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Communication Dans Un Congrès Année : 2015

ARFBF MODEL FOR NON STATIONARY RANDOM FIELDS AND APPLICATION IN HRTEM IMAGES

Résumé

This paper presents a new model called Autoregressive Fractional Brownian Field (ARFBF) for analyzing textures which contain stationary and non-stationary components. The paper also proposes two estimation methods for the parameter of an isotropic fractional Brownian field based on Wavelet Packet (WP) spectrum: the Log-Regression on Diagonal WP spectrum (Log-RDWP) and the Log-Regression on Polar representation of WP spectrum (Log-RPWP). The Log-RPWP method provides a better estimation performance for small size images. We show the interest of ARFBF model and Log-RPWP for characterizing High-Resolution Transmission Electron Microscopy (HRTEM) images.
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Dates et versions

hal-01175843 , version 1 (13-07-2015)

Identifiants

  • HAL Id : hal-01175843 , version 1

Citer

Zhangyun Tan, Abdourrahmane Atto, Olivier Alata, Maxime Moreaud. ARFBF MODEL FOR NON STATIONARY RANDOM FIELDS AND APPLICATION IN HRTEM IMAGES. IEEE International Conference on Image Processing (ICIP) 2015, Sep 2015, Québec City, Canada. ⟨hal-01175843⟩
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