Color processing apparatus and its method
In gamut mapping, when saturation is linearly compressed, a saturation drop of a low-saturation part is considerable. Linear compression based on zone division produces discontinuous points. Nonlinear compression cannot automatically and uniquely calculate a conversion curve. To combat these problems, first and second gamut data are obtained, the lightness ranges of the gamut data are normalized, and the lightness, hue, and saturation values of a sample point of the first gamut data after normalization are calculated. Maximum saturation points which have lightness and hue values equal to those of the sample points are calculated from the first and second gamut data after normalization. A color conversion table is then generated by calculating a mapping point in the second color gamut after normalization, which corresponds to the sample point, on the basis of the saturation values of the maximum saturation points and sample point.
1. A color processing method of determining saturation compression based on a visual characteristic, comprising using a color processing apparatus to perform the steps of:
calculating first and second boundary points, wherein the first boundary point is an intersection point of a line passing a sample point in a source gamut and a boundary of the source gamut, and the second boundary point is an intersection point of the line and a boundary of a destination gamut;
calculating a saturation difference ΔCmax from saturation C 1 of the first boundary point and saturation C 2 of the second boundary point by
Δ C max=√{( C 1− C 2)/(1+0.045 C* )} 2 ;
calculating a saturation difference ΔCin from saturation Cin of the sample point, the saturation C 1 of the first boundary point, and the saturation difference ΔCmax by
Δ C in=Δ C max· C in/ C 1; and
calculating a corrected saturation Cout of the sample point, to map the sample point into the destination gamut, by
C out=( k 2· C in−Δ C in) k 1,
where k 1=1+0.045/2×Δ C in, and
k 2=1−0.045/2×Δ C in,
wherein an amount of correcting the saturation grows larger as the saturation of the sample point rises.
2. The method according to claim 1 , further comprising the step of matching lightness of the source gamut and lightness of the destination gamut.
3. The method according to claim 2 , wherein the line indicates the same lightness and the same hue of the sample point.
4. The method according to claim 1 , further comprising the step of generating a color conversion table using the mapped sample point.
5. A color processing apparatus for determining saturation compression based on a visual characteristic, comprising:
a first calculator, arranged to calculate first and second boundary points, wherein the first boundary point is an intersection point of a line passing a sample point in a source gamut and a boundary of the source gamut, and the second boundary point is an intersection point of the line and a boundary of a destination gamut;
a second calculator, arranged to calculate a saturation difference ΔCmax from saturation C 1 of the first boundary point and saturation C 2 of the second boundary point by
Δ C max=√{( C 1− C 2)/(1+0.045 C* )} 2 ;
a third calculator, arranged to calculate a saturation difference ΔCin from saturation Cin of the sample point, the saturation C 1 of the first boundary point, and the saturation difference ΔCmax by
Δ C in=Δ C max· C in/ C 1; and
a corrector, arranged to calculate a corrected saturation Cout of the sample point, to map the sample point into the destination gamut, by
C out=( k 2· C in−Δ C in) k 1,
where k 1=1+0.045/2×Δ C in, and
k 2=1−0.045/2×Δ C in,
wherein an amount of correcting the saturation grows larger as the saturation of the sample point rises.
6. A computer-readable storage medium storing a computer-executable program for causing a computer to perform a color processing method of determining saturation compression based on a visual characteristic, the method comprising the steps of:
calculating first and second boundary points, wherein the first boundary point is an intersection point of a line passing a sample point in a source gamut and a boundary of the source gamut, and the second boundary point is an intersection point of the line and a boundary of a destination gamut;
calculating a saturation difference ΔCmax from saturation C 1 of the first boundary point and saturation C 2 of the second boundary point by
Δ C max=√{( C 1− C 2)/(1+0.045 C* )} 2 ;
calculating a saturation difference ΔCin from saturation Cin of the sample point, the saturation C 1 of the first boundary point, and the saturation difference ΔCmax by
Δ C in=Δ C max· C in/ C 1; and
calculating a corrected saturation Cout of the sample point, to map the sample point into the destination gamut, by
C out=( k 2· C in−Δ C in) k 1,
where k 1=1+0.045/2×Δ C in, and
k 2=1−0.045/2×Δ C in,
wherein an amount of correcting the saturation grows larger as the saturation of the sample point rises.