Title :
Multipole-motivated reduced-state estimation
Author :
Fieguth, Paul W.
Author_Institution :
Dept. of Syst. Design Eng., Waterloo Univ., Ont., Canada
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;
Conference_Titel :
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-8821-1
DOI :
10.1109/ICIP.1998.723580
