Kalman Filter Employment in Image Processing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F20%3A50017046" target="_blank" >RIV/62690094:18450/20:50017046 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-58799-4_60" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-58799-4_60</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-58799-4_60" target="_blank" >10.1007/978-3-030-58799-4_60</a>
Alternative languages
Result language
angličtina
Original language name
Kalman Filter Employment in Image Processing
Original language description
The Kalman filter is a classical algorithm of estimation and control theory. Its use in image processing is not very well known as it is not its typical application area. The paper deals with the presentation and demonstration of selected possibilities of using the Kalman filter in image processing. Particular attention is paid to problems of image noise filtering and blurred image restoration. The contribution presents the reduced update Kalman filter algorithm, that can be used to solve both the tasks. The construction of the image model, which is the necessary first step prior to the application of the algorithm itself, is briefly mentioned too. The described procedures are then implemented in the MATLAB software and the results are presented and discussed in the paper.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computational Science and Its Applications – ICCSA 2020, Lecture Notes in Computer Science
ISBN
978-3-030-58798-7
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
12
Pages from-to
833-844
Publisher name
Springer
Place of publication
Cham
Event location
Cagliari
Event date
Jul 1, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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