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rdf:type
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Description
| - Two restoration methods applied to the multitemporal solar images are presented. Our main goal is to model and remove degradation in a subimage, where a specific event is investigated. Using information of the input (blurred) channels within a short observed sequence a new undegraded image is reconstructed. Degradation is assumed to follow a linear degradation model with an unknown possibly non-homogeneous point spread function (PSF) and additive noise. The first method ({/bf VAM}) is based on multichannel blind deconvolution (MBD) using a variational approach to blur estimation, while the second one ({/bf SAM}) supposes solution of the multidimensional causal regressive model representing the degraded image (channel). Experimental image data are from the ground based observation (white light) and satellite SOHO mission - EIT (EUV). Contributions of both suggested methods and their generalization are discussed.
- Two restoration methods applied to the multitemporal solar images are presented. Our main goal is to model and remove degradation in a subimage, where a specific event is investigated. Using information of the input (blurred) channels within a short observed sequence a new undegraded image is reconstructed. Degradation is assumed to follow a linear degradation model with an unknown possibly non-homogeneous point spread function (PSF) and additive noise. The first method ({/bf VAM}) is based on multichannel blind deconvolution (MBD) using a variational approach to blur estimation, while the second one ({/bf SAM}) supposes solution of the multidimensional causal regressive model representing the degraded image (channel). Experimental image data are from the ground based observation (white light) and satellite SOHO mission - EIT (EUV). Contributions of both suggested methods and their generalization are discussed. (en)
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Title
| - Fine Structure Recognition in Multichannel Observations
- Fine Structure Recognition in Multichannel Observations (en)
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skos:prefLabel
| - Fine Structure Recognition in Multichannel Observations
- Fine Structure Recognition in Multichannel Observations (en)
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skos:notation
| - RIV/67985815:_____/12:00385357!RIV13-GA0-67985815
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - I, P(GA102/08/0593), P(GA102/08/1593), P(GAP103/11/1552)
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/67985815:_____/12:00385357
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - image restoration; image recognition (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
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http://linked.open...i/riv/nazevZdroje
| - International Conference on Digital Image Computing Techniques and Applications (DICTA) 2012
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...vavai/riv/projekt
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http://linked.open...UplatneniVysledku
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http://linked.open...iv/tvurceVysledku
| - Haindl, Michal
- Šroubek, Filip
- Šimberová, Stanislava
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http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
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number of pages
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http://purl.org/ne...btex#hasPublisher
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https://schema.org/isbn
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