Targeted Iterative Filtering

Targeted Iterative Filtering

The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different behavior of the applied denoising method. In this paper we propose a novel, nonlinear diffusion scheme that is derived...

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Main Authors: Åström, Freddie, Felsberg, Michael, Baravdish, George, Lundström, Claes
Format: Others
Language:English
Published: Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV 2013
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-89674
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spelling ndltd-UPSALLA1-oai-DiVA.org-liu-896742013-05-31T04:02:25ZTargeted Iterative FilteringengÅström, FreddieFelsberg, MichaelBaravdish, GeorgeLundström, ClaesLinköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIVLinköpings universitet, DatorseendeLinköpings universitet, Tekniska högskolanLinköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIVLinköpings universitet, DatorseendeLinköpings universitet, Tekniska högskolanLinköpings universitet, Kommunikations- och transportsystemLinköpings universitet, Tekniska högskolanLinköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIVLinköpings universitet, Medie- och InformationsteknikLinköpings universitet, Tekniska högskolan2013The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different behavior of the applied denoising method. In this paper we propose a novel, nonlinear diffusion scheme that is derived from a linear diffusion process in a value space determined by the application. We show that application-driven linear diffusion in the transformed space compares favorably with existing nonlinear diffusion techniques.  VIDIGARNICSSM10-002BILDLABConference paperinfo:eu-repo/semantics/conferenceObjecttexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-89674Lecture Notes in Computer Science, 0302-9743 (print), 1611-3349 (online) ; 7893, p. 1-11application/pdfinfo:eu-repo/semantics/openAccess
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language English
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sources NDLTD
description The assessment of image denoising results depends on the respective application area, i.e. image compression, still-image acquisition, and medical images require entirely different behavior of the applied denoising method. In this paper we propose a novel, nonlinear diffusion scheme that is derived from a linear diffusion process in a value space determined by the application. We show that application-driven linear diffusion in the transformed space compares favorably with existing nonlinear diffusion techniques.  === VIDI === GARNICS === SM10-002 === BILDLAB
author Åström, Freddie
Felsberg, Michael
Baravdish, George
Lundström, Claes
spellingShingle Åström, Freddie
Felsberg, Michael
Baravdish, George
Lundström, Claes
Targeted Iterative Filtering
author_facet Åström, Freddie
Felsberg, Michael
Baravdish, George
Lundström, Claes
author_sort Åström, Freddie
title Targeted Iterative Filtering
title_short Targeted Iterative Filtering
title_full Targeted Iterative Filtering
title_fullStr Targeted Iterative Filtering
title_full_unstemmed Targeted Iterative Filtering
title_sort targeted iterative filtering
publisher Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV
publishDate 2013
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-89674
work_keys_str_mv AT astromfreddie targetediterativefiltering
AT felsbergmichael targetediterativefiltering
AT baravdishgeorge targetediterativefiltering
AT lundstromclaes targetediterativefiltering
_version_ 1716586574563508224

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