Ville Heikkinen,1,*
Tuija Jetsu,1
Jussi Parkkinen,1
Markku Hauta-Kasari,1
Timo Jaaskelainen,1
and Seong Deok Lee2
1InFotonics Center, University of Joensuu, P.O. Box 111, FIN-80101 Joensuu, Finland
2Display and Image Processing STU, Computing Lab, Samsung Advanced Institute of Technology, San 14-1, Nongseo-Ri, Kiheung-Eup, Yongin Kyungki-Do 449-712, South Korea
Ville Heikkinen, Tuija Jetsu, Jussi Parkkinen, Markku Hauta-Kasari, Timo Jaaskelainen, and Seong Deok Lee, "Regularized learning framework in the estimation of reflectance spectra from camera responses," J. Opt. Soc. Am. A 24, 2673-2683 (2007)
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.
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.