Spaces of Spectral Distributions and Their Natural Geometry
In this paper we show that spaces of spectral distributions, like color stimuli, have a natural cone-like structure. We use the framework of the Karhunen-Loéve transform in a Hilbert space context to describe this cone-like structure and demonstrate how to compute natural coordinate systems from empirical data, like multi-spectral measurements and images. We will illustrate the theoretical findings with databases consisting of collections of multispectral measurements of color chips from color systems like Munsell, NCS and Pantone, multi-channel images of natural scenes, satellite data and daylight spectra.
We will also comment on the possible application of group theoretical methods in color science based on those findings.
Document Type: Research Article
Publication date: January 1, 2002
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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