Estimation of Reflectance Spectra Using Multiple Illuminations
In this paper we investigate the problem of estimating reflectance spectra from measurements taken with ordinary digital RGB cameras. We study the effects of using multiple illuminations and treat the estimation of the reflectance spectra as a regression or a statistical inversion problem. We use both, linear- and non-linear estimation methods where we focus on using reproducing kernels to avoid explicit formulation of non-linearities. We also include non-linear conditions based on the properties of the reflection spectra. Munsell Matte color and Pantone are used as data sets to support the proposed methods. The experiments show that the proposed methods improve the estimation results when compared to standard linear methods.
Document Type: Research Article
Publication date: January 1, 2008
Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.
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