Efficient two-dimensional ARX modeling

Author

Glentis, George-Othon ; Slump, Cornelis H. ; Herrmann, Otto E.

Author_Institution

Dept. of Electr. Eng., Twente Univ., Enschede, Netherlands

Volume

2

fYear

1994

fDate

13-16 Nov 1994

Firstpage

605

Abstract

In this paper a fast spatial adaptive algorithm is presented for the efficient least squares (LS), autoregressive exogenous (ARX), two-dimensional (2-D) modeling. Filter masks of general boundaries are allowed. Efficient space updating recursions are developed by exploiting the spatial shift invariance property of the 2-D data set

Keywords

adaptive filters; adaptive signal processing; autoregressive processes; image processing; least squares approximations; parameter estimation; two-dimensional digital filters; 2-D data set; 2-D spectral estimation; autoregressive exogenous 2D modeling; edge detection; fast spatial adaptive algorithm; filter masks; general boundaries; image compression; image enhancement; image restoration; image sequences; least squares modeling; parameter estimation; space updating recursions; spatial shift invariance property; stochastic texture modeling; system identification; two-dimensional ARX modeling; Computer networks; Control engineering computing; Control systems; Equations; Finite impulse response filter; Image edge detection; Least squares methods; Shape; Systems engineering and theory; Vectors;

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.1994.413642

Filename

413642