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dc.contributor.authorWestenberg, Michael A.
dc.contributor.authorErtl, Thomas
dc.contributor.editorSkala, Václav
dc.date.accessioned2013-03-07T07:41:33Z
dc.date.available2013-03-07T07:41:33Z
dc.date.issued2005
dc.identifier.citationJournal of WSCG. 2005, vol. 13, no. 1, p. 33-40.en
dc.identifier.issn1213–6964 (online)
dc.identifier.issn1213–6980 (CD-ROM)
dc.identifier.issn1213–6972 (hardcover)
dc.identifier.urihttp://wscg.zcu.cz/WSCG2005/Papers_2005/Journal/!WSCG2005_Journal_Final.pdf
dc.identifier.urihttp://hdl.handle.net/11025/1457
dc.description.abstractNoise reduction is an important preprocessing step for many visualization techniques that make use of feature extraction. We propose a method for denoising 2-D vector fields that are corrupted by additive noise. The method is based on the vector wavelet transform, which transforms a vector input signal to wavelet coefficients that are also vectors. We introduce modifications to scalar wavelet coefficient thresholding for dealing with vector-valued coefficients. We compare our wavelet-based denoising method with Gaussian filtering, and test the effect of these methods on the signal-to-noise ratio (SNR) of the vector fields before and after denoising. We also compare our method with component-wise scalar wavelet thresholding. Furthermore, we use a vortex measure to study the performances of the methods for retaining relevant details for visualization. The results show that for very low SNR, Gaussian filtering with large kernels has a slightly better performance than the wavelet-based method in terms of SNR. For larger SNR, the wavelet-based method outperforms Gaussian filtering, because Gaussian filtering removes small details that are preserved by the wavelet-based method. Component-wise denoising has a lower performance than our method.en
dc.format8 s.
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectredukce šumucs
dc.subjectvizualizace tokucs
dc.subject2D vektorová polecs
dc.titleDenoising 2-D vector fields by vector wavelet thresholdingen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatednoise reductionen
dc.subject.translatedflow visualizationen
dc.subject.translated2D vector fieldsen
dc.type.statusPeer-revieweden
Appears in Collections:Volume 13, Number 1-3 (2005)

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