BMINSAR: A NOVEL APPROACH FOR INSAR PHASE DENOISING BY CLUSTERING AND BLOCK MATCHING

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dc.contributor.authorBarreto, Thiago L. M.
dc.contributor.authorRosa, Rafael A. S.
dc.contributor.authorWimmer, Christian
dc.contributor.authorMoreira, Joao R.
dc.contributor.authorBins, Leonardo S.
dc.contributor.authorAlmeida, Jurandy [UNIFESP]
dc.contributor.authorCappabianco, Fabio A. M. [UNIFESP]
dc.coverageNew York
dc.date.accessioned2020-07-17T14:03:18Z
dc.date.available2020-07-17T14:03:18Z
dc.date.issued2017
dc.description.abstractWe present a novel approach for phase denoising in Interferometric Synthetic Aperture Radar (InSAR) images, named as Block-Matching InSAR (BMInSAR). It uses k-means clustering to solve the block matching similarity search problem, thus simplifying preprocessing steps and filtering several reference-blocks at once. Also, we propose a novel methodology based on ground-truth GPS measurements to assess the filtering quality of Digital Elevation Models (DEMs) derived from a pair of Very High-Resolution (VHR) SAR complex images. Our dataset was obtained by X-Band airborne sensor OrbiSAR-2 from BRADAR. BMInSAR significantly outperforms the state-of-the-art filtering methods in both accuracy and execution time. After filtering with BMInSAR, we achieved an accuracy of 21 cm in the resulting DEM of a homogeneous lawn area, which is quite similar to that obtained by LiDAR technology.en
dc.description.affiliationBradar Ind, Dept Remote Sensing Engn, BR-12244000 Sao Jose Dos Campos, SP, Brazil
dc.description.affiliationNatl Inst Space Res INPE, BR-12227010 Sao Jose Dos Campos, SP, Brazil
dc.description.affiliationFed Univ Sao Paulo UNIFESP, Inst Sci & Technol, BR-12247014 Sao Jose Dos Campos, SP, Brazil
dc.description.affiliationUnifespFed Univ Sao Paulo UNIFESP, Inst Sci & Technol, BR-12247014 Sao Jose Dos Campos, SP, Brazil
dc.description.sourceWeb of Science
dc.description.sponsorshipFAPESP
dc.description.sponsorshipCNPq
dc.description.sponsorshipCAPES
dc.description.sponsorshipIDFAPESP: 2016/06441-7
dc.format.extent2357-2360
dc.identifierhttps://doi.org/10.1109/IGARSS.2017.8127464
dc.identifier.citation2017 Ieee International Geoscience And Remote Sensing Symposium (Igarss). New York, v. , p. 2357-2360, 2017.
dc.identifier.doi10.1109/IGARSS.2017.8127464
dc.identifier.issn2153-6996
dc.identifier.urihttps://repositorio.unifesp.br/handle/11600/55295
dc.identifier.wosWOS:000426954602120
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartof2017 Ieee International Geoscience And Remote Sensing Symposium (Igarss)
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectRemote Sensingen
dc.subjectInSARen
dc.subjectBM3Den
dc.subjectNon Local Meansen
dc.subjectInterferometric Phase Denoisingen
dc.titleBMINSAR: A NOVEL APPROACH FOR INSAR PHASE DENOISING BY CLUSTERING AND BLOCK MATCHINGen
dc.typeinfo:eu-repo/semantics/conferenceObject
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