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RADIOMETRIC BLOCK-ADJUSTMENT OF SATELLITE IMAGES 
REFERENCE3D® PRODUCTION LINE IMPROVEMENT 
L. Falala 3, R. Gachet 3 , L. Cunin 3 
a IGN, Institut Géographique National, 6 Avenue de l’Europe, 31520 Ramonville, 
France - (laurent.falala, roland.gachet, laurent.cunin)@ign.fr 
Commission, WG IV/3 
KEY WORDS: SPOT, Radiometry, Mosaic, Block, Multitemporal, Orthoimage 
ABSTRACT: 
One layer of global geographic database Reference3D® is an image mosaic (5m resolution) made exclusively from panchromatic 
SPOT5-HRS images. In order to improve Reference3D® production line, in particular SPOT5 HRS images mosaicking step, a new 
strategy of radiometric block adjustment of satellite images was developed, implemented and tested at French mapping agency IGN. 
By analogy with “geometric” block adjustment, we developed an iterative algorithm, adapted to Reference3D datasets (many 
overlapping images covering a wide area), that calculates for each image a polynomial model to apply to its radiometry. These 
polynomials are found by least-square resolution of a global linear system. Among many tests conducted to try different parameters 
and validate the process, we present here results of a test case over Algeria (9 not too cloudy images taken in less than 3 months) and 
another more difficult over Tasmania (11 very cloudy images taken in 4 years). In both cases, radiometric differences between 
images were dramatically reduced. Reference3D contains also a DEM obtained by merging overlapping DEMs (calculated by 
automatic image matching of SPOT5-HRS stereo-pairs). Radiometric block adjustment methodology can be easily adapted for 
DEMs tilting, a preliminary step before merging. So, thanks to these new processes, previously manual tasks in reference3D® 
production line are now mostly automatic. 
1. CONTEXT 
1.1 Reference3D® database 
Reference3D® is a global geographic database produced by 
Spot Image and French mapping agency IGN. It contains three 
layers of information: 
• DTED2 Digital Elevation Models (DEM with pixel 
size at 1”), 
• 5m panchromatic ortho-images, 
• Quality and traceability metadata (including water 
and cloud masks). 
Reference3D® is made exclusively from SPOT5-HRS stereo 
pairs with the following production line: 
• Block adjustment of large sets of HRS stereo-pairs, 
• DEM generation by automatic image matching of 
stereo-pairs, 
• Orthorectification of every HRS scene with 
previously generated DEM, 
• Image mosaicking and DEM merging, 
• Quality metadata editing, tiling and packaging. 
Annual production rate reaches 7 million km 2 in 2007 but 
studies are conducted to improve productivity, especially to 
automate previously manual tasks. For this purpose, a new 
algorithm of automatic radiometric block-adjustment was 
developed, implemented and tested on real Reference3D® 
datasets. It performs automatic radiometric adjustment and 
helps to build a cloud mask, which improve image mosaicking 
and metadata editing steps. It can be used also to tilt DEM, 
which may be necessary for DEM merging step. 
1.2 Radiometric adjustment techniques 
Radiometric block adjustment consists in modifying radiometry 
of each image of a block in order to reduce radiometric 
difference between images and create a more visually pleasing 
and almost seamless mosaic. Various methodologies exist to 
complete this task, each tailored to a particular context. 
Radiometric adjustment, based on physical modelling of solar 
illumination, has been developed for mosaics of cloud-free, 
mono-date and multispectral aerial images (Martinoty 2005). 
But Reference3D input images are multi-temporal and 
distributed throughout the world, making any physical 
modelling too complex if not impossible. 
On the other hand, image harmonization and cloud detection 
techniques exist for low-resolution satellite images with many 
spectral bands, like NASA cloud masking algorithm on MODIS 
images (Ackerman, 1998). But such methods can’t be used on 
panchromatic SPOT5-HRS images containing only one spectral 
band. 
2. METHODOLOGY 
2.1 Introduction 
By analogy with “geometric” block adjustment, we developed a 
radiometric adjustment methodology adapted to Reference3D 
datasets made of many overlapping images covering a wide 
area. This non-physical iterative algorithm calculates a 
polynomial model for each image of the block, by least-square 
resolution of a global linear system. At the end of this process, 
radiometry of any pixel(colmun, row) of a given image I is 
modified as follows (eq. 1):