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The acquisition output vectors are then processed to correct noise and geometry of
illumination, and are feeded through the characterization model to obtain estimated
reflectances. The model itself is built using standard numerical analysis techniques
for system inversion, revolving around Singular Value Decomposition. A complete
diagram of our operation pipeline can be seen in Figure 3.
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Fig. 3 – A framework for ‘wide-band’ multispectral acquisition
As a reference, Figure 4 shows results obtained by the authors for a few different
acquired color samples in terms of a comparison between the estimated reflectance
curves and the corresponding measurements obtained using a Minolta CM-2002
spectrophotometer.
5. Mosaicking of multispectral images
A single multispectral image does not necessarily provide a complete
representation of the scene or artifact considered. Whenever large artifacts or
scenes must be acquired, and / or a high image resolution is wanted, it is unlikely
that a single acquired image can be sufficient; a narrow field of view in the
acquisition system can also contribute to this situation. In fact, often several
images (called ‘tessels’) covering different parts of the scene will have to be taken