In this paper the problem of texture image analysis in the presence of noise is examined from a higher-order statistical perspective. The objective is to develop analysis techniques through which robust texture characteristics are extracted. The approach taken involves the use of autoregressive models derived from joint second and third order cumulants. The paper describes the fundamental issues of the various components of the approach.<>


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Autoregressive modelling through joint and weighted second and third order statistics


    Contributors:


    Publication date :

    1994-01-01


    Size :

    275395 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    Autoregressive Modelling through Joint and Weighted Second and Third Order Statistics

    Stathaki, P. T. / Constantinides, A. G. / IEEE; Hong Kong Chapter of Signal Processing | British Library Conference Proceedings | 1994


    A Fast and Accurate Method for Evaluating Joint Second-Order PMD Statistics

    Forestieri, E. | British Library Online Contents | 2003


    Statistics of Second-Order PMD Depolarization

    Foschini, G. J. / Nelson, L. E. / Jopson, R. M. et al. | British Library Online Contents | 2001


    Second order fading statistics of UAV networks

    Jameel, Furqan / Faisal / Haider, M. Asif Ali et al. | IEEE | 2017


    Second-Order Cyclic Statistics for Mechanical Fault Diagnosis

    Li, L. / Liangsheng, Q. | British Library Online Contents | 2002