The Synthesis and Analysis of Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVGIP: Image Understanding
Principles of Digital Image Synthesis
Principles of Digital Image Synthesis
How to Derive a Spectrum from an RGB Triplet
IEEE Computer Graphics and Applications
Deriving Spectra from Colors and Rendering Light Interference
IEEE Computer Graphics and Applications
An RGB-to-spectrum conversion for reflectances
Journal of Graphics Tools
A tool to create illuminant and reflectance spectra for light-driven graphics and visualization
ACM Transactions on Graphics (TOG)
Spectralization: reconstructing spectra from sparse data
EGSR'10 Proceedings of the 21st Eurographics conference on Rendering
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Physically-based image synthesis requires measured spectral quantities for illuminants and reflectances as part of the virtual scene description to compute trustworthy lighting simulations. When spectral distributions are not available, a method to reconstruct spectra from color triplets needs to be applied. A comprehensive evaluation of the practical applicability of previously published approaches in the context of realistic rendering is still lacking. Thus, we designed three different comparison scenarios typical for computer graphic applications to evaluate the suitability of the methods to reconstruct illumination and reflectance spectra. Furthermore, we propose a novel approach applying empirical mean spectra as basis functions to reconstruct spectral distributions. The mean spectra are derived from averaging sets of typical red, green, and blue spectra. This method is intuitive, computationally inexpensive, and achieved the best results for all scenarios in our evaluation. However, reconstructed spectra are not unrestrictedly applicable in physically-based rendering where reliable synthetic images are crucial.