Number of the records: 1

Probabilistic suppression of astronomical degradations

SYSNO ASEP	0080188
Document Type	A - Abstract
R&D Document Type	The record was not marked in the RIV
R&D Document Type	Není vybrán druh dokumentu
Title	Probabilistic suppression of astronomical degradations
Author(s)	Haindl, Michal (UTIA-B)_{RID, ORCID} Šimberová, Stanislava (ASU-R)_RID
Source Title	Proceedings of Abstracts of Modern Solar Facilities - Advanced Solar Science. - Göttingen : Universitätsverlag Göttingen, 2007 s. 1-1
Number of pages	1 s.
Action	Modern solar facilities - advanced solar science
Event date	27.09.2006-29.09.2006
VEvent location	Göttingen
Country	DE - Germany
Event type	WRD
Language	eng - English
Country	DE - Germany
Keywords	image restoration ; multichannel restoration
Subject RIV	BD - Theory of Information
R&D Projects	1ET400750407 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR)
	1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS)
	GA102/04/0155 GA ČR - Czech Science Foundation (CSF)
CEZ	AV0Z10750506 - UTIA-B (2005-2011)
Annotation	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.
Workplace	Institute of Information Theory and Automation
Contact	Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Year of Publishing	2007

Number of the records: 1