The International Archives of the Photo gramme try. Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B4. Beijing 2008 
(a) Multispectral image 
Figure 7: Road extraction example combining radiometric and 
geometric features. 
image can reach 1 Giga pixels often in several spectral bands. 
In this situation, it is unreasonable to load the whole image in 
the computer memory to process it. This is even truer for high 
resolution imagery based mapping applications, where, in order 
to cover the area of interest several satellite scenes are usually 
used. 
Thus, streaming techniques enable to read, process and write the 
result progressively without having to load the entire image into 
memory. Most of typical image processing operations work lo 
cally and are compatible with streaming. Streaming capabilities 
are included in OTB transparently for the user, thus enabling an 
easy processing of huge images. 
6.3 Efficient data processing 
Since images are divided into separate streams and since most 
current processors have two, four, or even more, cores, it is tempt 
ing to use this capabilities process data in parallel and to save 
some time. This property is called multithreading. Once again, 
OTB automatically enables multithreading when it is possible. 
This is especially valuable to work on clusters where the combi 
nation of several processors help to greatly reduce the total pro 
cessing time. These operations and the repartition on the different 
computing units is transparent for the OTB user, thus removing 
most of the burden of multithreaded programming. 
7 CONCLUSION 
In the mapping and photogrammetry fields the concepts used are 
often difficult to handle and many users rely on commercial prod 
ucts. However, to truly master the process, a hands on approach 
is unavoidable. 
In this context, OTB allows the user to practice and experiment 
with real data and real tools and can be used in several situations: 
• for engineers: efficient development on new remote sensing 
applications; 
• for engineers: quick evaluation of the performance of a par 
ticular algorithm on a specific type of data; 
• for researchers: fast prototyping of new algorithms; 
• for researchers: library of existing algorithms to compare 
the results with a new one; 
• for professors: teaching of image processing; 
• for students: benefit from many heavily-tested algorithms 
popular in the literature. 
The ORFEO Toolbox concerns all people working in the remote 
sensing imagery community. Releasing it as an open source soft 
ware, CNES hopes to benefit from the contribution of many spe 
cialists to help grow the practical use of satellite imagery. 
REFERENCES 
Christophe, E. and Inglada, J., 2007. Robust road extraction for 
high resolution satellite images. In: IEEE International Confer 
ence on Image Processing, ICIP’07. 
Inglada, J. and Giros, A., 2004. On the possibility of automatic 
multi-sensor image registration. IEEE Trans. Geoscience and Re 
mote Sensing. 
1267