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Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/14163
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dc.contributor.authorGhamisi, Pedramen
dc.contributor.authorSepehrband, Farshiden
dc.contributor.authorKumar, Laliten
dc.contributor.authorCouceiro, Micael Sen
dc.contributor.authorMartins, Fernando M Len
dc.date.accessioned2014-03-06T15:48:00Z-
dc.date.issued2013-
dc.identifier.citationScienceAsia, 39(5), p. 546-555en
dc.identifier.issn1513-1874en
dc.identifier.urihttps://hdl.handle.net/1959.11/14163-
dc.description.abstractRemote sensing sensors generate useful information about climate and the Earth's surface, and are widely used in resource management, agriculture, and environmental monitoring. Compression of the RS data helps in long-term storage and transmission systems. Lossless compression is preferred for high-detail data, such as from remote sensing. In this paper, a less complex and efficient lossless compression method for images is introduced. It is based on improving the energy compaction ability of prediction models. The proposed method is applied to image processing, RS grey scale images, LiDAR rasterized data, and hyperspectral images. All the results are evaluated and compared with different lossless JPEG and a lossless version of JPEG2000, thus confirming that the proposed lossless compression method leads to a high speed transmission system because of a good compression ratio and simplicity.en
dc.languageenen
dc.publisherScience Society of Thailand under the Patronage of His Majesty the Kingen
dc.relation.ispartofScienceAsiaen
dc.titleA new method for compression of remote sensing images based on an enhanced differential pulse code modulation transformationen
dc.typeJournal Articleen
dc.identifier.doi10.2306/scienceasia1513-1874.2013.39.546en
dcterms.accessRightsGolden
dc.subject.keywordsGeospatial Information Systemsen
dc.subject.keywordsPhotogrammetry and Remote Sensingen
local.contributor.firstnamePedramen
local.contributor.firstnameFarshiden
local.contributor.firstnameLaliten
local.contributor.firstnameMicael Sen
local.contributor.firstnameFernando M Len
local.subject.for2008090905 Photogrammetry and Remote Sensingen
local.subject.for2008090903 Geospatial Information Systemsen
local.subject.seo2008960501 Ecosystem Assessment and Management at Regional or Larger Scalesen
local.subject.seo2008960906 Forest and Woodlands Land Managementen
local.profile.schoolSchool of Environmental and Rural Scienceen
local.profile.emaillkumar@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.identifier.epublicationsrecordune-20140214-143841en
local.publisher.placeThailanden
local.format.startpage546en
local.format.endpage555en
local.peerreviewedYesen
local.identifier.volume39en
local.identifier.issue5en
local.access.fulltextYesen
local.contributor.lastnameGhamisien
local.contributor.lastnameSepehrbanden
local.contributor.lastnameKumaren
local.contributor.lastnameCouceiroen
local.contributor.lastnameMartinsen
dc.identifier.staffune-id:lkumaren
local.profile.orcid0000-0002-9205-756Xen
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:14376en
local.identifier.handlehttps://hdl.handle.net/1959.11/14163en
dc.identifier.academiclevelAcademicen
local.title.maintitleA new method for compression of remote sensing images based on an enhanced differential pulse code modulation transformationen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorGhamisi, Pedramen
local.search.authorSepehrband, Farshiden
local.search.authorKumar, Laliten
local.search.authorCouceiro, Micael Sen
local.search.authorMartins, Fernando M Len
local.uneassociationUnknownen
local.identifier.wosid000330208300013en
local.year.published2013en
local.subject.for2020401304 Photogrammetry and remote sensingen
local.subject.for2020401302 Geospatial information systems and geospatial data modellingen
local.subject.seo2020180403 Assessment and management of Antarctic and Southern Ocean ecosystemsen
local.subject.seo2020180607 Terrestrial erosionen
local.subject.seo2020180603 Evaluation, allocation, and impacts of land useen
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