DocumentCode :
2085137
Title :
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
Link To Document :
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