Formula for the steady-state gain of a recursive estimator

Access Full Text

Formula for the steady-state gain of a recursive estimator

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A formula for the direct computation of the steady-state gain of a recursive estimator is derived. The estimator is presented as a general 3-D recursive filter for noise smoothing of 3-D wide-sense Markov fields. The 1-D and 2-D estimators are special cases of the general filter presented. The filter with its steady-state gain computed from the derived formula is very useful because of its computational efficiency.

Inspec keywords: picture processing; estimation theory; noise; filtering and prediction theory; Markov processes

Other keywords: noise smoothing; direct computation; 3-D recursive filter; recursive estimator; computational efficiency; image processing; one-dimensional estimators; 3-D wide-sense Markov fields; steady-state gain; 2-D estimators

Subjects: Optical information, image and video signal processing; Pattern recognition

References

    1. 1)
      • M.G. Strintzis . Comments on Two-dimensional Bayesian estimate of Images. Proc. IEEE , 1255 - 1257
    2. 2)
      • A. Rosenfeld , A.C. Kak . (1982) , Digital picture processing.
    3. 3)
      • Biemond, J.: `Image restoration: A linear stochastic filtering approach', 1982, PhD Dissertation, Delft University of Technology, Department of Electrical Engineering, The Netherlands.
    4. 4)
      • A. Habibi . Two-dimensional Bayesian estimate of images. Proc. IEEE , 7 , 878 - 883
    5. 5)
      • Katsaggelos, A.K., Driessen, J.N., Efstratiadis, S.N., Lagenduk, R.L.: `Spatio-temporal motion compensated noise filtering of image sequences', Proc SPIE Conf. Visual Commun. and Image Processing IV, 1989, 1199, p. 61–70.
http://iet.metastore.ingenta.com/content/journals/10.1049/el_19901076
Loading

Related content

content/journals/10.1049/el_19901076
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading