ARFBF morphological analysis - Application to the discrimination of catalyst active phases

作者: Zhangyun Tan , Maxime Moreaud , Olivier Alata , Abdourrahmane M. Atto

DOI: 10.5566/IAS.1624

关键词: High-resolution transmission electron microscopyResidualBrownian motionBiological systemMaterials scienceCharacterization (materials science)Statistical modelAutoregressive modelMorphological analysisMathematical morphology

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

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