Optimal bases for convex color mixture

Mean and Median $\Delta E_{ab}^{*}$ Achieved When Representing the Munsell Spectral Data as Convex Sums of the NMF Basis Vectors versus Those with the New Convex Bases Algorithm ^a

^a  The results are for four to eight bases. The last two rows show the results of reconstructing the Macbeth data, 24 spectra, with eight bases.

Mean and Median $\Delta E_{ab}^{*}$ Achieved by Representing the Munsell Spectral Data as Convex Sums of 20–100 Extreme Spectra Versus Those with the New Convex Bases Algorithm ^a

^a  The results are based on 8–12 bases.

Mean and Median $\Delta E_{ab}^{*}$ Achieved by Representing the Spectral Data of the Esser Calibration Chart as Convex Sums of 8–12 Bases ^a

^a  The basis vectors are derived based on the spectra of the Munsell book of colors.

Table 1

Mean and Median $\Delta E_{ab}^{*}$ Achieved When Representing the Munsell Spectral Data as Convex Sums of the NMF Basis Vectors versus Those with the New Convex Bases Algorithm ^a

^a  The results are for four to eight bases. The last two rows show the results of reconstructing the Macbeth data, 24 spectra, with eight bases.

Table 2

Mean and Median $\Delta E_{ab}^{*}$ Achieved by Representing the Munsell Spectral Data as Convex Sums of 20–100 Extreme Spectra Versus Those with the New Convex Bases Algorithm ^a

^a  The results are based on 8–12 bases.

Table 3

Mean and Median $\Delta E_{ab}^{*}$ Achieved by Representing the Spectral Data of the Esser Calibration Chart as Convex Sums of 8–12 Bases ^a

^a  The basis vectors are derived based on the spectra of the Munsell book of colors.