Regularized learning framework in the estimation of reflectance spectra from camera responses.
For digital cameras, device-dependent pixel values describe the camera's response to the incoming spectrum of light. We convert device-dependent RGB values to device- and illuminant-independent reflectance spectra. Simple regularization methods with widely used polynomial modeling provide an efficient approach for this conversion. We also introduce a more general framework for spectral estimation: regularized least-squares regression in reproducing kernel Hilbert spaces (RKHS). Obtained results show that the regularization framework provides an efficient approach for enhancing the generalization properties of the models.
Heikkinen
Ville
V
InFotonics Center, University of Joensuu, Finland. villehe@cc.joensuu.fi
Jetsu
Tuija
T
Parkkinen
Jussi
J
Hauta-Kasari
Markku
M
Jaaskelainen
Timo
T
Lee
Seong Deok
SD