P. Abry, S. Jaffard, and H. Wendt, When Van Gogh meets Mandelbrot: Multifractal classification of painting's texture, Signal Process, vol.93, pp.554-572, 2013.
DOI : 10.1016/j.sigpro.2012.01.016

URL : https://hal-upec-upem.archives-ouvertes.fr/hal-00798395/file/WVGMM.pdf

V. V. Anh and K. E. Lunney, Parameter estimation of random fields with long-range dependence, Math. Comput. Model, vol.21, pp.67-77, 1995.

J. Antoine, R. Murenzi, P. Vandergheynst, and S. T. Ali, Two-Dimensional Wavelets and Their Relatives, 2004.
DOI : 10.1017/cbo9780511543395

A. Arneodo, N. Decoster, P. Kestener, and S. G. Roux, A wavelet-based method for multifractal image analysis: From theoretical concepts to experimental applications, Advances in Imaging and Electron Physics, vol.126, pp.1-92, 2003.
URL : https://hal.archives-ouvertes.fr/hal-01557107

C. L. Benhamou, S. Poupon, E. Lespessailles, S. Loiseau, R. Jennane et al., Fractal analysis of radiographic trabecular bone texture and bone mineral density: Two complementary parameters related to osteoporotic fractures, J. Bone Miner. Res, vol.16, pp.697-704, 2001.
URL : https://hal.archives-ouvertes.fr/hal-00768782

J. Beran, Statistics for Long-Memory Processes, 1994.

J. Besag, Statistical analysis of non-lattice data, The Statistician, vol.24, pp.179-195, 1975.
DOI : 10.2307/2987782

J. Bruna, S. Mallat, E. Bacry, and J. Muzy, Intermittent process analysis with scattering moments, Ann. Stat, vol.43, pp.323-351, 2015.
DOI : 10.1214/14-aos1276

URL : https://hal.archives-ouvertes.fr/hal-01297107

B. Castaing, Y. Gagne, and M. Marchand, Log-similarity for turbulent flows?, Phys. D, issue.93, p.90132, 1993.
DOI : 10.1016/0167-2789(93)90132-k

P. Chainais, Infinitely divisible cascades to model the statistics of natural images, IEEE Trans. Pattern Anal. Mach. Intel, vol.29, pp.2105-2119, 2007.

N. H. Chan and W. Palma, Estimation of long-memory time series models: A survey of different likelihood-based methods, Adv. Econom, vol.20, pp.89-121, 2006.

C. Chang, Q. Du, T. Sun, and M. L. Althouse, A joint band prioritization and banddecorrelation approach to band selection for hyperspectral image classification, IEEE Trans. Geosci. Remote Sensing, vol.37, pp.2631-2641, 1999.

J. Coddington, J. Elton, D. Rockmore, and Y. Wang, Multifractal analysis and authentication of Jackson Pollock paintings, Computer Image Analysis in the Study of Art, Proc. SPIE 6810, p.68100, 2008.
DOI : 10.1117/12.765015

S. Combrexelle and H. Wendt, Multifractal analysis of multivariate images using gamma Markov random field priors
URL : https://hal.archives-ouvertes.fr/hal-01925387

S. Combrexelle, H. Wendt, Y. Altmann, J. Tourneret, S. Mclaughlin et al., A bayesian framework for the multifractal analysis of images using data augmentation and a Whittle approximation, Proc. IEEE Int. Conf. Acoust., Speech, and Signal Process. (ICASSP), 2016.
URL : https://hal.archives-ouvertes.fr/hal-01511897

S. Combrexelle, H. Wendt, Y. Altmann, J. Tourneret, S. Mclaughlin et al., Bayesian joint estimation of the multifractality parameter of image patches using gamma Markov random field priors, Proc. IEEE Int. Conf. Image Proc. (ICIP), 2016.
URL : https://hal.archives-ouvertes.fr/hal-01447351

S. Combrexelle, H. Wendt, N. Dobigeon, J. Tourneret, S. Mclaughlin et al., Bayesian estimation of the multifractality parameter for image texture using a Whittle approximation, IEEE Trans. Image Process, vol.24, pp.2540-2551, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01187463

S. Combrexelle, H. Wendt, J. Tourneret, P. Abry, and S. Mclaughlin, Bayesian multifractal analysis of multi-temporal images using smooth priors, Proc. IEEE Workshop Statistical Signal Proces. (SSP), 2016.
URL : https://hal.archives-ouvertes.fr/hal-01461698

O. Dikmen and A. Cemgil, Gamma Markov random fields for audio source modeling, IEEE Trans. Audio Speech Language Process, vol.18, pp.589-601, 2010.
DOI : 10.1109/tasl.2009.2031778

URL : http://www.cmpe.boun.edu.tr/~cemgil/papers/dikmen-cemgil-tsalp2010.pdf

D. A. Dyk and X. Meng, The art of data augmentation, J. Comput. Graphic. Stat, vol.10, pp.1-50, 2001.

M. Fuentese, Approximate likelihood for large irregularly spaced spatial data, J. Amer. Statist. Assoc, vol.102, pp.321-331, 2007.

N. R. Goodman, Statistical analysis based on a certain multivariate complex Gaussian distribution (an introduction), Ann. Math. Stat, vol.34, pp.152-177, 1963.
DOI : 10.1214/aoms/1177704250

URL : https://doi.org/10.1214/aoms/1177704250

T. C. Halsey, M. H. Jensen, L. P. Kadanoff, I. Procaccia, and B. I. Shraiman, Fractal measures and their singularities: The characterization of strange sets, Phys. Rev. A, vol.33, pp.1141-1151, 1986.

R. M. Haralick, Statistical and structural approaches to texture, Proc. IEEE, vol.67, pp.786-804, 1979.
DOI : 10.1109/proc.1979.11328

G. E. Hinton, Training products of experts by minimizing contrastive divergence, Neural Comput, vol.14, pp.1771-1800, 2002.
DOI : 10.1162/089976602760128018

URL : http://learning.cs.toronto.edu/~hinton/absps/nccd.pdf

S. Jaffard, Wavelet techniques in multifractal analysis, Fractal Geometry and Applications: A Jubilee of Beno??tBeno??t Mandelbrot, pp.91-152, 2004.
DOI : 10.1090/pspum/072.2/2112122

URL : http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA433872&Location=U2&doc=GetTRDoc.pdf

S. Jaffard, P. Abry, and H. Wendt, Irregularities and scaling in signal and image processing: Multifractal analysis, Benoit Mandelbrot: A Life in Many Dimensions, pp.31-116, 2015.
URL : https://hal.archives-ouvertes.fr/hal-00798427

S. Jaffard, S. Seuret, H. Wendt, R. Leonarduzzi, S. Roux et al., Multivariate multifractal analysis, Appl. Comput. Harmon. Anal
DOI : 10.1016/j.acha.2018.01.004

H. Ji, X. Yang, H. Ling, and Y. Xu, Wavelet domain multifractal analysis for static and dynamic texture classification, IEEE Trans. Image Process, vol.22, pp.286-299, 2013.

C. R. Johnson, P. Messier, W. Sethares, A. Klein, C. Brown et al., Pursuing automated classification of historic photographic papers from raking light photomicrographs, J. Amer. Inst. Conserv, vol.53, pp.159-170, 2014.
DOI : 10.1179/1945233014y.0000000024

P. Kestener, J. Lina, P. Saint-jean, and A. Arneodo, Wavelet-based multifractal formalism to assist in diagnosis in digitized mammograms, Image Anal. Stereol, vol.20, pp.169-175, 2001.
DOI : 10.5566/ias.v20.p169-174

URL : https://www.ias-iss.org/ojs/IAS/article/download/674/577

J. Lévy-véhel, P. Mignot, and J. Berroir, Multifractals, texture and image analysis, Proc. IEEE Conf. Comp. Vis. Pattern Recognition (CVPR), pp.661-664, 1992.

R. Lopes and N. Betrouni, Fractal and multifractal analysis: A review, Med. Image Anal, vol.13, pp.634-649, 2009.
DOI : 10.1016/j.media.2009.05.003

S. Lovejoy and D. Schertzer, The Weather and Climate: Emergent Laws and Multifractal Cascades, 2013.
DOI : 10.1017/cbo9781139093811

URL : https://hal.archives-ouvertes.fr/hal-00805839

T. Lux, Higher dimensional multifractal processes: A GMM approach, J. Bus. Econom. Stat, vol.26, pp.194-210, 2007.

S. Mallat, A Wavelet Tour of Signal Processing, 2008.

B. B. Mandelbrot, Intermittent turbulence in self-similar cascades: Divergence of high moments and dimension of the carrier, J. Fluid Mech, vol.62, pp.331-358, 1974.

C. Meneveau, K. Sreenivasan, P. Kailasnath, and M. Fan, Joint multifractal measures: Theory and applications to turbulence, Phys. Rev. A, vol.41, pp.894-913, 1990.
DOI : 10.1103/physreva.41.894

E. Moulines, F. Roueff, and M. Taqqu, A wavelet Whittle estimator of the memory parameter of a nonstationary Gaussian time series, Ann. Stat, pp.1925-1956, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00016446

M. Pereyra, N. Whiteley, C. Andrieu, and J. Tourneret, Maximum marginal likelihood estimation of the granularity coefficient of a Potts-Markov random field within an MCMC algorithm

, Proc. IEEE Workshop on Statistical Signal Proces. (SSP), pp.121-124, 2014.

L. Ponson, D. Bonamy, H. Auradou, G. Mourot, S. Morel et al., Anisotropic self-affine properties of experimental fracture surface, J. Fracture, vol.140, pp.27-36, 2006.

J. Prats-montalbán, A. De-juan, and A. Ferrer, Multivariate image analysis: A review with applications, Chemometrics Intell. Lab. Syst, vol.107, pp.1-23, 2011.

T. S. Rao and R. Chandler, A frequency domain approach for estimating parameters in point process models, Athens Conference on Applied Probability and Time Series Analysis, pp.392-405, 1996.

R. H. Riedi, Multifractal processes, in Theory and Applications of Long Range Dependence, pp.625-717, 2003.

L. Risser, T. Vincent, F. Forbes, J. Idier, and P. Ciuciu, Min-max extrapolation scheme for fast estimation of 3D Potts field partition functions. Application to the joint detection-estimation of brain activity in FMRI, J. Signal Process. Syst, vol.65, pp.325-338, 2011.
URL : https://hal.archives-ouvertes.fr/hal-00555919

C. P. Robert and G. Casella, Monte Carlo Statistical Methods, 2005.

R. Robert and V. Vargas, Gaussian multiplicative chaos revisited, Ann. Probab, vol.38, pp.605-631, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00293830

S. G. Roux, A. Arneodo, and N. Decoster, A wavelet-based method for multifractal image analysis. III. Applications to high-resolution satellite images of cloud structure, Eur. Phys. J. B, vol.15, pp.765-786, 2000.
URL : https://hal.archives-ouvertes.fr/hal-01557112

F. Schmitt, D. Schertzer, S. Lovejoy, and Y. Brunet, Multifractal temperature and flux of temperature variance in fully developed turbulence, Europhys. Lett, vol.34, p.195, 1996.

F. G. Schmitt and L. Seuront, Multifractal random walk in copepod behavior, Phys. A, vol.301, pp.375-396, 2001.

D. Sheeren, M. Fauvel, S. Ladet, A. Jacquin, G. Bertoni et al., Mapping ash tree colonization in an agricultural mountain landscape: Investigating the potential of hyperspectral imagery, Proc. IEEE Int. Conf. Geosci. Remote Sens. (IGARSS), pp.3672-3675, 2011.

M. A. Tanner and W. H. Wong, The calculation of posterior distributions by data augmentation, J. Amer. Stat. Assoc, vol.82, pp.528-540, 1987.

C. Vacar, J. Giovannelli, and Y. Berthoumieu, Bayesian texture classification from indirect observations using fast sampling, IEEE Trans. Signal Process, vol.64, pp.146-159, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01719190

H. Wendt, P. Abry, and S. Jaffard, Bootstrap for empirical multifractal analysis, IEEE Signal Process. Mag, vol.24, pp.38-48, 2007.

H. Wendt, P. Abry, S. Jaffard, H. Ji, and Z. Shen, Wavelet leader multifractal analysis for texture classification, Proc. IEEE Int. Conf. Image Proces. (ICIP), 2009.

H. Wendt, S. Jaffard, and P. Abry, Multifractal analysis of self-similar processes, Proc. IEEE Workshop on Statistical Signal Proces. (SSP), pp.69-72, 2012.

H. Wendt, R. Leonarduzzi, P. Abry, S. Roux, S. Jaffard et al., Assessing crossdependencies using bivariate multifractal analysis, IEEE Int. Conf. Acoust., Speech, and Signal Process. (ICASSP), 2018.

H. Wendt, S. G. Roux, S. Jaffard, and P. Abry, Wavelet leaders and bootstrap for multifractal analysis of images, Signal Process, vol.89, pp.1100-1114, 2009.

P. Whittle, On stationary processes in the plane, Biometrika, pp.434-449, 1954.

G. Wornell and A. V. Oppenheim, Estimation of fractal signals from noisy measurements using wavelets, IEEE Trans. Signal Process, vol.40, pp.611-623, 1992.
DOI : 10.1109/78.120804

Y. Xu, X. Yang, H. Ling, and H. Ji, A new texture descriptor using multifractal analysis in multiorientation wavelet pyramid, Proc. IEEE Conf. Comp. Vis. Pattern Recognition (CVPR), pp.161-168, 2010.
DOI : 10.1109/cvpr.2010.5540217

URL : http://www.ist.temple.edu/%7Ehbling/publication/wavelet-cvpr10.pdf