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
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