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21 December 1999How to convert RGB signals to colorimetric and densitometric values
Several techniques are discussed in literature, such as first or higher order polynomial modeling and the application of neural networks. We used another technique based on a Principal Component Analysis (PCA) in order to predict spectra. To calibrate the camera one may work with reflectance spectra or with density spectra. The PCA is affected by this choice and leads to basic spectra, which are more sensitive to either reflectance or to density. We discuss the advantages/disadvantages working with reflectances or densities and we present the results we have obtained by calculating colorimetric and densitometric values.
Hansjoerg Kuenzli
"How to convert RGB signals to colorimetric and densitometric values", Proc. SPIE 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V, (21 December 1999); https://doi.org/10.1117/12.373440
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Hansjoerg Kuenzli, "How to convert RGB signals to colorimetric and densitometric values," Proc. SPIE 3963, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts V, (21 December 1999); https://doi.org/10.1117/12.373440