Diffracted Image Restoration: A Machine learning approach

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F13%3APU105721" target="_blank" >RIV/00216305:26220/13:PU105721 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICEAA.2013.6632375" target="_blank" >http://dx.doi.org/10.1109/ICEAA.2013.6632375</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICEAA.2013.6632375" target="_blank" >10.1109/ICEAA.2013.6632375</a>

Result language
angličtina
Original language name
Diffracted Image Restoration: A Machine learning approach
Original language description
Image restoration issues are closely connected with imaging systems, where image resolution is limited by diffraction phenomenon. The presented work is motivated by the super acuity of the Human vision, where the restoration step is implemented by some kind of parallel processor unit - neural network. The de-convolution process is formulated as a machine learning problem and the inverse operator is interpreted as a connectionist model.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 2013 International Conference on Electromagnetics in Advanced Applications
ISBN
978-1-4673-5705-0
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
931-934
Publisher name
COREP
Place of publication
Torino, Italy
Event location
Torino
Event date
Sep 9, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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