COMPARISON OF PANSHARPENING ALGORITHMS FOR COMBINING RADAR AND 
MULTISPECTRAL DATA 
S. Klonus 3 
a Institute for Geoinformatics and Remote Sensing, University of Osnabrück, 49084 Osnabrück, Germany - 
sklonus@igf.uni-osnabrueck.de 
Youth Forum 
KEY WORDS: Image Processing, Sharpening, Image Understanding, Fusion, Environmental Monitoring, Radar, Colour, 
Multisensor 
ABSTRACT: 
Iconic image fusion is a technique that is used to combine the spatial structure of a high resolution panchromatic image with the 
spectral information of a lower resolution multispectral image to produce a high resolution multispectral image. This process is often 
referred to as pansharpening. In this study, image data of the new RADAR satellite TerraSAR-X are used to sharpen optical 
multispectral data. To produce these images, use is made of the Ehlers fusion, a fusion technique that is developed for preserving 
maximum spectral information. The Ehlers Fusion is modified to integrate radar data with optical data. The results of the modified 
Ehlers fusion are compared with those of other standard fusion techniques such as Brovey, Principal Component, and with recently 
developed fusion techniques such as Gram-Schmidt, UNB, wavelet based fusion and CN-Spectral Sharpening. The evaluation is 
based on the verification of the preservation of spectral characteristics and the improvement of the spatial resolution. The results 
show that most of the fusion methods are not capable to integrate TerraS AR-X data into multispectral data without color distortions. 
The result is confirmed by statistical analysis. 
KURZFASSUNG: 
Ikonische Bildfusion ist eine Technik, um die räumliche Struktur von hochaufgelösten panchromatischen Bilddaten mit den 
spektralen Informationen eines niedriger aufgelösten Multispektralbildes zu kombinieren, um ein hochaufgelöstes multispektrales 
Bild zu erhalten. Dieser Prozess wird auch „Pansharpening“ genannt. In dieser Untersuchung werden Bilddaten des neuen RADAR 
Satelliten TerraSAR-X verwendet, um die geometrische Auflösung der optischen multispektralen Daten zu verbessern. Um diese 
Bilder zu erstellen, wird die Ehlers Fusion verwendet. Dieses Fusionsverfahren wurde speziell zur bestmöglichen Erhaltung der 
spektralen Informationen entwickelt. Die Ehlers Fusion wurde modifiziert, um RADAR Daten in optische Daten zu integrieren. Die 
Resultate der modifizierten Ehlers Fusion wurden mit Standard-Fusionstechniken wie der Brovey Transformation oder dem 
Principal Component Verfahren und auch mit aktuelleren weiter entwickelten Fusionsverfahren, wie Gram-Schmidt, UNB, Wavelet 
basierter Fusion und Color-Normalized Spectral Sharping verglichen. Die Evaluierung der Ergebnisse basiert auf der Untersuchung 
der Erhaltung der spektralen Charakteristiken und der Verbesserung der geometrischen Auflösung. Die Ergebnisse zeigen, dass die 
Fusionsverfahren überwiegend daran scheitern, die TerraSAR-X Daten in die multispektralen Daten ohne Farbveränderungen zu 
integrieren. Die quantitativ-statistischen Ergebnisse bestätigen diese Aussage. 
1. INTRODUCTION 
Image fusion is a technique that is used to combine the spatial 
structure of a high resolution panchromatic image with the 
spectral information of a lower resolution multispectral image 
to produce a high resolution multispectral image. This process 
is often referred to as pansharpening. 
In this study, image data of the new RADAR satellite 
TerraSAR-X are used to sharpen optical multispectral data. 
TerraSAR-X is the first non-military RADAR satellite which 
provides data with a ground resolution of 1 m. The opportunity 
to acquire images independent of any illumination by the sun 
and independent of weather conditions such as, for example, 
cloud coverage allows measurements at any time of day or 
night. Fusion with multispectral image data from other dates 
can make it possible to produce higher resolution color images, 
even under clouded skies or adverse weather conditions. These 
enhanced images can be submitted to rescue staff in conflict 
areas caused by disaster such as earthquakes, tsunamis or 
flooding. With this information, for example, it will be easier 
for rescue forces to identify the most affected areas, the extent 
and degree of damage and site accessibility. 
Many other publications have already focused on how to fuse 
high resolution panchromatic images with lower resolution 
multispectral data to obtain high resolution multispectral 
imagery while retaining the spectral characteristics of the 
multispectral data (see, for example, Welch and Ehlers 1987 or 
Gonzalez-Audicana et al. 2006). Fewer publications focus on 
the use of SAR data for Fusion. Ehlers (1991) showed that 
fused SIR-B and Landsat TM data improved the quality for 
vegetation mapping. Riccietti (2001) used SAR data as a 
panchromatic input for image fusion with optical data. He used 
the SAR image to fuse it with Landsat TM data. Chibani (2006) 
used Spot panchromatic and SAR data to integrate this 
information into multispectral Spot data.