An RGB-to-spectrum conversion for reflectances
Journal of Graphics Tools
Colorization using optimization
ACM SIGGRAPH 2004 Papers
AppWand: editing measured materials using appearance-driven optimization
ACM SIGGRAPH 2007 papers
EGSR'05 Proceedings of the Sixteenth Eurographics conference on Rendering Techniques
Image-based BRDF measurement including human skin
EGWR'99 Proceedings of the 10th Eurographics conference on Rendering
EGSR'07 Proceedings of the 18th Eurographics conference on Rendering Techniques
Reconstruction of spectra using empirical basis functions
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
Practical spectral characterization of trichromatic cameras
Proceedings of the 2011 SIGGRAPH Asia Conference
ACM Transactions on Graphics (TOG) - SIGGRAPH 2013 Conference Proceedings
High-quality computational imaging through simple lenses
ACM Transactions on Graphics (TOG)
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Traditional RGB reflectance and light data suffers from the problem of metamerism and is not suitable for rendering purposes where exact color reproduction under many different lighting conditions is needed. Nowadays many setups for cheap and fast acquisition of RGB or similar trichromatic datasets are available. In contrast to this, multi- or even hyper-spectral measurements require costly hardware and have severe limitations in many cases. In this paper, we present an approach to combine efficiently captured RGB data with spectral data that can be captured with small additional effort for example by scanning a single line of an image using a spectral line-scanner. Our algorithm can infer spectral reflectances and illumination from such sparse spectral and dense RGB data. Unlike other approaches, our method reaches acceptable perceptual errors with only three channels for the dense data and thus enables further use of highly efficient RGB capture systems. This way, we are able to provide an easier and cheaper way to capture spectral textures, BRDFs and environment maps for the use in spectral rendering systems.