2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys
Today, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensiona...
Gespeichert in:
| Veröffentlicht in: | Publications of the Astronomical Society of Australia 2012-01, Vol.29 (3), p.244-250 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 250 |
|---|---|
| container_issue | 3 |
| container_start_page | 244 |
| container_title | Publications of the Astronomical Society of Australia |
| container_volume | 29 |
| creator | Flöer, L. Winkel, B. |
| description | Today, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensionality. In this paper we will review the basic method of denoising data by thresholding wavelet coefficients and implement a 2D–1D wavelet decomposition to obtain an efficient way of denoising spectroscopic data cubes. We conduct different simulations to evaluate the usefulness of the algorithm as part of a source finding pipeline. |
| doi_str_mv | 10.1071/AS11042 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1323816673</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cupid>10_1071_AS11042</cupid><sourcerecordid>1323816673</sourcerecordid><originalsourceid>FETCH-LOGICAL-c255t-7c7ab33f733f6d07714b02bf91206769175704abb0d0643507f694a93c8b4a003</originalsourceid><addsrcrecordid>eNplkM9Kw0AQxhdRsFbxFfamHqKzf7KbHEtrtVAQTMWLEDabTdmSZOtuUujNd_ANfRJT7M3DMAPzY-b7PoSuCdwTkORhkhECnJ6gEeE8iQQk7HSYGWURixM4RxchbAAIF5SO0Aed_Xx9kxl-VztTmw6_Gu3a0Pled9a1WAWs8Mq5GlfO48z1Xhs8t21p2zW2Lc62RnfeBe22VuNFo9aHRdb7ndmHS3RWqTqYq2Mfo7f542r6HC1fnhbTyTLSNI67SGqpCsYqOZQoQUrCC6BFlRIKQoqUyFgCV0UBJQjOYpCVSLlKmU4KrgDYGN3-3d1699mb0OWNDdrUtWqN60N-MJ8QIYYHY3Tzh-pBdPCmyrfeNsrvcwL5Ib_8mN9A3h1J1RTelmuTbwb77WDkH_sLREJuXw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1323816673</pqid></control><display><type>article</type><title>2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Cambridge University Press Journals Complete</source><creator>Flöer, L. ; Winkel, B.</creator><creatorcontrib>Flöer, L. ; Winkel, B.</creatorcontrib><description>Today, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensionality. In this paper we will review the basic method of denoising data by thresholding wavelet coefficients and implement a 2D–1D wavelet decomposition to obtain an efficient way of denoising spectroscopic data cubes. We conduct different simulations to evaluate the usefulness of the algorithm as part of a source finding pipeline.</description><identifier>ISSN: 1323-3580</identifier><identifier>EISSN: 1448-6083</identifier><identifier>EISSN: 1323-3580</identifier><identifier>DOI: 10.1071/AS11042</identifier><language>eng</language><publisher>Cambridge, UK: Cambridge University Press</publisher><subject>Algorithms ; Numerical simulations</subject><ispartof>Publications of the Astronomical Society of Australia, 2012-01, Vol.29 (3), p.244-250</ispartof><rights>Copyright © Astronomical Society of Australia 2012</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c255t-7c7ab33f733f6d07714b02bf91206769175704abb0d0643507f694a93c8b4a003</citedby><cites>FETCH-LOGICAL-c255t-7c7ab33f733f6d07714b02bf91206769175704abb0d0643507f694a93c8b4a003</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S1323358000001260/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,314,777,781,27905,27906,55609</link.rule.ids></links><search><creatorcontrib>Flöer, L.</creatorcontrib><creatorcontrib>Winkel, B.</creatorcontrib><title>2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys</title><title>Publications of the Astronomical Society of Australia</title><addtitle>Publ. Astron. Soc. Aust</addtitle><description>Today, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensionality. In this paper we will review the basic method of denoising data by thresholding wavelet coefficients and implement a 2D–1D wavelet decomposition to obtain an efficient way of denoising spectroscopic data cubes. We conduct different simulations to evaluate the usefulness of the algorithm as part of a source finding pipeline.</description><subject>Algorithms</subject><subject>Numerical simulations</subject><issn>1323-3580</issn><issn>1448-6083</issn><issn>1323-3580</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNplkM9Kw0AQxhdRsFbxFfamHqKzf7KbHEtrtVAQTMWLEDabTdmSZOtuUujNd_ANfRJT7M3DMAPzY-b7PoSuCdwTkORhkhECnJ6gEeE8iQQk7HSYGWURixM4RxchbAAIF5SO0Aed_Xx9kxl-VztTmw6_Gu3a0Pled9a1WAWs8Mq5GlfO48z1Xhs8t21p2zW2Lc62RnfeBe22VuNFo9aHRdb7ndmHS3RWqTqYq2Mfo7f542r6HC1fnhbTyTLSNI67SGqpCsYqOZQoQUrCC6BFlRIKQoqUyFgCV0UBJQjOYpCVSLlKmU4KrgDYGN3-3d1699mb0OWNDdrUtWqN60N-MJ8QIYYHY3Tzh-pBdPCmyrfeNsrvcwL5Ib_8mN9A3h1J1RTelmuTbwb77WDkH_sLREJuXw</recordid><startdate>20120101</startdate><enddate>20120101</enddate><creator>Flöer, L.</creator><creator>Winkel, B.</creator><general>Cambridge University Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>KL.</scope></search><sort><creationdate>20120101</creationdate><title>2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys</title><author>Flöer, L. ; Winkel, B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c255t-7c7ab33f733f6d07714b02bf91206769175704abb0d0643507f694a93c8b4a003</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Algorithms</topic><topic>Numerical simulations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Flöer, L.</creatorcontrib><creatorcontrib>Winkel, B.</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><jtitle>Publications of the Astronomical Society of Australia</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Flöer, L.</au><au>Winkel, B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys</atitle><jtitle>Publications of the Astronomical Society of Australia</jtitle><addtitle>Publ. Astron. Soc. Aust</addtitle><date>2012-01-01</date><risdate>2012</risdate><volume>29</volume><issue>3</issue><spage>244</spage><epage>250</epage><pages>244-250</pages><issn>1323-3580</issn><eissn>1448-6083</eissn><eissn>1323-3580</eissn><abstract>Today, image denoising by thresholding of wavelet coefficients is a commonly used tool for 2D image enhancement. Since the data product of spectroscopic imaging surveys has two spatial dimensions and one spectral dimension, the techniques for denoising have to be adapted to this change in dimensionality. In this paper we will review the basic method of denoising data by thresholding wavelet coefficients and implement a 2D–1D wavelet decomposition to obtain an efficient way of denoising spectroscopic data cubes. We conduct different simulations to evaluate the usefulness of the algorithm as part of a source finding pipeline.</abstract><cop>Cambridge, UK</cop><pub>Cambridge University Press</pub><doi>10.1071/AS11042</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1323-3580 |
| ispartof | Publications of the Astronomical Society of Australia, 2012-01, Vol.29 (3), p.244-250 |
| issn | 1323-3580 1448-6083 1323-3580 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1323816673 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Cambridge University Press Journals Complete |
| subjects | Algorithms Numerical simulations |
| title | 2D–1D Wavelet Reconstruction as a Tool for Source Finding in Spectroscopic Imaging Surveys |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-21T08%3A10%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=2D%E2%80%931D%20Wavelet%20Reconstruction%20as%20a%20Tool%20for%20Source%20Finding%20in%20Spectroscopic%20Imaging%20Surveys&rft.jtitle=Publications%20of%20the%20Astronomical%20Society%20of%20Australia&rft.au=Fl%C3%B6er,%20L.&rft.date=2012-01-01&rft.volume=29&rft.issue=3&rft.spage=244&rft.epage=250&rft.pages=244-250&rft.issn=1323-3580&rft.eissn=1448-6083&rft_id=info:doi/10.1071/AS11042&rft_dat=%3Cproquest_cross%3E1323816673%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1323816673&rft_id=info:pmid/&rft_cupid=10_1071_AS11042&rfr_iscdi=true |