACM Transactions on Graphics, vol.24, issue.3, pp.777-786, 2005.
DOI : 10.1145/1073204.1073261
URL : http://www.research.microsoft.com/~hoppe/paratexsyn.pdf

E. Levina and P. J. Bickel, Texture synthesis and nonparametric resampling of random fields. The Annals of Statistics, pp.1751-1773, 2006.
DOI : 10.1214/009053606000000588
URL : http://doi.org/10.1214/009053606000000588

C. Li and M. Wand, Code for paper " combining markov random fields and convolutional neural networks for image synthesis " . https:// github.com/chuanli11/CNNMRF, pp.2015-2016
DOI : 10.1109/cvpr.2016.272

C. Li and M. Wand, Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.2479-2486, 2016.
DOI : 10.1109/CVPR.2016.272

L. Liang, C. Liu, Y. Xu, B. Guo, and H. Shum, Real-time texture synthesis by patch-based sampling, ACM Transactions on Graphics, vol.20, issue.3, pp.127-150, 2001.
DOI : 10.1145/501786.501787

G. Liu, Y. Gousseau, and G. Xia, Texture synthesis through convolutional neural networks and spectrum constraints, 23rd International Conference on Pattern Recognition, ICPR 2016, pp.3234-3239, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01567165

Y. David-lockerman, B. Sauvage, J. Rémialì-egre, J. Dischler, . Dorsey et al., Multi-scale label-map extraction for texture synthesis, ACM Transactions on Graphics, vol.35, issue.4, pp.140-141, 2016.
DOI : 10.1145/1620993.1621027

Y. Lu, S. Zhu, and Y. Wu, Code for Learning FRAME Models Using CNN Filters

Y. Lu, S. Zhu, and Y. Wu, Learning FRAME Models Using CNN Filters, Thirtieth AAAI Conference on Artificial Intelligence, 2016.

J. Malik and P. Perona, Preattentive texture discrimination with early vision mechanisms, Journal of the Optical Society of America A, vol.7, issue.5, pp.923-932, 1990.
DOI : 10.1364/JOSAA.7.000923
URL : http://www.cs.berkeley.edu/~malik/papers/malik-perona90.pdf

B. S. Manjunathi and W. Y. Ma, Texture features for browsing and retrieval of image data, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, issue.8, pp.837-842, 1996.
DOI : 10.1109/34.531803

G. Matheron, Schéma booléen séquentiel de partition aléatoire Rapport technique N-83, 1968.

D. Mumford and A. Desolneux, Pattern Theory: The Stochastic Analysis of Real-World Signals, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00713576

R. Novak and Y. Nikulin, Improving the neural algorithm of artistic style. arXiv preprint, 2016.

A. Van-den-oord, N. Kalchbrenner, and K. Kavukcuoglu, Pixel recurrent neural networks. arXiv preprint, 2016.

K. Perlin, An image synthesizer, ACM SIGGRAPH Computer Graphics, vol.19, issue.3, pp.287-296, 1985.
DOI : 10.1145/325165.325247

G. Peyré, Sparse Modeling of Textures, Journal of Mathematical Imaging and Vision, vol.27, issue.2, pp.17-31, 2009.
DOI : 10.1016/S1076-5670(04)32006-9

G. Peyré, Texture Synthesis with Grouplets, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, issue.4, pp.733-746, 2010.
DOI : 10.1109/TPAMI.2009.54

J. Portilla and E. P. Simoncelli, Representation and synthesis of visual texture

J. Portilla and E. P. Simoncelli, A parametric texture model based on joint statistics of complex wavelet coefficients, International Journal of Computer Vision, vol.40, issue.1, pp.49-70, 2000.
DOI : 10.1023/A:1026553619983

L. Raad, A. Desolneux, and J. Morel, A Conditional Multiscale Locally Gaussian Texture Synthesis Algorithm, Journal of Mathematical Imaging and Vision, vol.52, issue.1, pp.260-279, 2016.
DOI : 10.1145/344779.345009

L. Raad and B. Galerne, Efros and Freeman Image Quilting Algorithm for Texture Synthesis, Image Processing On Line, vol.7, pp.1-22, 2017.
DOI : 10.5201/ipol.2017.171
URL : https://hal.archives-ouvertes.fr/hal-01435329

J. Rabin, G. Peyré, J. Delon, and M. Bernot, Wasserstein Barycenter and Its Application to Texture Mixing, Scale Space and Variational Methods in Computer Vision, pp.435-446, 2012.
DOI : 10.1109/18.119725

A. Radford, L. Metz, and S. Chintala, Unsupervised representation learning with deep convolutional generative adversarial networks, 2015.

D. Amir-rosenberger, D. Cohen-or, and . Lischinski, Layered shape synthesis: automatic generation of control maps for non-stationary textures, In ACM Transactions on Graphics, vol.28, p.107, 2009.

O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh et al., ImageNet Large Scale Visual Recognition Challenge, International Journal of Computer Vision, vol.1010, issue.1, pp.211-252, 2015.
DOI : 10.1007/978-3-642-15555-0_11
URL : http://arxiv.org/pdf/1409.0575

T. Salimans, A. Karpathy, X. Chen, P. Diederik, and . Kingma, Pixelcnn++: Improving the pixelcnn with discretized logistic mixture likelihood and other modifications, Proceedings of the International Conference on Learning Representations (ICLR), 2017.

J. Serra, Image analysis and mathematical morphology, v. 1. Academic press, 1982.

C. E. Shannon, A Mathematical Theory of Communication, Bell System Technical Journal, vol.27, issue.3, pp.379-423, 1948.
DOI : 10.1002/j.1538-7305.1948.tb01338.x

P. Eero, W. T. Simoncelli, and . Freeman, The steerable pyramid: a flexible architecture for multi-scale derivative computation, ICIP (3), pp.444-447, 1995.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition. arXiv preprint, 2014.

G. Tartavel, Y. Gousseau, and G. Peyré, Variational Texture Synthesis with Sparsity and Spectrum Constraints, Journal of Mathematical Imaging and Vision, vol.40, issue.1, pp.124-144, 2014.
DOI : 10.1137/130918010
URL : https://hal.archives-ouvertes.fr/hal-00881847

M. R. Turner, Texture discrimination by Gabor functions, Biological Cybernetics, vol.55, pp.71-82, 1986.

D. Ulyanov, V. Lebedev, A. Vedaldi, and V. Lempitsky, Texture networks: Feed-forward synthesis of textures and stylized images, Int. Conf. on Machine Learning (ICML), 2016.

M. Unser, Texture classification and segmentation using wavelet frames, IEEE Transactions on Image Processing, vol.4, issue.11, pp.1549-1560, 1995.
DOI : 10.1109/83.469936

I. Ustyuzhaninov, W. Brendel, L. Gatys, and M. Bethge, What does it take to generate natural textures, Proceedings of the International Conference on Learning Representations (ICLR), 2017.

A. Van-den-oord, N. Kalchbrenner, L. Espeholt, A. Vinyals, and . Graves, Conditional image generation with pixelcnn decoders, Advances in Neural Information Processing Systems 29, pp.4790-4798, 2016.

J. Jarke and . Van-wijk, Spot noise texture synthesis for data visualization, SIGGRAPH '91, pp.309-318, 1991.

X. Wang and A. Gupta, Generative Image Modeling Using Style and Structure Adversarial Networks, European Conference on Computer Vision, pp.318-335, 2016.
DOI : 10.1109/CVPR.2016.309

L. Wei, S. Lefebvre, V. Kwatra, and G. Turk, State of the art in example-based texture synthesis, Eurographics 2009, State of the Art Report, EG-STAR, pp.93-117, 2009.
URL : https://hal.archives-ouvertes.fr/inria-00606853

L. Wei and M. Levoy, Fast texture synthesis using tree-structured vector quantization, Proceedings of the 27th annual conference on Computer graphics and interactive techniques , SIGGRAPH '00, pp.479-488, 2000.
DOI : 10.1145/344779.345009

P. Wilmot, E. Risser, and C. Barnes, Stable and controllable neural texture synthesis and style transfer using histogram losses, 2017.

Y. Wu, S. Zhu, and X. Liu, Equivalence of Julesz ensembles and FRAME models, International Journal of Computer Vision, vol.38, issue.3, pp.247-265, 2000.
DOI : 10.1023/A:1008199424771

J. Xie, Y. Lu, S. Zhu, and Y. Wu, A theory of generative convnet, International Conference on Machine Learning, pp.2635-2644, 2016.

C. Zhu, R. H. Byrd, P. Lu, and J. Nocedal, Lbfgs-b: Fortran subroutines for large-scale bound constrained optimization, 1994.
DOI : 10.1145/279232.279236

S. Zhu, Y. Cheng-en-guo, Z. Wang, and . Xu, What are Textons?, International Journal of Computer Vision, vol.62, issue.1-2, pp.121-143, 2005.
DOI : 10.1007/s11263-005-4638-1

S. Zhu, X. W. Liu, and Y. Wu, Exploring texture ensembles by efficient Markov chain Monte Carlo-Toward a "trichromacy" theory of texture, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.22, issue.6, pp.554-569, 2000.
DOI : 10.1109/34.862195

S. Zhu, Y. N. Wu, and D. Mumford, Minimax Entropy Principle and Its Application to Texture Modeling, Neural Computation, vol.24, issue.319, pp.1627-1660, 1997.
DOI : 10.1145/127719.122750

S. Zhu, Y. N. Wu, and D. Mumford, Filters, random fields and maximum entropy (frame): Towards a unified theory for texture modeling, International Journal of Computer Vision, vol.27, issue.2, pp.107-126, 1998.
DOI : 10.1023/A:1007925832420