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231224s2013 xx |||||o 00| ||eng c |
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|a 10.1109/TIP.2013.2272515
|2 doi
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|a eng
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|a Roux, Stéphane G
|e verfasserin
|4 aut
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|a Self-similar anisotropic texture analysis
|b the hyperbolic wavelet transform contribution
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|c 2013
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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|a Date Completed 14.04.2014
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|a Date Revised 19.09.2013
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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|a Textures in images can often be well modeled using self-similar processes while they may simultaneously display anisotropy. The present contribution thus aims at studying jointly selfsimilarity and anisotropy by focusing on a specific classical class of Gaussian anisotropic selfsimilar processes. It will be first shown that accurate joint estimates of the anisotropy and selfsimilarity parameters are performed by replacing the standard 2D-discrete wavelet transform with the hyperbolic wavelet transform, which permits the use of different dilation factors along the horizontal and vertical axes. Defining anisotropy requires a reference direction that needs not a priori match the horizontal and vertical axes according to which the images are digitized; this discrepancy defines a rotation angle. Second, we show that this rotation angle can be jointly estimated. Third, a nonparametric bootstrap based procedure is described, which provides confidence intervals in addition to the estimates themselves and enables us to construct an isotropy test procedure, which can be applied to a single texture image. Fourth, the robustness and versatility of the proposed analysis are illustrated by being applied to a large variety of different isotropic and anisotropic self-similar fields. As an illustration, we show that a true anisotropy built-in self-similarity can be disentangled from an isotropic self-similarity to which an anisotropic trend has been superimposed
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|a Journal Article
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|a Clausel, Marianne
|e verfasserin
|4 aut
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|a Vedel, Béatrice
|e verfasserin
|4 aut
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|a Jaffard, Stéphane
|e verfasserin
|4 aut
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|a Abry, Patrice
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 22(2013), 11 vom: 17. Nov., Seite 4353-63
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|x 1941-0042
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|g volume:22
|g year:2013
|g number:11
|g day:17
|g month:11
|g pages:4353-63
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|u http://dx.doi.org/10.1109/TIP.2013.2272515
|3 Volltext
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