DocumentCode
3013739
Title
Markov image modeling
Author
Woods, J.W.
Author_Institution
Rensselaer Polytechnic Institute, Troy, New York
fYear
1976
fDate
1-3 Dec. 1976
Firstpage
596
Lastpage
600
Abstract
The theory of two-dimensional spectral factorization is reviewed in the context of recursive modeling. The role of the Markov random field in recursive image modeling is then presented, Since spectral factorization in two-or higher-dimensions generally results in infinite order factors, it is necessary to perform Markov modeling after spectral factorization. The above concepts are then applied to the problem of Kalman filtering of images.
Keywords
Gaussian noise; Kalman filters;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control including the 15th Symposium on Adaptive Processes, 1976 IEEE Conference on
Conference_Location
Clearwater, FL, USA
Type
conf
DOI
10.1109/CDC.1976.267799
Filename
4045659
Link To Document