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Probabilistic suppression of astronomical degradations
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SYSNO ASEP 0080188 Druh ASEP A - Abstrakt Zařazení RIV Záznam nebyl označen do RIV Zařazení RIV Není vybrán druh dokumentu Název Probabilistic suppression of astronomical degradations Tvůrce(i) Haindl, Michal (UTIA-B) RID, ORCID
Šimberová, Stanislava (ASU-R) RIDZdroj.dok. Proceedings of Abstracts of Modern Solar Facilities - Advanced Solar Science. - Göttingen : Universitätsverlag Göttingen, 2007
s. 1-1Poč.str. 1 s. Akce Modern solar facilities - advanced solar science Datum konání 27.09.2006-29.09.2006 Místo konání Göttingen Země DE - Německo Typ akce WRD Jazyk dok. eng - angličtina Země vyd. DE - Německo Klíč. slova image restoration ; multichannel restoration Vědní obor RIV BD - Teorie informace CEP 1ET400750407 GA AV ČR - Akademie věd 1M0572 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy GA102/04/0155 GA ČR - Grantová agentura ČR CEZ AV0Z10750506 - UTIA-B (2005-2011) Anotace A multichannel fast adaptive recursive restoration method based on the underlying spatial probabilistic image model is presented. The method assumes linear degradation model with the unknown possibly non-homogeneous point-spread function and additive noise for each of mutually registered degraded observations. Pixels in the vicinity of image steep discontinuities are left unrestored to minimize restoration blurring effect. The method is completely autonomous and doesn't assume any knowledge of the underlying degradation process. The algorithm is verified on the artificial data with known ideal image. In the multichannel input are blurred channels created from the ideal image using various degradation functions. Then the method is applied to the real optical solar data. The experiments are carried on the synthetic data set and on a sequence of the short-exposure solar photosphere images. The multichannel input is presented by the temporal plains of a data cube. The results are compared under the most frequented criterions of image quality. The method can be also easily and naturally generalized for multispectral (e.g. colour, multispectral satellite images) or registered images which is seldom the case for alternative methods. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2007
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