Show simple item record

dc.contributor.authorDeborah, Hilda
dc.contributor.authorRichard, Noël
dc.date.accessioned2021-10-28T08:31:30Z
dc.date.available2021-10-28T08:31:30Z
dc.date.created2021-08-12T13:03:20Z
dc.date.issued2021
dc.identifier.issn2158-6276
dc.identifier.urihttps://hdl.handle.net/11250/2826190
dc.description.abstractA metrological extension of morphological granulometry for the hyperspectral domain is introduced in this work. This development is enabled by the latest study of a suitable ordering relation for hyperspectral images. With granulometry as a texture descriptor, a suitable similarity measure for it is also introduced. In addition to providing validation experiments to the extension, a preliminary result in a texture discrimination task can also be found in this work.en_US
dc.language.isoengen_US
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en_US
dc.titleMorphological Texture Description For Hyperspectral Images: Pattern Spectrumen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.source.journalWorkshop on Hyperspectral Image and Signal Processing, Evolution in Remote Sensingen_US
dc.identifier.doi10.1109/WHISPERS52202.2021.9484052
dc.identifier.cristin1925580
dc.relation.projectNorges forskningsråd: 274881en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record