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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: XXIII ISPRS Congress, Technical Commission VII, XLI-B7, pp. 693-702. ISPRS. ISPRS 2016, 12.-19. Jul. 2016, Prague, Czech Republic. DOI: 10.5194/isprsarchives-XLI-B7-693-2016

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


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.

Item URL in elib:https://elib.dlr.de/103670/
Document Type:Conference or Workshop Item (Speech)
Title:Pan-Sharpening Approaches Based on Unmixing of Multispectral Remote Sensing Imagery
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Palubinskas, GintautasGintautas.Palubinskas (at) dlr.deUNSPECIFIED
Journal or Publication Title:XXIII ISPRS Congress, Technical Commission VII
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In ISI Web of Science:No
DOI :10.5194/isprsarchives-XLI-B7-693-2016
Page Range:pp. 693-702
Keywords:image processing, multi-resolution image fusion, pan-sharpening, quality assessment, model based approach, remote sensing
Event Title:ISPRS 2016
Event Location:Prague, Czech Republic
Event Type:international Conference
Event Dates:12.-19. Jul. 2016
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Palubinskas, Dr.math. Gintautas
Deposited On:31 Mar 2016 14:20
Last Modified:31 Jul 2019 20:00

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