DocumentCode
329533
Title
Multipole-motivated reduced-state estimation
Author
Fieguth, Paul W.
Author_Institution
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
Volume
1
fYear
1998
fDate
4-7 Oct 1998
Firstpage
635
Abstract
This paper discusses efficient solutions to large-scale two-dimensional estimation problems, using reduced state methods motivated by the multipole method of mathematical physics. The work is mainly exploratory, building on past efforts in multiscale statistical signal modeling and estimation. We will illustrate applications to the estimation of Markov random field textures, with the motivation and goal the estimation of remotely-sensed fields
Keywords
Markov processes; image texture; parameter estimation; remote sensing; state estimation; statistical analysis; Markov random field textures; large-scale 2D estimation problems; mathematical physics; multipole method; multipole-motivated reduced-state estimation; multiscale statistical signal estimation; multiscale statistical signal modeling; reduced state methods; remotely-sensed fields; Buildings; Decorrelation; Design engineering; Large-scale systems; Markov random fields; Physics; Recursive estimation; Remote sensing; State estimation; Systems engineering and theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location
Chicago, IL
Print_ISBN
0-8186-8821-1
Type
conf
DOI
10.1109/ICIP.1998.723580
Filename
723580
Link To Document