FAST MULTICHANNEL APPROACH TO ADAPTIVE ESTIMATION AND FILTERING OF TWO DIMENSIONAL IMAGES.

Boutalis, Yiannis; Kollias, Stefanos; Carayannis, George

dc.contributor.author	Boutalis, Yiannis	en
dc.contributor.author	Kollias, Stefanos	en
dc.contributor.author	Carayannis, George	en
dc.date.accessioned	2014-03-01T02:40:50Z
dc.date.available	2014-03-01T02:40:50Z
dc.date.issued	1987	en
dc.identifier.issn	07367791	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30246
dc.subject	Adaptive Estimation	en
dc.subject	Ar Model	en
dc.subject	Image Modeling	en
dc.subject	Parameter Estimation	en
dc.subject	Sliding Window	en
dc.subject	Fast Recursive Least Squares	en
dc.subject	Shift Invariant	en
dc.subject.other	MATHEMATICAL TECHNIQUES - Least Squares Approximations	en
dc.subject.other	SIGNAL FILTERING AND PREDICTION	en
dc.subject.other	AUTOREGRESSIVE MODELS	en
dc.subject.other	IMAGE PROCESSING	en
dc.title	FAST MULTICHANNEL APPROACH TO ADAPTIVE ESTIMATION AND FILTERING OF TWO DIMENSIONAL IMAGES.	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICASSP.1987.1169370	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICASSP.1987.1169370	en
heal.publicationDate	1987	en
heal.abstract	A fast, computationally efficient method for adaptive image estimation is presented. The method is based on the multichannel form of the fast a posteriori error sequential technique (FAEST) for the estimation of the parameters of two-dimensional autoregressive (AR) models. These models are designed to have the shift invariance property necessary for fast recursive least squares techniques. Inclusion of a forgetting factor, or of a sliding window in the algorithm, permits adaptive image model parameter estimation. The specific properties of the algorithm are examined and it is shown that the proposed estimation scheme is much faster than other existing approaches. Various interesting applications of the method are dicussed and examples are given which illustrate the theoretical results.	en
heal.publisher	IEEE, New York, NY, USA	en
heal.journalName	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings	en
dc.identifier.doi	10.1109/ICASSP.1987.1169370	en
dc.identifier.spage	1981	en
dc.identifier.epage	1984	en