Evaluation and unification of some methods for estimating reflectance spectra from RGB images
Autor: | Timo Jaaskelainen, Reiner Lenz, Ville Heikkinen, Markku Hauta-Kasari, Jussi Parkkinen, Tuija Jetsu |
---|---|
Rok vydání: | 2008 |
Předmět: |
business.product_category
Unification Color constancy business.industry Machine vision Computer science 02 engineering and technology Iterative reconstruction Inverse problem 01 natural sciences Atomic and Molecular Physics and Optics Spectral line Electronic Optical and Magnetic Materials 010309 optics Optics 0103 physical sciences 0202 electrical engineering electronic engineering information engineering RGB color model 020201 artificial intelligence & image processing Computer Vision and Pattern Recognition business Digital camera |
Zdroj: | Journal of the Optical Society of America. A, Optics, image science, and vision. 25(10) |
ISSN: | 1084-7529 |
Popis: | The problem of estimating spectral reflectances from the responses of a digital camera has received considerable attention recently. This problem can be cast as a regularized regression problem or as a statistical inversion problem. We discuss some previously suggested estimation methods based on critically undersampled RGB measurements and describe some relations between them. We concentrate mainly on those models that are using a priori information in the form of high-resolution measurements. We use the "kernel machine" framework in our evaluations and concentrate on the use of multiple illuminations and on the investigation of the performance of global and locally adapted estimation methods. We also introduce a nonlinear transformation of reflectance values to ensure that the estimated reflection spectra fulfill physically motivated boundary conditions. The reported experimental results are derived from measured and simulated camera responses from the Munsell Matte, NCS, and Pantone data sets. |
Databáze: | OpenAIRE |
Externí odkaz: |