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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
isadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W/3FCL5B3
Repositorysid.inpe.br/plutao/2013/12.12.15.36.55
Last Update2015:03.10.17.58.57 (UTC) administrator
Metadata Repositorysid.inpe.br/plutao/2013/12.12.15.36.56
Metadata Last Update2022:06.09.22.25.52 (UTC) administrator
Labellattes: 7832536123089184 1 TorresFrer:2013:SAImDe
Citation KeyTorresFrer:2013:SAImDe
TitleSAR Image Despeckling Algorithms using Stochastic Distances and Nonlocal Means
FormatDVD; On-line.
Year2013
Access Date2024, Apr. 28
Secondary TypePRE CI
Number of Files1
Size1988 KiB
2. Context
Author1 Torres, Leonardo José Tenório Mourão
2 Frery, Alejandro César
Group1 CAP-COMP-SPG-INPE-MCTI-GOV-BR
Affiliation1 Instituto Nacional de Pesquisas Espaciais (INPE)
2 Universidade Federal de Alagoas (UFAL)
Author e-Mail Address1 ljmtorres@gmail.com
2 acfrery@gmail.com
EditorFalcão, Alexandre
Paulovich, Fernando
e-Mail Addressljmtorres@gmail.com
Conference NameConference on Graphics, Patterns and Images, 26 (SIBGRAPI).
Conference LocationArequipa, Peru
Date5-8 Aug. 2013
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Pages1-6
Book TitleProceedings
Tertiary TypeMaster's or Doctoral Works
History (UTC)2013-12-12 15:36:56 :: lattes -> administrator ::
2022-06-09 22:25:52 :: administrator -> :: 2013
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typefinaldraft
KeywordsImagens SAR
Speckle reduction
Stochastic distances
Information theory
AbstractThis paper presents two approaches for filter design based on stochastic distances for intensity speckle reduction. A window is defined around each pixel, overlapping samples are compared and only those which pass a goodness-of-fit test are used to compute the filtered value. The tests stem from stochastic divergences within the Information Theory framework. The technique is applied to intensity Synthetic Aperture Radar (SAR) data with homogeneous regions using the Gamma model. The first approach uses a Nagao-Matsuyama-type procedure for setting the overlapping samples, and the second uses the nonlocal method. The proposals are compared with the Improved Sigma filter and with anisotropic diffusion for speckled data (SRAD) using a protocol based on Monte Carlo simulation. Among the criteria used to quantify the quality of filters, we employ the equivalent number of looks, and line and edge preservation. Moreover, we also assessed the filters by the Universal Image Quality Index and by the Pearson correlation between edges. Applications to real images are also discussed. The proposed methods show good results.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção pgr ATUAIS > CAP > SAR Image Despeckling...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Contentthere are no files
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGP3W/3FCL5B3
zipped data URLhttp://urlib.net/zip/8JMKD3MGP3W/3FCL5B3
Languageen
Target FileTorres_sar.pdf
User Grouplattes
marcelo.pazos@inpe.br
Reader Groupadministrator
marcelo.pazos@inpe.br
Visibilityshown
Read Permissionallow from all
Update Permissionnot transferred
5. Allied materials
Mirror Repositoryiconet.com.br/banon/2006/11.26.21.31
Next Higher Units8JMKD3MGPCW/3F2PHGS
URL (untrusted data)http://www.ucsp.edu.pe/sibgrapi2013/eproceedings
Host Collectiondpi.inpe.br/plutao@80/2008/08.19.15.01
sid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist callnumber copyholder copyright creatorhistory descriptionlevel dissemination doi edition isbn issn lineage mark nextedition notes numberofvolumes orcid organization parameterlist parentrepositories previousedition previouslowerunit progress project resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark serieseditor session shorttitle sponsor subject tertiarymark type volume


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