| Bispectral analysis and model validation of texture images. | |
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MedLine Citation:
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PMID: 18290049 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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Statistical approaches to texture analysis and synthesis have largely relied upon random models that characterize the 2-D process in terms of its first- and second-order statistics, and therefore cannot completely capture phase properties of random fields that are non-Gaussian and/or asymmetric. In this paper, higher than second-order statistics are used to derive and implement 2-D Gaussianity, linearity, and spatial reversibility tests that validate the respective modeling assumptions. The nonredundant region of the 2-D bispectrum is correctly defined and proven. A consistent parameter estimator for nonminimum phase, asymmetric noncausal, 2-D ARMA models is derived by minimizing a quadratic error polyspectrum matching criterion. Simulations on synthetic data are performed and the results of the bispectral analysis on real textures are reported. |
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Authors:
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T E Hall; G B Giannakis |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Volume: 4 ISSN: 1057-7149 ISO Abbreviation: IEEE Trans Image Process Publication Date: 1995 |
Date Detail:
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Created Date: 2008-02-21 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9886191 Medline TA: IEEE Trans Image Process Country: United States |
Other Details:
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Languages: eng Pagination: 996-1009 Citation Subset: - |
Affiliation:
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Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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