M. Do and M. Vetterli, Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance, IEEE Transactions on Image Processing, vol.11, issue.2, pp.146-158, 2002.
DOI : 10.1109/83.982822

J. Huang and D. Mumford, Statistics of natural images and models Computer Vision and Pattern Recognition, IEEE Computer Society Conference on, vol.1, p.547, 1999.

J. Mathiassen, A. Skavhaug, and K. Bø, Texture Similarity Measure Using Kullback-Leibler Divergence between Gamma Distributions, European Conference on Computer Vision, pp.19-49, 2002.
DOI : 10.1007/3-540-47977-5_9

R. Kwitt and A. Uhl, Image similarity measurement by Kullback-Leibler divergences between complex wavelet subband statistics for texture retrieval, 2008 15th IEEE International Conference on Image Processing, pp.933-936, 2008.
DOI : 10.1109/ICIP.2008.4711909

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

G. Tzagkarakis, B. Beferull-lozano, and P. Tsakalides, Rotation-invariant texture retrieval with gaussianized steerable pyramids, IEEE Transactions on Image Processing, vol.15, issue.9, pp.2702-2718, 2006.
DOI : 10.1109/TIP.2006.877356

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.108.6100

D. Cho and T. D. Bui, Multivariate statistical modeling for image denoising using wavelet transforms, Signal Processing: Image Communication, pp.77-89, 2005.
DOI : 10.1016/j.image.2004.10.003

S. Tan and L. Jiao, Multivariate Statistical Models for Image Denoising in the Wavelet Domain, International Journal of Computer Vision, vol.85, issue.12, pp.209-230, 2007.
DOI : 10.1007/s11263-006-0019-7

L. Boubchir, R. Boumaza, and B. Pumo, Multivariate Statistical Modeling of Images in Wavelet and Curvelet Domain using the Bessel K Form Densities, 16th IEEE International Conference on, 2009.

E. Conte, A. De-maio, and G. Ricci, Recursive estimation of the covariance matrix of a compound-Gaussian process and its application to adaptive CFAR detection, IEEE Transactions on Signal Processing, vol.50, issue.8, pp.1908-1915, 2002.
DOI : 10.1109/TSP.2002.800412

K. Yao, M. Simon, and E. Bigiieri, Unified theory on wireless communication fading statistics based on SIRP, Signal Processing Advances in Wireless Communications, pp.135-139, 2004.

T. Barnard and F. Khan, Statistical Normalization of Spherically Invariant Non-Gaussian Clutter, IEEE Journal of Oceanic Engineering, vol.29, issue.2, pp.303-309, 2004.
DOI : 10.1109/JOE.2004.828204

K. Yao, A representation theorem and its applications to spherically-invariant random processes Information Theory, IEEE Transactions on, vol.19, pp.600-608, 1973.

F. Pascal, Y. Chitour, J. Ovarlez, P. Forster, and P. Larzabal, Covariance Structure Maximum-Likelihood Estimates in Compound Gaussian Noise: Existence and Algorithm Analysis, [15] K. Krishnamoorthy, Handbook of Statistical Distributions with Applications16] MIT Vision and modeling group. Vision texture. [online]. Available from, pp.34-48, 2006.
DOI : 10.1109/TSP.2007.901652