Detail výsledku

Diffracted Image Restoration: A Machine learning approach

KOUDELKA, V.; DEL RIO BOCIO, C.; RAIDA, Z. Diffracted Image Restoration: A Machine learning approach. In Proceedings of 2013 International Conference on Electromagnetics in Advanced Applications. Torino, Italy: COREP, 2013. p. 931-934. ISBN: 978-1-4673-5705-0.
Typ
článek ve sborníku konference
Jazyk
angličtina
Autoři
Koudelka Vlastimil, Ing., Ph.D., REL-SIX (FEKT), UREL (FEKT)
DEL RIO BOCIO, C.
Raida Zbyněk, prof. Dr. Ing., REL-SIX (FEKT), UREL (FEKT)
Abstrakt

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.

Klíčová slova

Diffraction, Image restoration, Imaging, Noise, Sensors, Stability analysis, Training

Rok
2013
Strany
931–934
Sborník
Proceedings of 2013 International Conference on Electromagnetics in Advanced Applications
Konference
International Conference on Electromagnetics in Advanced Applications (ICEAA) 2013
ISBN
978-1-4673-5705-0
Vydavatel
COREP
Místo
Torino, Italy
DOI
10.1109/ICEAA.2013.6632375
BibTeX 
@inproceedings{BUT102451,
  author="KOUDELKA, V. and DEL RIO BOCIO, C. and RAIDA, Z.",
  title="Diffracted Image Restoration: A Machine learning approach",
  booktitle="Proceedings of 2013 International Conference on Electromagnetics in Advanced Applications",
  year="2013",
  pages="931--934",
  publisher="COREP",
  address="Torino, Italy",
  doi="10.1109/ICEAA.2013.6632375",
  isbn="978-1-4673-5705-0"
}
Pracoviště
Ústav radioelektroniky (UREL)
Nahoru