elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Impressum | Datenschutz | Kontakt | English
Schriftgröße: [-] Text [+]

Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery

Palubinskas, Gintautas (2016) Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, XLI-B7, Seiten 693-702. ISPRS. ISPRS 2016, 2016-07-12 - 2016-07-19, Prague, Czech Republic. doi: 10.5194/isprsarchives-XLI-B7-693-2016. ISSN 1682-1750.

[img] PDF
5MB

Offizielle URL: http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLI-B7/693/2016/isprs-archives-XLI-B7-693-2016.pdf

Kurzfassung

Model based analysis or explicit definition/listing of all models or assumptions used in the derivation of a pan-sharpening method allows us to understand the rationale or properties of existing methods and shows a way for a proper usage or proposal/selection of new methods ‘better’ satisfying the needs of a particular application. Most existing pan-sharpening methods are based mainly on the two models or assumptions: spectral consistency for high resolution multispectral data (physical relationship between multispectral and panchromatic data in a high resolution scale) and spatial consistency for multispectral data (so-called Wald’s protocol first property or relationship between multispectral data in different resolution scales). Additionally, it can be seen/shown easily that the following two popular groups of methods: spectral transformation (e.g. Intensity-Hue-Saturation (HIS), Principal Component Analysis (PCA), Gram–Schmidt orthogonalization (GS) and filtering (e.g. High Pass Filtering (HPF), Multi-Resolution Analysis (MRA)) based methods are based implicitly on a pure pixels assumption. Thus, their usage for mixed pixels (quite common situation in remote sensing applications) can lead to wrong image fusion results. Two methods, one based on a linear unmixing model and another one based on spatial unmixing, are described/proposed/modified which respect models assumed and thus can produce correct or physically justified fusion results. Earlier mentioned property ‘better’ should be measurable quantitatively, e.g. by means of so-called quality measures. The difficulty of a quality assessment task in multi-resolution image fusion or pan-sharpening is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions used are not valid or not fulfilled. From a model based view it follows naturally that a quality assessment measure can be defined as a combination of error model residuals using common or general models assumed in all fusion methods. Thus in this paper a comparison of the two earlier proposed/modified pan-sharpening methods together with some already existing model based methods and several other popular methods is performed. Experimental validation/verification is carried out in the urban area of Munich city for optical remote sensing multispectral data and panchromatic imagery of the WorldView-2 satellite sensor. The quality assessment of image fusion or pan-sharpening results is performed using a newly proposed measures based on common or general model error residuals and their combinations. Preliminary results confirm ideas of the author and show a great potential for future applications.

elib-URL des Eintrags:https://elib.dlr.de/103670/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Palubinskas, GintautasGintautas.Palubinskas (at) dlr.dehttps://orcid.org/0000-0001-7322-7917NICHT SPEZIFIZIERT
Datum:2016
Erschienen in:International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Referierte Publikation:Nein
Open Access:Ja
Gold Open Access:Nein
In SCOPUS:Ja
In ISI Web of Science:Nein
Band:XLI-B7
DOI:10.5194/isprsarchives-XLI-B7-693-2016
Seitenbereich:Seiten 693-702
Herausgeber:
HerausgeberInstitution und/oder E-Mail-Adresse der HerausgeberHerausgeber-ORCID-iDORCID Put Code
NICHT SPEZIFIZIERTISPRSNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Verlag:ISPRS
ISSN:1682-1750
Status:veröffentlicht
Stichwörter:image processing, multi-resolution image fusion, pan-sharpening, quality assessment, model based approach, remote sensing
Veranstaltungstitel:ISPRS 2016
Veranstaltungsort:Prague, Czech Republic
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:12 Juli 2016
Veranstaltungsende:19 Juli 2016
Veranstalter :ISPRS
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Raumfahrt
HGF - Programmthema:Erdbeobachtung
DLR - Schwerpunkt:Raumfahrt
DLR - Forschungsgebiet:R EO - Erdbeobachtung
DLR - Teilgebiet (Projekt, Vorhaben):R - Vorhaben hochauflösende Fernerkundungsverfahren (alt)
Standort: Oberpfaffenhofen
Institute & Einrichtungen:Institut für Methodik der Fernerkundung > Photogrammetrie und Bildanalyse
Hinterlegt von: Palubinskas, Dr.math. Gintautas
Hinterlegt am:31 Mär 2016 14:20
Letzte Änderung:24 Apr 2024 20:09

Nur für Mitarbeiter des Archivs: Kontrollseite des Eintrags

Blättern
Suchen
Hilfe & Kontakt
Informationen
electronic library verwendet EPrints 3.3.12
Gestaltung Webseite und Datenbank: Copyright © Deutsches Zentrum für Luft- und Raumfahrt (DLR). Alle Rechte vorbehalten.