Bispectral-based test for spatial reversibility with application to texture images

Thomas E. Hall, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Statistical approaches to image-modeling have largely relied upon random models which characterize the 2-D process in terms of its first-and second-order statistics and therefore cannot completely capture phase properties of random fields which are non-Gaussian. This constrains the parameters of non-causal image models to be symmetric and therefore the underlying random field to be spatially reversible. In this paper, higher-than second-order statistics are used to derive and implement a spatial reversibility test to validate this modeling assumption and consequently determine if higher-order statistic would be more appropriate for modeling an image. The performance of this test is analyzed both theoretically and experimentally and then applied to texture images.

Original languageEnglish (US)
Title of host publicationConference Record of the Asilomar Conference on Signals, Systems & Computers
EditorsAvtar Singh
PublisherPubl by IEEE
Pages456-460
Number of pages5
ISBN (Print)0818641207
StatePublished - Dec 1 1993
EventProceedings of the 27th Asilomar Conference on Signals, Systems & Computers - Pacific Grove, CA, USA
Duration: Nov 1 1993Nov 3 1993

Publication series

NameConference Record of the Asilomar Conference on Signals, Systems & Computers
Volume1
ISSN (Print)1058-6393

Other

OtherProceedings of the 27th Asilomar Conference on Signals, Systems & Computers
CityPacific Grove, CA, USA
Period11/1/9311/3/93

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