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.<>
Autoregressive modelling through joint and weighted second and third order statistics
1994-01-01
275395 byte
Conference paper
Electronic Resource
English
Autoregressive Modelling through Joint and Weighted Second and Third Order Statistics
British Library Conference Proceedings | 1994
|A Fast and Accurate Method for Evaluating Joint Second-Order PMD Statistics
British Library Online Contents | 2003
|Statistics of Second-Order PMD Depolarization
British Library Online Contents | 2001
|Second order fading statistics of UAV networks
IEEE | 2017
|Second-Order Cyclic Statistics for Mechanical Fault Diagnosis
British Library Online Contents | 2002
|