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Fusion of Multi-Resolution Digital Surface Models

Kuschk, Georg and d'Angelo, Pablo (2013) Fusion of Multi-Resolution Digital Surface Models. In: ISPRS Archives, XL-1/W (WG I/4), pp. 247-251. Copernicus Publications. SMPR Conference 2013, 5.-8. Oct. 2013, Teheran, Iran.

Full text not available from this repository.

Official URL: http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W3/247/2013/isprsarchives-XL-1-W3-247-2013.pdf

Abstract

This paper proposes an algorithm for fusing digital surface models (DSM) obtained by heterogenous sensors. Based upon prior confidence knowledge, each DSM can be weighted locally adaptively and therefore strengthen or lessen its influence on the fused result. The proposed algorithm is based on variational methods of first and second order, minimizing a global energy functional comprising of a data term forcing the resulting DSM being similar to all of the input height information and incorporating additional local smoothness constraints. By applying these additional constraints in the form of favoring low gradients in the spatial direction, the surface model is forced to be locally smooth and in contrast to simple mean or median based fusion of the height information, this global formulation of context-awareness reduced the noise level of the result significantly. Minimization of the global energy functional is done with respect to the L1 norm and therefore is robust to large height differences in the data, which preserves sharp edges and fine details in the fused surface model, which again simple mean- and median-based methods are not able to do in comparable quality. Due to the convexity of the framed energy functional, the solution furthermore is guaranteed to converge towards the global energy minimum. The accuracy of the algorithms and the quality of the resulting fused surface models is evaluated using synthetic datasets and real world spaceborne datasets from different optical satellite sensors. constraints. By applying these additional constraints in the form of favoring low gradients in the spatial direction, the surface model is forced to be locally smooth and in contrast to simple mean or median based fusion of the height information, this global formulation of context-awareness reduced the noise level of the result significantly. Minimization of the global energy functional is done with respect to the L1 norm and therefore is robust to large height differences in the data, which preserves sharp edges and fine details in the fused surface model, which again simple mean- and median-based methods are not able to do in comparable quality. Due to the convexity of the framed energy functional, the solution furthermore is guaranteed to converge towards the global energy minimum. The accuracy of the algorithms and the quality of the resulting fused surface models is evaluated using synthetic datasets and real world spaceborne datasets from different optical satellite sensors.

Item URL in elib:https://elib.dlr.de/86390/
Document Type:Conference or Workshop Item (Speech)
Title:Fusion of Multi-Resolution Digital Surface Models
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Kuschk, Georggeorg.kuschk (at) dlr.deUNSPECIFIED
d'Angelo, Pablopablo.angelo (at) dlr.deUNSPECIFIED
Date:October 2013
Journal or Publication Title:ISPRS Archives
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Volume:XL-1/W
Page Range:pp. 247-251
Editors:
EditorsEmail
Arefi, H.UNSPECIFIED
Sharifi, M. A.UNSPECIFIED
Reinartz, P.peter.reinartz@dlr.de
M. R. Delavar, M. R.UNSPECIFIED
Publisher:Copernicus Publications
Series Name:ISPRS Archives
Status:Published
Keywords:DSM, 3D Reconstruction, Data Fusion
Event Title:SMPR Conference 2013
Event Location:Teheran, Iran
Event Type:international Conference
Event Dates:5.-8. Oct. 2013
Organizer:ISPRS
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Transport
HGF - Program Themes:Traffic Management (old)
DLR - Research area:Transport
DLR - Program:V VM - Verkehrsmanagement
DLR - Research theme (Project):V - Projekt VABENE (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By:INVALID USER
Deposited On:06 Dec 2013 14:55
Last Modified:08 May 2014 23:19

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