DSpace Repository

Utilizarea filtrului Wiener pentru restabilirea imaginilor distorsionate prin focus blur și motion blur

Show simple item record

dc.contributor.author CAPCANARI, I.
dc.contributor.author LAZĂR, D.
dc.contributor.author GRIŢCOV, S.
dc.contributor.author POCOTILENCO, V.
dc.contributor.author SOROCHIN, G.
dc.date.accessioned 2019-07-17T07:54:34Z
dc.date.available 2019-07-17T07:54:34Z
dc.date.issued 2015
dc.identifier.citation CAPCANARI, I., LAZĂR, D., GRIŢCOV, S. et al. Utilizarea filtrului Wiener pentru restabilirea imaginilor distorsionate prin focus blur și motion blur. In: Telecomunicaţii, Electronică şi Informatică: proc. of the 5th intern. conf., May 20-23, 2015. Chişinău, 2015, pp. 353-356. ISBN 978-9975-45-377-6. en_US
dc.identifier.isbn 978-9975-45-377-6
dc.identifier.uri http://repository.utm.md/handle/5014/3587
dc.description.abstract Wiener theory, formulated by Norbert Wiener in 1940, forms the foundation of data-dependent linear least square error filters. Wiener filters play a central role in a wide range of applications such as linear prediction, echo cancellation, signal restoration, channel equalization and system identification. The coefficients of a Wiener filter are calculated to minimize the average squared distance between the filter output and a desired signal. In its basic form, the Wiener theory assumes that the signals are stationary processes. However, if the filter coefficients are periodically recalculated for every block of N signal samples then the filter adapts itself to the average characteristics of the signals within the blocks and becomes block-adaptive. A block-adaptive (or segment adaptive) filter can be used for signals such as speech and image that may be considered almost stationary over a relatively small block of samples. In this paper, we study Wiener filter theory, and consider alternative methods of formulation of the Wiener filter problem. We consider the application of Wiener filters in restoration of image for focus blure and motion blur and also additive noise reduction. A case study of the frequency response of a Wiener filter, for additive noise reduction, provides useful insight into the operation of the filter. We also deal with some implementation issues of Wiener filters. en_US
dc.language.iso ro en_US
dc.publisher Technical University of Moldova en_US
dc.rights Attribution-NonCommercial-NoDerivs 3.0 United States *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/us/ *
dc.subject optimal linear filters en_US
dc.subject Wiener filters en_US
dc.subject image restoration en_US
dc.subject distorted images en_US
dc.subject focus blur en_US
dc.subject motion blur en_US
dc.subject filtre liniare optimale en_US
dc.subject filtre Wiener en_US
dc.subject restabilirea imaginilor en_US
dc.subject imagini distorsionate en_US
dc.title Utilizarea filtrului Wiener pentru restabilirea imaginilor distorsionate prin focus blur și motion blur en_US
dc.type Article en_US


Files in this item

The following license files are associated with this item:

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 United States Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States

Search DSpace


Advanced Search

Browse

My Account