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231223s1995 xx ||||| 00| ||eng c |
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|a (NLM)18290049
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|a DE-627
|b ger
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|e rakwb
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|a eng
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| 100 |
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|a Hall, T E
|e verfasserin
|4 aut
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|a Bispectral analysis and model validation of texture images
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|c 1995
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|a Text
|b txt
|2 rdacontent
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|a ohne Hilfsmittel zu benutzen
|b n
|2 rdamedia
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|a Band
|b nc
|2 rdacarrier
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| 500 |
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|a Date Completed 02.10.2012
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|a Date Revised 21.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a 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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|a Journal Article
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|a Giannakis, G B
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
|d 1992
|g 4(1995), 7 vom: 15., Seite 996-1009
|w (DE-627)NLM09821456X
|x 1941-0042
|7 nnas
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| 773 |
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|g volume:4
|g year:1995
|g number:7
|g day:15
|g pages:996-1009
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|d 4
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