DocumentCode :
3348417
Title :
Multivariate statistical modeling of images in sparse multiscale transforms domain
Author :
Boubchir, Larbi ; Nait-Ali, Amine ; Petit, Eric
Author_Institution :
Lab. Images, Signaux et Syst. Intelligents, Univ. de Paris 12, Créteil, France
fYear :
2010
fDate :
26-29 Sept. 2010
Firstpage :
1877
Lastpage :
1880
Abstract :
In this paper, we propose a multivariate statistical model to characterize the inter- and intra-scale dependencies between image coefficients in the oriented and non-oriented sparse multiscale transforms domain. Our proposed model, namely the Multivariate Bessel K Form, is based on multivariate extension of Bessel K Form distribution. To establish this model in practice, we propose an analytical form of PDF and then estimate its hyperparameters. Also, we compared it to the other models proposed in literature such as the Anisotropic Multivariate Generalized Gaussian and the Jeffrey models, in order to demonstrate its capabilities to capture the inter- and intra-scale dependencies between image detail coefficients.
Keywords :
image processing; statistical analysis; Jeffrey models; anisotropic multivariate generalized Gaussian; image coefficients; multivariate Bessel K form; multivariate statistical model; sparse multiscale transforms domain; Analytical models; Image color analysis; Joints; Mathematical model; Wavelet domain; Wavelet transforms; Curvelet; EM algorithm; Multivariate Bessel K Form; Statistical modeling; Wavelet;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
ISSN :
1522-4880
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2010.5652329
Filename :
5652329
Link To Document :
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