2‐D Spectral Analysis

Cariou, Claude; Rouquette, S.; Alata, Olivier

doi:10.1002/9780470611067.ch3

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-D Ar Model1

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Cited by 2 publications

(1 citation statement)

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“…The 2-D spectrum estimated from this method is easy to compute and has good estimation properties with respect to the other existing methods, see Alata and Cariou (2008b) for details.…”

Section: -D Ar Modelmentioning

confidence: 99%

Arfbf Morphological Analysis - Application to the Discrimination of Catalyst Active Phases

Tan¹,

Moreaud²,

Alata³

et al. 2018

Image Anal Stereol

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This paper addresses the characterization of spatial arrangements of fringes in catalysts imaged by High Resolution Transmission Electron Microscopy (HRTEM). It presents a statistical model-based approach for analyzing these fringes. The proposed approach involves Fractional Brownian Field (FBF) and 2-D AutoRegressive (AR) modeling, as well as morphological analysis. The originality of the approach consists in identifying the image background as an FBF, subtracting this background, modeling the residual by 2-D AR so as to capture fringe information and, finally, discriminating catalysts from fringe characterizations obtained by morphological analysis. The overall analysis is called ARFBF (Auto-Regressive Fractional Brownian Field) based morphology characterization.

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“…The 2-D spectrum estimated from this method is easy to compute and has good estimation properties with respect to the other existing methods, see Alata and Cariou (2008b) for details.…”

Section: -D Ar Modelmentioning

confidence: 99%