The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
322 
Figure 3. Influence of punctual constraints on final radiometry 
3.3 Test case over Tasmania 
The process has been tested on Tasmania Island, southeast of 
Australia. Due to oceanic climate, input data is very 
heterogeneous. Eleven very cloudy SPOT5-HRS segments 
taken from 2004 to 2007 in winter (July) as in summer (January) 
were required to cover nearly 70000 km 2 . With one point every 
kilometre, an initial water mask and two iterations, results are 
promising. Degree 1 polynomials make globally well-adjusted 
images (Fig. 4). RMS of radiometric differences on overlapping 
area drops from 62 to 14. And consequently, seams between 
images are less visible if not invisible (Fig. 5). 
Figure 4. Initial and final radiometries - Tasmania 
07/06/2004 
07/06/2004 
i 
13/04/2007 
13/04/2007 
Figure 5. initial and final limit between 2 images - Tasmania 
For each image, a cloud mask is created automatically from 
invalid grid nodes (Fig. 6). These masks have proved to be very 
useful for mosaicking step. 
Figure 6. Image and cloud mask - Tasmania 
4. APPLICATION TO DEM TILTING 
Reference3D DEM is obtained by merging overlapping DEMs, 
calculated by automatic image matching of SPOT5-HRS stereo 
pairs. But residual errors in “geometric” block adjustment result 
in small altimetric discontinuities between DEMs so tilting 
them is necessary before merging step. Radiometric block 
adjustment methodology can be adapted easily for DEM tilting. 
Image radiometry is simply replaced by DEM altitude and 
polynomial model applied to altitude is as follows (eq.7): 
FinalAlt(col, row)= InitialAlt(col, row)+Q(col, row) (7) 
where: 
• InitialAlti is initial DEM altitude for pixel (col,row) 
• FinalAlti is calculated altitude for pixel (col,row) 
• Q is a polynomial limited to degree 1. 
Multiplier polynomial P, present for radiometric block 
adjustment, is not used for DEM tilting. Addition to initial 
altitude is the only permitted operation, multiplication is 
forbidden. 
5. PERSPECTIVES 
Radiometric block-adjustment strategy described in this article 
has been validated on medium-size datasets. Previously manual 
tasks like radiometric adjustment or DEM tilting are now 
mostly automatic and give good results. But, many studies 
could be conducted to improve this algorithm, in particular 
concerning system constraints on standard deviation invariance 
to have a better control of image dynamic. And practically, this 
functionality has yet to be transferred to Reference3D mass 
production, typically from Tasmania dataset to Australia dataset. 
REFERENCES 
Ackerman, S.A., Strabala, K. I., Menzel, P. W.P., Frey, R.A., 
Moeller, C.C. and Gumley, L.E., 1998: Discriminating clear 
sky from clouds with MODIS, Journal of Geophysical 
Research, 103(D24):32,141-32,157. 
Caprioli, M., Figorito, B. and Tarantino, E., 2006. Radiometric 
Normalization of Landsat Etm+ Data for Multitemporal 
Analysis, ISPRS Proceedings “From pixels to processes”, 
Enschede (NL).