title: Regularized learning framework in the estimation of reflectance spectra from camera responses.
abstract: 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.
authors.affiliation: InFotonics Center, University of Joensuu, Finland. villehe@cc.joensuu.fi
authors.forename: Ville
authors.initials: V
authors.lastname: Heikkinen
authors.forename: Tuija
authors.initials: T
authors.lastname: Jetsu
authors.forename: Jussi
authors.initials: J
authors.lastname: Parkkinen
authors.forename: Markku
authors.initials: M
authors.lastname: Hauta-Kasari
authors.forename: Timo
authors.initials: T
authors.lastname: Jaaskelainen
authors.forename: Seong Deok
authors.initials: SD
authors.lastname: Lee