About: Image Extrapolation using sparse methods

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Image extrapolation is the specific application in image processing. You have to extrapolate the image for example when you want to process the given image piecewise. When the border patches are incompleted you must extrapolate them to the given size. Nowadays,some basic extrapolations, e.g. linear, polynomial etc. are used. The advanced methods are presented in this paper. We are using the algorithms that are based on finding the sparse solutions in underdetermined systems of linear equations. Three algorithms are presented for image extrapolation. First one is the K-SVD algorithm. K-SVD is the algorithm that trains a dictionary which allows the optimal sparse representation. Second one is Morphological Component Analysis (MCA) which is based on Independent Component Analysis (ICA). The last is the Expectation Maximization (EM) algorithm. This algorithm is statistics-based. These three algorithms for image extrapolation are compared on the real images. Image extrapolation is the specific application in image processing. You have to extrapolate the image for example when you want to process the given image piecewise. When the border patches are incompleted you must extrapolate them to the given size. Nowadays,some basic extrapolations, e.g. linear, polynomial etc. are used. The advanced methods are presented in this paper. We are using the algorithms that are based on finding the sparse solutions in underdetermined systems of linear equations. Three algorithms are presented for image extrapolation. First one is the K-SVD algorithm. K-SVD is the algorithm that trains a dictionary which allows the optimal sparse representation. Second one is Morphological Component Analysis (MCA) which is based on Independent Component Analysis (ICA). The last is the Expectation Maximization (EM) algorithm. This algorithm is statistics-based. These three algorithms for image extrapolation are compared on the real images. (en)
Title	Image Extrapolation using sparse methods Image Extrapolation using sparse methods (en)
skos:prefLabel	Image Extrapolation using sparse methods Image Extrapolation using sparse methods (en)
skos:notation	RIV/00216305:26220/13:PU104292!RIV15-MSM-26220___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ED2.1.00/03.0072), S
http://linked.open...iv/cisloPeriodika	2a
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Špiřík, Jan Zátyik, Ján
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	78854
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/13:PU104292
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	image extrapolation, sparse, K-SVD, MCA, EM (en)
http://linked.open.../riv/klicoveSlovo	EM MCA sparse K-SVD image extrapolation
http://linked.open...odStatuVydavatele	SK - Slovenská republika
http://linked.open...ontrolniKodProRIV	[5818367853D3]
http://linked.open...i/riv/nazevZdroje	Communications
http://linked.open...in/vavai/riv/obor	JA
http://linked.open...ichTvurcuVysledku	2 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...vavai/riv/projekt	Centre of sensor, information and communication systems
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	2013
http://linked.open...iv/tvurceVysledku	Špiřík, Jan Zátyik, Ján
issn	1335-4205
number of pages	6 (xsd:int)
http://localhost/t...ganizacniJednotka	26220

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