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dc.contributor.authorMorgan, Huwcs
dc.contributor.authorDruckmüller, Miloslavcs
dc.date.accessioned2021-10-01T10:53:41Z
dc.date.available2021-10-01T10:53:41Z
dc.date.issued2014-08-01cs
dc.identifier.citationSolar Physics. 2014, vol. 289, issue 8, p. 2945-2955.en
dc.identifier.issn0038-0938cs
dc.identifier.other109713cs
dc.identifier.urihttp://hdl.handle.net/11012/201728
dc.description.abstractExtreme ultra-violet images of the corona contain information over a wide range of spatial scales, and different structures such as active regions, quiet Sun, and filament channels contain information at very different brightness regimes. Processing of these images is important to reveal information, often hidden within the data, without introducing artefacts or bias. It is also important that any process be computationally efficient, particularly given the fine spatial and temporal resolution of Atmospheric Imaging Assembly on the Solar Dynamics Observatory (AIA/SDO), and consideration of future higher resolution observations. A very efficient process is described here, which is based on localised normalising of the data at many different spatial scales. The method reveals information at the finest scales whilst maintaining enough of the larger-scale information to provide context. It also intrinsically flattens noisy regions and can reveal structure in off-limb regions out to the edge of the field of view. We also applied the method successfully to a white-light coronagraph observation.en
dc.formattextcs
dc.format.extent2945-2955cs
dc.format.mimetypeapplication/pdfcs
dc.language.isoencs
dc.publisherSpringercs
dc.relation.ispartofSolar Physicscs
dc.relation.urihttps://link.springer.com/article/10.1007%2Fs11207-014-0523-9cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectImage processingen
dc.subjectCoronaen
dc.titleMulti-Scale Gaussian Normalization for Solar Image Processingen
thesis.grantorVysoké učení technické v Brně. Fakulta strojního inženýrství. Ústav matematikycs
sync.item.dbidVAV-109713en
sync.item.dbtypeVAVen
sync.item.insts2021.10.01 12:53:41en
sync.item.modts2021.10.01 12:15:11en
dc.coverage.issue8cs
dc.coverage.volume289cs
dc.identifier.doi10.1007/s11207-014-0523-9cs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/0038-0938/cs
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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Creative Commons Attribution 4.0 International
Except where otherwise noted, this item's license is described as Creative Commons Attribution 4.0 International