On the optimality of a new class of 2D recursive filters

Leopoldo Jetto

Kybernetika (1999)

  • Volume: 35, Issue: 6, page [777]-792
  • ISSN: 0023-5954

Abstract

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The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures based on strip processing. Experimental results show the effectiveness of the new filtering schemes.

How to cite

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Jetto, Leopoldo. "On the optimality of a new class of 2D recursive filters." Kybernetika 35.6 (1999): [777]-792. <http://eudml.org/doc/33462>.

@article{Jetto1999,
abstract = {The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures based on strip processing. Experimental results show the effectiveness of the new filtering schemes.},
author = {Jetto, Leopoldo},
journal = {Kybernetika},
keywords = {minimum variance property; finite-dimensional filter; Gaussian random field; 2D recursive filters; strip processing; image pixels; minimum variance property; finite-dimensional filter; Gaussian random field; 2D recursive filters; strip processing; image pixels},
language = {eng},
number = {6},
pages = {[777]-792},
publisher = {Institute of Information Theory and Automation AS CR},
title = {On the optimality of a new class of 2D recursive filters},
url = {http://eudml.org/doc/33462},
volume = {35},
year = {1999},
}

TY - JOUR
AU - Jetto, Leopoldo
TI - On the optimality of a new class of 2D recursive filters
JO - Kybernetika
PY - 1999
PB - Institute of Information Theory and Automation AS CR
VL - 35
IS - 6
SP - [777]
EP - 792
AB - The purpose of this paper is to prove the minimum variance property of a new class of 2D, recursive, finite-dimensional filters. The filtering algorithms are derived from general basic assumptions underlying the stochastic modelling of an image as a 2D gaussian random field. An appealing feature of the proposed algorithms is that the image pixels are estimated one at a time; this makes it possible to save computation time and memory requirement with respect to the filtering procedures based on strip processing. Experimental results show the effectiveness of the new filtering schemes.
LA - eng
KW - minimum variance property; finite-dimensional filter; Gaussian random field; 2D recursive filters; strip processing; image pixels; minimum variance property; finite-dimensional filter; Gaussian random field; 2D recursive filters; strip processing; image pixels
UR - http://eudml.org/doc/33462
ER -

References

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