A novel coarse-to-fine remote sensing image retrieval system in JPEG-2000 compressed domain

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dc.contributor.authorPreethy Byju, Akshara
dc.contributor.authorDemir, Begüm
dc.contributor.authorBruzzone, Lorenzo
dc.date.accessioned2019-11-25T19:12:03Z
dc.date.available2019-11-25T19:12:03Z
dc.date.issued2018-10-09
dc.descriptionCopyright 2018 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.en
dc.description.abstractThis paper presents a novel content-based image search and retrieval (CBIR) system that achieves coarse to fine remote sensing (RS) image description and retrieval in JPEG 2000 compressed domain. The proposed system initially: i) decodes the code-streams associated to the coarse (i.e., the lowest) wavelet resolution, and ii) discards the most irrelevant images to the query image that are selected based on the similarities estimated among the coarse resolution features of the query image and those of the archive images. Then, the code-streams associated to the sub-sequent resolution of the remaining images in the archive are decoded and the most irrelevant images are selected by considering the features associated to both resolutions. This is achieved by estimating the similarities between the query image and remaining images by giving higher weights to the features associated to the finer resolution while assigning lower weights to those related to the coarse resolution. To this end, the pyramid match kernel similarity measure is exploited. These processes are iterated until the code-streams associated to the highest wavelet resolution are decoded only for a very small set of images. By this way, the proposed system exploits a multiresolution and hierarchical feature space and accomplish an adaptive RS CBIR with significantly reduced retrieval time. Experimental results obtained on an archive of aerial images confirm the effectiveness of the proposed system in terms of retrieval accuracy and time when compared to the standard CBIR systems.en
dc.identifier.eissn1996-756X
dc.identifier.isbn9781510621626
dc.identifier.isbn9781510621619
dc.identifier.issn0277-786X
dc.identifier.urihttps://depositonce.tu-berlin.de/handle/11303/10381
dc.identifier.urihttp://dx.doi.org/10.14279/depositonce-9341
dc.language.isoenen
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.ddc006 Spezielle Computerverfahrende
dc.subject.otherimage retrieval in compressed domainen
dc.subject.otherJPEG 2000 algorithmen
dc.subject.othercoarse to fine image retrievalen
dc.subject.otherremote sensingen
dc.titleA novel coarse-to-fine remote sensing image retrieval system in JPEG-2000 compressed domainen
dc.typeConference Objecten
dc.type.versionpublishedVersionen
dcterms.bibliographicCitation.articlenumber107890Ten
dcterms.bibliographicCitation.doi10.1117/12.2327051en
dcterms.bibliographicCitation.editorBruzzone, Lorenzo
dcterms.bibliographicCitation.editorBovolo, Francesca
dcterms.bibliographicCitation.originalpublishernameSPIEen
dcterms.bibliographicCitation.originalpublisherplaceBellingham, Wash.en
dcterms.bibliographicCitation.proceedingstitleProceedings of SPIE 10789 – Image and Signal Processing for Remote Sensing XXIVen
tub.accessrights.dnbfreeen
tub.affiliationFak. 4 Elektrotechnik und Informatik::Inst. Technische Informatik und Mikroelektronik::FG Remote Sensing Image Analysis Groupde
tub.affiliation.facultyFak. 4 Elektrotechnik und Informatikde
tub.affiliation.groupFG Remote Sensing Image Analysis Groupde
tub.affiliation.instituteInst. Technische Informatik und Mikroelektronikde
tub.publisher.universityorinstitutionTechnische Universität Berlinen

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