JPH01114268A - Color data correction device - Google Patents

Abstract

PURPOSE:To improve a correction effect by preparing plural correction matrixes, selecting the matrix which gives optimum correction in correspondence with the value ot input color data, and correcting color data. CONSTITUTION:When input color data RGB is inputted, a matrix coefficient look up table 1 outputs nine matrix coefficient data a11-a33 with the value of RGB data as an address input. Coefficient data a11 is inputted to a multiplication look up table 2, and a multiplied result a11R between coefficient data a11 and data R is outputted. Similarly, data a12G is outputted from a multiplication look up table 3 and data a13B from a multiplication look up table 4. An adder 11 adds the outputs and a correction output R1 is obtained. Other correction outputs G1 and B1 can similarly be obtained. Since the matrix which gives the optimum matrix is selected and color data is corrected in correspondence with the value of input color data, high correction effect can always be obtained.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a one-color data correction device, and particularly to a color correction method suitable for improving color reproducibility.

[Conventional technology]

Traditionally, color data correction has been done as discussed at the Television Society National Conference 1-8 (1979).
This was done using matrix calculations. The coefficients of this correction matrix are optimized for the entire color space, for example, so that the sum of squared errors is minimized. In this way, color data has been corrected using one fixed correction matrix.

[Problem that the invention seeks to solve]

The conventional method described above uses only one general-purpose correction matrix that is optimized for the entire color space, so it is possible to perform various corrections on all color data. A satisfactory correction effect was not necessarily obtained.

An object of the present invention is to provide a color data correction device that can enhance the correction effect of various color data and improve color reproducibility.

Means for Solving Problem C] In order to achieve the above object, the present invention provides a color data correction device including a calculation means for performing color correction by performing matrix calculation on color data obtained by digitizing an input signal. The present invention proposes a color data correction device including a plurality of correction matrices that are selectively used depending on the color data.

Specifically, the helices 71 to 71 are a set of optimally corrected helices 71 obtained by dividing the color space in which the color data exists into a plurality of subspaces and finding each subspace.

Alternatively, the color space in which the color data exists may be divided into a plurality of subspaces, and the matrix obtained for each subspace may be weighted and added according to the value of the input color data to obtain a correction matrix. can.

[Effect]

In the present invention, a plurality of correction 71 helices are prepared,
Since the matrix that provides the optimum correction is selected according to the value of the input color data and the color data is corrected, a high correction effect can always be obtained.

〔Example〕

An embodiment of the present invention will be described in detail with reference to the drawings.

FIG. 2 is a block diagram showing an example of a signal processing circuit of a color image reading device to which the present invention is applied.

An output electrical signal from an input section 14 such as a COD licensor is amplified by an amplifier 15 and converted into a digital signal by an 8-digit converter 16. This signal is processed by the shading correction circuit 17 to detect uneven illumination and the CCD line sensor 14.
Fluctuations caused by variations in sensitivity between each element are corrected. The multiplexer]8 divides the signal into three colors, for example, white (W), yellow (Y), and cyan (C), corresponding to each color filter, and inputs the signal to the color conversion circuit]-9. Color conversion circuit]-9 converts the wYc signal into three colors, for example, red (R), green (G), and blue (B).
Convert to primary color signal. The data converted to RGB signals is input to the color correction circuit 20, which is the object of the present invention, and color deviations caused by the spectral characteristics of the light source, optical system, color filter, etc. are corrected, and the data is sent to an output device, such as a color Output to the display.

The color correction circuit 20 uses matrix calculation to correct color deviations that occur in color separation characteristics determined by a light source, an optical system, a color filter, and the like.

Below, 3×3 71~Rikus A = a7. a,,,, a7.3(1)a3j
``23a33'' will be explained.

An example of a specific configuration of the color correction circuit 20 of the present invention is shown in FIG. Input color data RGB is input into a matrix coefficient lookup table 1.

71-Risk coefficient lookup table 1 takes RGB data values as address inputs and outputs nine matrix data a11 to 833. Coefficient data att is input into multiplication lookup table 2,
Multiplication result a11R of this coefficient data a, □ and R data
is output. Similarly, from multiplication lookup table 3, a, , G, and from multiplication lookup table 4, a
l and B are output. An adder 11 adds these outputs to obtain a corrected output R1. Other correction output G1.
B, can also be obtained in the same way.

FIG. 3 is a flowchart illustrating an example of a method for determining coefficients of a correction matrix. First, the color space S is divided into N subspaces Si (i=1...,N). Next, an optimized correction matrix Ai (i=1...,N) is obtained for each of the divided subspaces Sj. In order to determine the coefficients of such corrections 71 to RISK, a plurality of color samples whose correct RGB values are known are prepared. For data obtained by reading these color samples with a color image reading device, each coefficient of the correction 71-lix is determined using the most squared method so as to minimize the sum of squared errors of the correction result. After determining the correction matrix A] for each subspace Si in the following manner, the RGB values of all input color data are assigned 71 to 71 to be used for correction, and the matrix Set the coefficient values in matrix coefficient lookup table 1. Here, when the color data belongs to the subspace Sn, a correction 71-rix An optimized in the subspace Sn is assigned.

The easiest way to divide the color space S into subspaces Si (i=1...,N) is to simply divide them equally. R
FIG. 4 shows an example in which the GB color sky blue space is equally divided into subspaces 81 to SO. However, in reality, there may be areas in the RGB color space where no data exists due to the spectral characteristics of photographic coloring materials, printing inks, and the like. Additionally, the size of color shift tends to vary depending on the region of the RGB color space; for example, data with a high ratio of R has a large color shift, and data with a high ratio of B has a small color shift. There is a certain bias. therefore,
It is desirable that the color space be divided in consideration of the characteristics described in 1. An example is shown below.

Color samples for determining the coefficients of the correction matrix are selected so as to be evenly distributed over as wide a range as possible. Each color sample is read by a color image reading device and the magnitude of color shift (color difference) is calculated. The color space S is divided such that in each divided subspace Si, the sum of the color differences of the color samples included in that subspace is the same or a similar value. For example, the RGB color sky blue space part axis is divided into two subspaces such that the sum of color differences in each subspace is the same. Next, in each subspace divided about the R axis, the G axis is similarly divided, and the B axis is further divided. An example of actual division is shown below.
It is shown in FIG. 2. There are various methods of matching the sum of color differences in each partial region, and the results of division are different for each method. Even when dividing on each axis as shown in FIG. 5, care must be taken because if the order of the axes for one division changes, the division results will be completely different. For example, a method may be adopted in which a weighted variance using color difference as a weight is obtained for each axis and the distribution is divided in descending order of the value.

”-In addition to the method of dividing the color scheme space S into subspaces Si, there are many other possible methods of determining the coefficients of the correction matrix in accordance with the color data. Another example of a method for determining coefficients of a correction matrix will be described with reference to FIG.

M subspaces Si in color space S (j=1...

In M), an optimized correction matrix Ai (j=1.., M) is determined for each subspace Sj. The subspace Si can be selected arbitrarily; the sum of all subspaces does not have to match the color space S, and two or more subspaces may partially or entirely overlap. The correction of color data is as follows:
1. , M), weights wi, (j=1...
, M) and add them together. Weight W]
is changed according to the value of the input color data so as to increase the weight Wm of the subspace Am, for example, when the color data exists inside or near the subspace Sm. Determine the weight wi for all color data, calculate the correction matrix coefficients, and set Ai (i = 1, . . . , M) in the matrix coefficient look-up table and wj = 1. ..., M).

A specific example of how to select the subspace Si and the weight wi will be shown below. As RGB color sky blue space subspaces, subspace SR has a high ratio of R component, and subspace S has a high ratio of G component.
A subspace Se with a high ratio of G and B components is selected. Subspace SR+s selected by setting the ratio of each color component to 0.8 or more
al S[3 is shown in FIG. Each subspace s, +
Correction matrix ARr AG in SOr so,
AB weight WR.

WG I WB is defined as the ratio of each color component of the color data, and the value is determined by the following formula.

R+G+B Here, the coefficient kRr kG + k13 is determined so that the sum of squares of color differences after correction is minimized. At this time, the entire correction matrix A is expressed by the following equation.

A=WRAp +WG AG +W13 As (
5) Furthermore, as shown in FIG. 8, by adding a subspace Sw centered on an achromatic color to the above example, the effect of correction can be enhanced.

Note that in the first embodiment, the RGB color space is divided into eight subspaces, but the number of divisions into subspaces is arbitrary, and the color reproducibility improves as the number of divisions increases. However, as the number of divisions increases, the amount of calculation and the number of required color samples increase, so the number of divisions may be determined depending on the degree of color reproducibility required.

In this embodiment, the correction is performed by a matrix operation consisting of a sum of products, and does not particularly depend on the type of data.
YMC data or XYZ data may be input instead of B data. Also, from RGB data to XYZ data or Y
Since conversion to MC data can be expressed by a 3×3 matrix operation, it is possible to combine such color conversion and the correction shown in this example into one matrix operation. For example, if the input is RGB data, The output can be MMC data.

The 3×3 matrix of this embodiment is just an example, and
The size of the correction matrix is not limited to this. Also,
The matrix calculation circuit shown in Figure 1 is one example.
In particular, various methods of matrix calculation can be considered. For example, you can calculate the corrected output values for all Kugata color data values in advance, and add them to the lookup table.
Alternatively, the input color data may be used as an address, and the corrected output may be obtained directly from the lookup table.

Further, in this embodiment, the case of color correction of a color image reading device has been described, but the present invention can also be used for correction of other color data 11= such as masking of a color printer.

According to this embodiment, highly accurate color correction can be performed with a simple circuit configuration, so that a color image reading device with high color reproducibility can be easily configured.

〔Effect of the invention〕

According to the present invention, a plurality of correction matrices are prepared, and the matrix that provides the optimum correction is selected according to the value of the input color data, and the color data is corrected, so that appropriate correction can always be performed.

[Brief explanation of the drawing]

Fig. 1 is a block diagram showing an example of a color correction circuit used in the present invention, Fig. 2 is a block diagram showing an example of a signal processing circuit of a color image reading device to which the invention is applied, and Fig. 3 is a block diagram showing an example of a signal processing circuit of a color image reading device to which the present invention is applied. Flowchart showing an example of the method, No. 4
The figure shows an example of dividing the color space into equal subspaces.
Figure 6 shows another example of dividing the color space into subspaces.
The figure is a flowchart showing another example of how to obtain a correction matrix, Figure 7 is a diagram showing an example of a subspace constructed within a color space, and Figure 8 is a diagram showing an example of a subspace constructed within a color space between -13= It is a figure which shows another example. 1... Matrix coefficient lookup table, 2-1
0: Multiplication lookup table, 11-13: Adder, 18: Multiplexer, 19: Color conversion circuit, 20: Color correction circuit. Agent Patent attorney Tatsuyuki Unuma H RGB color space S Figure 5 RGB color space S

Claims (3)

[Claims] (1) A color data correction device including arithmetic means for performing color correction by performing matrix calculations on color data obtained by digitizing an input signal, comprising a plurality of correction matrices that are selectively used according to the color data. A color data correction device characterized by: (2) Claim 1 is characterized in that the correction matrix is a set of optimal correction matrices obtained for each subspace by dividing the color space in which the color data exists into a plurality of subspaces. Color data correction device. (3) In claim 1, the correction matrix divides the color space in which the color data exists into a plurality of subspaces, and adds a matrix obtained for each subspace according to the value of the input color data. A color data correction device characterized in that the correction matrix is obtained by weighted addition.