Image modeling using inverse filtering criteria with application to texture images

Author

Hall, Thomas E. ; Giannakis, Georgios B.

Author_Institution

Dept. of Electr. Eng., Virginia Univ., Charlottesville, VA, USA

Volume

3

fYear

1994

fDate

13-16 Nov 1994

Firstpage

392

Abstract

Higher-than second-order statistics are used in the paper to derive and implement two classes of inverse filtering criteria for consistent parameter estimation of asymmetric noncausal ARMA image models with known orders. Contrary to existing approaches, FIR inverse filters are employed and as a result image models with zeros on the unit bi-circle can be handled. The performance of these parameter estimators is evaluated with Monte Carlo simulations and texture classification experiments

Keywords

FIR filters; Monte Carlo methods; autoregressive moving average processes; digital filters; higher order statistics; image classification; image texture; inverse problems; parameter estimation; poles and zeros; FIR inverse filters; Monte Carlo simulations; asymmetric noncausal ARMA image models; image modeling; inverse filtering criteria; parameter estimation; texture classification experiments; texture images; unit bi-circle; zeros; Electronic mail; Filtering; Finite impulse response filter; Image processing; Image representation; Inverse problems; Parameter estimation; Phase estimation; Random processes; Statistics;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference

Conference_Location

Austin, TX

Print_ISBN

0-8186-6952-7

Type

conf

DOI

10.1109/ICIP.1994.413820

Filename

413820