2008 
41 
ASPECTS OF THE STANDARDIZATION OF SENSOR AND DATA FUSION OF 
REMOTE SENSING DATA 
R. Hoffmann, R. Reulke 
Humboldt-University Berlin, Department of Computer Science, Computer Vision 
Unter den Linden 6, 10099 Berlin, Germany 
(rhoffmann, reulke)@informatik.hu-berlin.de 
Commission I, WG 1/1 
KEY WORDS: Standards, Fusion, Algorithms, Sensor, Classification, Remote Sensing 
ABSTRACT: 
Owing to continuous developments in technology and new requirements single sensor measurements are faced with constraints in 
their accuracy and thus in the applicability of their results. An innovative method of improving the geometric and radiometric data 
quality is the fusion of data obtained from different digital sensors. Sensor fusion means merging data obtained from different 
individual physical sensors to provide more comprehensive information from a single ’logical’ or ’virtual’ sensor. Airborne and 
spacebome high-resolution digital cameras, laser scanners, hyperspectral systems, radar and InSAR systems have been considered in 
this context.Common fusion methods are resolution improvement, fusion of altitude or distance information and texture information 
(orthophoto generation), pan-sharpening and tracking. The derivation of orientation information from fusion of different sensors is 
not regarded in this paper.Assessment criteria for fusion results of data obtained from different sources have so far only been 
established in a few cases. Within the INS project (German Institute for Standardization DIN, 2008) the scientific bases for 
standardization has been developed to provide manufacturers and users with rules for the quality of the end products - also with 
regard to the international market. Therefore sensors and methods for achieving possible fusion products were introduced and 
discussed. This formed the basis for the development of a working document for a draft standard for requirements for geometric 
fusion methods. 
KURZFASSUNG: 
Messungen mit einzelnen Sensoren kommen durch die ständige technologische Entwicklung und neue Anforderungen an die 
Grenzen ihrer Genauigkeit und damit auch der Verwendbarkeit dieser Ergebnisse. Eine innovative Methode zur Verbesserung der 
geometrischen und radiometrischen Datenqualität ist die Fusion von Daten unterschiedlicher digitaler Sensoren. Dabei werden die 
Daten von verschiedenen individuellen physikalischen Sensoren zu einer umfassenderen Information eines „logischen“ oder 
„virtuellen“ Sensors zusammengefügt. In diesem Zusammenhang wurden flugzeug- und satellitengetragene hochauflösende 
Kameras, Laserscanner, Hyperspektralscanner, Radar- und InSAR-Systeme berücksichtigt.Typische Fusionsverfahren sind die 
Auflösungsverbesserung, die Verbindung von Höheninformation und bildhafter Information (mit Parallelen zur 
Orthophotoerstellung), Pan-sharpening sowie Objektverfolgung. Die Ableitung von Orientierungsinformationen aus der Fusion 
unterschiedlicher Sensoren wird hier nicht betrachtet.Bislang existieren nur in wenigen Fällen Kriterien, die eine Beurteilung der 
Ergebnisse der Fusion von Daten unterschiedlicher Quellen erlauben. Im INS-Projekt (German Institute for Standardization DIN, 
2008) sollten die wissenschaftlichen Grundlagen erarbeitet werden, um Herstellern und Anwendern - auch in Hinblick auf den 
internationalen Markt - Festlegungen über die Qualität der Endprodukte an die Hand geben zu können. Deshalb wurden Sensoren 
und Verfahren für potenzielle Fusionsprodukte vorgestellt und diskutiert, um auf dieser Grundlage einen Norm-Entwurf für 
Anforderungen an geometrische Fusionsverfahren zu erarbeiten. 
1. INTRODUCTION 
In order to improve measurement accuracy and therefore also to 
extend the applicability of sensors it is advisable to merge data 
obtained from different individual physical sensors so that more 
comprehensive information is provided by a single “logical” 
sensor. The measurement data of a virtual sensor is already 
calibrated and has a well-known spatial and temporal relation 
between each single dataset. Currently many sensors, 
applications and techniques exist. Scientific literature has been 
reporting on it for more than 25 years (Haydn et al., 1982). One 
of the first applications was the integration of the low-resolution 
multispectral bands of Landsat data with the high-resolution 
panchromatic band of SPOT data (pan-sharpening). This 
opened up new possibilities for simultaneous processing of 
remote sensing data. With the introduction of digital 
photogrammetric airborne cameras different applications, which 
were only discussed in the scientific community, are becoming 
economically important. Especially the simultaneous 
measurements with multispectral bands also open up 
possibilities for remote sensing applications apart from 
photogrammetric products. Thus, fusion products are already 
available and integrated into a workflow for higher level 
photogrammetric and remote sensing products. So this new 
generation of digital cameras with multispectral bands is 
leading towards integration between photogrammetry and 
remote sensing. At the same time, high resolution multispectral 
data pose a new challenge for the remote sensing community.