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Bayesian joint estimation of the multifractality parameter of image patches using gamma Markov Random Field priors

Combrexelle, Sébastien and Wendt, Herwig and Altmann, Yoann and Tourneret, Jean-Yves and Mclaughlin, Stephen and Abry, Patrice Bayesian joint estimation of the multifractality parameter of image patches using gamma Markov Random Field priors. (2016) In: IEEE International Conference on Image Processing (ICIP 2016), 25 September 2016 - 28 September 2016 (Phoenix, United States).

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Official URL: http://dx.doi.org/10.1109/ICIP.2016.7533205

Abstract

Texture analysis can be embedded in the mathematical framework of multifractal (MF) analysis, enabling the study of the fluctuations in regularity of image intensity and providing practical tools for their assessment, wavelet leaders. A statistical model for leaders was proposed permitting Bayesian estimation of MF parameters for images yielding improved estimation quality over linear regression based estimation. This present work proposes an extension of this Bayesian model for patch-wise MF analysis of images. Classical MF analysis assumes space homogeneity of the MF properties whereas here we assume MF properties may change between texture elements and we do not know where the changes are located. This paper proposes a joint Bayesian model for patches formulated using spatially smoothing gamma Markov Random Field priors to counterbalance the increased statistical variability of estimates caused by small patch sizes. Numerical simulations based on synthetic multi-fractal images demonstrate that the proposed algorithm outperforms previous formulations and standard estimators.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org This papers appears in Proceeding of ICIP 2016. Electronic ISBN: 978-1-4673-9961-6 Electronic ISSN: 2381-8549 The original PDF of the article can be found at: http://ieeexplore.ieee.org/document/7533205/ Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
HAL Id:hal-01447351
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Other partners > Ecole Normale Supérieure de Lyon - ENS de Lyon (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Heriot-Watt University (UNITED KINGDOM)
Laboratory name:
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Deposited By: IRIT IRIT
Deposited On:19 Jan 2017 11:03

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