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Model based view at multi-resolution image fusion methods and quality assessment measures

Palubinskas, Gintautas (2016) Model based view at multi-resolution image fusion methods and quality assessment measures. International Journal of Image and Data Fusion, 7 (3), pp. 203-218. Informa UK Limited. DOI: 10.1080/19479832.2016.1180326 ISBN 1947-9832 ISSN 1947-9832

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Official URL: http://www.tandfonline.com/doi/abs/10.1080/19479832.2016.1180326


We propose to look at multi-resolution image fusion or pan-sharpening task from a model based perspective. Explicit definition of all models or assumptions used in the derivation of a fusion 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. 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 is that a reference image is missing. Existing measures or so-called protocols are still not satisfactory because quite often the rationale or assumptions 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 fusion methods. It is shown that most existing methods based on a spectral transformation or filtering are model based methods. Unfortunately, it was found out that they are based additionally on a pure pixels assumption. As they are applied for mixed pixels too that can lead to wrong fusion results. Model based view analysis shows which methods respect models assumed and thus can help to select methods which deliver correct or physically justified fusion results.

Item URL in elib:https://elib.dlr.de/104383/
Document Type:Article
Title:Model based view at multi-resolution image fusion methods and quality assessment measures
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Palubinskas, GintautasGintautas.Palubinskas (at) dlr.dehttps://orcid.org/0000-0001-7322-7917
Journal or Publication Title:International Journal of Image and Data Fusion
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
DOI :10.1080/19479832.2016.1180326
Page Range:pp. 203-218
Zhang, JixianChinese Academy of Surveying and Mapping, China
Publisher:Informa UK Limited
Keywords:remote sensing; image processing; multi-resolution image fusion; pan-sharpening; quality assessment; model based
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:26 May 2016 09:26
Last Modified:14 Dec 2019 04:21

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