JP2575134B2 - Color estimation method by color patch - Google Patents

Abstract

PURPOSE:To record a color picture based on corrected color separation picture information by interpolating with a curve approximation by the use of the colors of color patch points more than three points at the time of matching a coordinate system constituted of a basic color to the coordinate system of a color specification system. CONSTITUTION:8 bit and 9 bit intervals are distributed in a mixed form as a lattice point. The data of four bits for referring to a weight coefficient in which the maximum distance between the lattice points corresponds to the 9 bits is supplied to a weight coefficient storing means 24 side from an address signal forming means 40. A control signal for sequentially selecting chips is supplied to LUTs 21-23 for color correcting data, the color correcting data is sequentially read and supplied to a multiplying and accumulating means 30. In the means 30, the corrected values of respective colors are sequentially calculated and the data of the high order 8 bits of the accumulated outputs are sequentially outputted for every color. At the time of increasing the number of color patches, the interpolation is carried out by the curve approximation using the lattice points more than three points, so that an interpolating point can be correctly calculated to remarkably improve a color reproductivity.

Description

DETAILED DESCRIPTION OF THE INVENTION [Industrial Application Field] The present invention relates to color correction between different color systems, such as when a television image signal is hard-copied using a video printer, a digital color copier, or the like. The present invention relates to a color estimation method using a color patch suitable for being applied to a color measurement system such as when (color proof) is performed.

[Background of the Invention] When a television image signal is hard-copied by using a video printer, a digital color copier, or the like, the color systems are different from each other. A color separation image correction device is often used for color correction such as correction.

For example, as is well known, a color masking device, which is one of the color separation image correcting devices, cancels a sub-absorption amount of a color material (a dye such as a toner, an ink, a thermal transfer ink, and a photographic paper) to cancel a correct color (a dye). (Intermediate color).

That is, a television image is formed into a color image by an addition method, and its color system uses the R, G, B coordinate system of the phosphor. On the other hand, a photographic paper or the like forms a color image by the subtractive color method, and its color system uses a color system such as L ^* , u ^* , v ^* . In such a case, it is necessary to convert (color correct) the signal data between these color systems.

For example, in the color masking device 10 shown in FIG.
New image data (image data after color correction, in this example, cyan C, magenta M, and yellow Y) is formed by numerically calculating the input three primary color image data of R, G, and B, A color image is recorded based on the new image data C, M, Y.

In FIG. 1, reference numeral 11 denotes a television receiver, 12 denotes a color printer, and 13 denotes a recording medium such as photographic paper.

If the color characteristics of a color printer or the like can be accurately grasped, the combination of the basic colors (three or four colors) that reproduces a specified color can be accurately determined, thereby reducing the color conversion error and color reproduction. Sex is greatly improved.

A basic color (3 colors or 4 colors) that reproduces a specified color
Conventionally, the following two methods are known as a method for calculating the combination of colors.

When making a hard copy using photographic paper, etc.
As shown in FIG. 26, the spectral absorption densities of each of the single colors (Y, M, C) are measured, and the total absorption characteristics are calculated using the density additivity. After that, it is converted into a color system such as X, Y, Z, L ^* , u ^* , v ^* .

The density additiveness is a method of calculating by adding the density of each color at each spectral absorption density.

In printing or the like, a combination of basic colors is estimated by the Neugebauer equation.

[Problems to be Solved by the Invention] By the way, among the above calculation methods, in the case of photographic paper,
Concentration additiveness does not hold in an actual system. for that reason,
Poor accuracy when estimating color reproducibility.

Even when the Neugebauer equation is used, since it is an approximate expression, the difference between the approximate expression and the actual value is large, and the accuracy of color reproducibility is not sufficient.

As one method of solving this problem, a method of directly recording a color image from a television image signal on a recording medium such as photographic paper, directly measuring the color of the recorded image, and calculating a correction value is considered. .

In such a case, it is preferable to perform colorimetry based on a plurality of color images obtained by combining a plurality of basic colors, that is, a color patch image, since a colorimetric point can be clearly specified.

This is because, when a color patch image is formed, the larger the number, the larger the number of colorimetric points, and the more accurate correction points can be obtained.

However, if the number of color patches is increased indiscriminately, the number of colorimetric points will increase in proportion to it, so simply increasing the number of colorimetric points would not be advisable simply by unnecessarily lengthening the colorimetric time. It is hard to say that it is a solution.

In view of the above, the present invention has solved such a problem, and has proposed a color estimation method using color patches that can expand and multiply the apparent number of color patches without increasing the number of color patches to be measured. It is a suggestion.

[Technical Means for Solving the Problems] In order to solve the above problems, in the present invention,
When estimating an intermediate color of a certain color system obtained by mixing a plurality of basic colors constituting a color separation image, a plurality of color patches are created in advance by a combination of a plurality of basic colors, and each coordinate of the color system is estimated. Each time, the number of color patches is increased by performing curve interpolation using the color coordinate system of the corresponding coordinates of the three or more color patches that have already been created, and the color created in advance using the increased color patches It is characterized in that point color estimation is performed by a combination of basic colors other than patches.

[Operation] When the basic colors are three or four, the coordinate system constituted by these basic colors is three-dimensional (super-solid in the case of four colors).
And the color system corresponding to this three-dimensional object is also three-dimensional. However, the color system is not a simple three-dimensional, but very complex.

Therefore, when associating the coordinate system composed of the basic colors with the coordinate system of the color system, points other than a plurality of color patches are not interpolated by simple linear approximation, but instead of 3 points.
Interpolation is performed using the colors of the color patch points above the point, that is, by curve approximation.

According to this curve interpolation, even in a distorted solid, points in the solid can be estimated with high accuracy.

The following processing steps are conceivable for creating a color patch and calculating the amount of mixing of the basic colors.

First, there is a step (first step) of previously outputting a plurality of samples having a color tone close to the intermediate color to be obtained.

Secondly, there is a step (second step) of examining the mixing amount of the basic color of each sample and the value of the color system for the mixing amount.

Third, there is a step (third step) of performing a convergence operation using the values of the color system of the sample.

By the third step, the amount of mixing of the basic colors for reproducing the intermediate color is calculated.

The sample in the first step is obtained as follows.

It is actually printed on photographic paper by a signal of n discrete points (the sum of which is nnnn points) for a basic color composed of a specific color system, for example, a Y, M, C coordinate system. Print in color.

By measuring the color of a color-printed color patch image and plotting the measured data on a color system of photographic paper (for example, L ^* , u ^* , v ^* color system, the same applies hereinafter), Y, The colors in the M and C coordinate systems are mapped as values in the L ^* , u ^* , v ^* color system. This mapped value becomes the sample value.

In order to convert the measurement data into a value of a specific color system, a specific conversion formula for the color system is used.

In the third step, the sample values closest to the intermediate color are calculated by converging while sequentially interpolating the sample values. The convergence sample value is used as the basic color mixture amount (Y, M,
C (each color data of C).

A plurality of these mixing amounts are prepared as color correction data,
These are referred to by the input color information.

In the color separation image correcting apparatus, these color correction data are tabulated, and the corresponding color correction data is referred to by the input color separation image information.

Thus, a color image can be recorded based on the corrected color separation image information.

[Embodiment] Next, a case where an example of a color patch color estimation method according to the present invention is applied to the above-described color separation image correction method will be described in detail with reference to FIG.

First, the basic principle of the color separation image correction method to which the present invention is applied will be described.

For convenience of explanation, a case where the basic colors are three colors of Y, M, and C will be described.

Intermediate colors on a recording medium, for example, a color photographic light-sensitive material such as photographic paper, can be expressed innumerably by combining the densities of Y, M, and C, but the expression range is shown in three dimensions. When expressed in a coordinate system of Y, M, and C, the expression range is a cube as shown in FIG. Change the coordinate system of Y, M, C to another color system, for example, X,
When converted into the Y, Z color system, a three-dimensional object is obtained as shown in FIG.

 In the figure, vertices A to H correspond to A 'to H'.

As is apparent from FIG. 2, most of the solids that determine this expression range are distorted, and each side is not necessarily a straight line, and each side is a complicated curved surface.

Within this solid, a predetermined intermediate color can be reproduced by an appropriate combination of Y, M, and C. Therefore, the color correction data must be formed so as to fall within this three-dimensional object.
The present invention proposes a method for determining the mixed amount of Y, M, and C so as to fall within this solid.

For simplicity, the basic colors will be described as two colors (for example, Y and M), and then the algorithm using the original basic colors will be described.

FIG. 3 shows a coordinate system of Y and M, which is mapped to an L ^* , u ^* , v ^* color system as shown in FIG. Vertices B, C,
G and F correspond to B ', C', G 'and F'.

Each intersection in FIG. 3 (5 × 5 = 25 grid points in the embodiment)
Is supplied to a color printer, and the color level is recorded on a recording medium (hereinafter referred to as photographic paper) to form a color patch.

The actual color was measured from the obtained color patches, and the measured values were converted into color system values (sample values) using a color system conversion formula, and this was plotted for each grid point. Fig. 4 shows this.

Although the number of color patches does not exceed a large number, it takes time for actual color measurement, and therefore, about 5 × 5 = 25 color patches are used in the embodiment.

Then, in order to increase the apparent number of color patches, in the present invention, the number of color patches is expanded and multiplied by arithmetic processing. At this time, the colors of the points other than the color patches are calculated by curve approximation using three or more previously obtained points of the color patches.

The reason why the curve interpolation is used as the interpolation processing is based on the following reason. That is, the solid representing the color system corresponding to FIG. 2 is distorted as shown in FIG. Therefore, a more accurate interpolation point is estimated by approximating a curve using three or more points as described above. In the curve interpolation, in addition to the interpolation of the interpolation points in FIG. 3, the interpolation processing using three or more sample points is similarly performed for the interpolation points in FIG. 2 corresponding to the interpolation points in FIG. Becomes

By such an interpolation process, for example, by interpolating the middle of 5 × 5 = 25 color patches, 9 ×
It can be expanded and expanded to 9 = 81 color patches.

In the example shown below, combinations of basic colors are estimated by 5 × 5 = 25 color patches.

Here, as shown in FIG. 4, when a certain intermediate color is represented by x (referred to as a target value T ′), the combination of the Y and M coordinate systems indicating this color is represented by grid points a to d in FIG. It is presumed to be within the enclosed area.

The arithmetic processing of which grid point is closest is obtained by converging the color system of FIG. 4 while associating it with the coordinate system of FIG.

As described above, the convergence operation is performed using only the color system of FIG. 4 and the convergence result is not estimated in association with the coordinate system of FIG. This is because, although the conversion for the color system is known, the reverse conversion operation is very complicated, and its preferred conversion formula is not yet known.

For this reason, the target value T shown in the coordinate system of FIG. 3 is to be estimated by the following processing. The estimation processing operation will be described in detail with reference to FIGS.

First, a grid point closest to the target value T 'is calculated using the target value T' and a total of 25 basic grid points (see FIG. 4).

In practice, a grid point at which the difference between the two is minimized is calculated. Assuming that the grid point is b ', the target value T can be estimated to be close to the grid point b corresponding to the grid point b' in FIG.

Next, a total of eight grid points (division points) surrounding the grid point b are set at a level interval at which the grid point interval becomes 1/2, and these grid points are calculated by the weighted average of surrounding grid points. .
For example, two or four surrounding points and grid points are weighted and averaged.

The values corresponding to the newly calculated grid points e to l are plotted again in the color system of FIG.

Then, the plotted grid points e 'to l' (total 8
Of the grid points closest to the target value T ′ are obtained by the same method as described above, and the grid point (in this example,
h ′) and the eight grid points m to t including the grid point h in FIG. 5 are calculated by further reducing the grid interval to half.

By repeating such a division of the grid, the grid gradually narrows and eventually ends. The target value T in FIG. 5 corresponding to the converged lattice point value indicates a combination of basic colors (a mixed amount of Y, M, and C) for reproducing the intermediate color.

The above estimation operation is executed for each given target value. It is also possible to construct a table of the estimated target values and to refer to the target values by the values of the input color separation image.

Actually, when applied to a color separation image correction device or the like, a lookup table is used. One example will be described later.

An algorithm when three colors are used as basic colors will be described below.

It is assumed that each of Y, M, and C has a level of 256 steps from 0 to 255. Of these levels, in this example,
Five levels are extracted. For example, five levels 0, 64, 128, 192 and 255 are extracted for each of Y, M and C. Color patches of colors (5 × 5 × 5 = 125) of all combinations are created.

An example of a color patch is shown in FIG. As the color system of the color patches, LIE, L ^* , u ^* , v ^* , L ^* , a ^* , b ^* color system of CIE are suitable.

The color patches do not always have the same number of levels for each color.
That is, when a color patch is configured in consideration of the human eyes' discrimination ability, generally, each color does not have the same number of levels. That is, the human eye's discrimination ability is M
This is because (magenta) is the highest and Y (yellow) is the lowest, and accordingly, it is conceivable that the color patch also has a small Y and a large M according to this.

FIG. 8 shows an example of such a case, and exemplifies a case where Y, M, and C = 3 × 5 × 4. As a result, the number of color patches is reduced, and the actual measurement time of the color separation is reduced.

When these relationships are generalized, the number of patches PY, PM, and PC of Y, M, and C may be set so as to satisfy the following relationship.

PY <PC ≦ PM When the number of color patches is increased by interpolation processing as in the present invention, the following is performed.

As a basic lattice, when 5 × 5 × 5 = 125, L ^* , u ^* ,
v ^{* The} color system is interpolated by curve interpolation as shown in the following calculation example.

In this case, as shown in FIG. 9, when a black circle is a grid point (sample point), and if a mark and a mark are points to be interpolated, the grid points are shifted forward and backward by two points as shown by the mark. In the case where it exists, and in the case where there are one point and three points before and after as indicated by a cross,
Different interpolation formulas are used.

When the color system of the point to be _{^{interpolated, L m *, u m *}} , and v _m ^*, the color system of each sample ^point, Li ^*, ui ^*, was vi ^{* (i} = 1~4) When there are two grid points before and after each point as indicated by the triangles, the interpolation is performed by the following interpolation formula.

^{_{L m * = - (1/16)}} L1 * + (9/16) L2 * + (9/16) L3 * - (1/16) L4 * u m * = - (1/16) u1 * + ( 9/16) u2 ^* + (9/16) u3 ^* -(1/16) u4 ^* v _m ^* =-(1/16) v1 ^* + (9/16) v2 ^* + (9/16) v3 ^* In the case where one point and three point lattice points exist before and after as indicated by − (1/16) v4 ^* × mark, the following interpolation formula is used.

^{_{L m * = (5/16) L1}} * + (15/16) L2 * - (5/16) L3 * - (1/16) L4 * u m * = (5/16) u1 * + (15 / 16) u2 ^* -(5/16) u3 ^* -(1/16) u4 ^* v _m ^* = (5/16) v1 ^* + (15/16) v2 ^* -(5/16) v3 ^* -(1 / 16) v4 ^* An example of the order of the interpolation processing is shown in FIG. Numbers I, II, III
Are interpolated in this order.

By such interpolation processing, the number of color patches can be expanded and multiplied to 729 by electrical processing, although the actual measurement is only 125 color patches, and the Y, M, C coordinates at that time The color patches shown in the system are as shown in FIG.

This is mapped to the L ^* , u ^* , v ^* color system as shown in FIG.

FIG. A is a color system viewed from the vertex side in FIG. 11, FIG. B is a mapping on the L ^* , v ^* plane side, and FIG. C is a mapping on the L ^* , u ^* , plane side. is there.

The above-described process of estimating the target value T is performed using a total of 729 color patches created by such an interpolation process.

Here, in order to calculate which grid point the target value T 'is close to, it is sufficient to use the following evaluation function △ E.

^{_{△ E = | L T * -Li}} * | + | u T * -ui * | + | v T * -vi * | △ E = [(L T * -Li *) 2 + (u T * -ui * _{^{) 2 + (v T * -vi}} *) 2] no problem using either ^1/2 evaluation function.

In the case where all the final target values T are calculated by the convergence calculation process, and when the interval of the basic lattice is divided by 64 quantization steps as in the above example, the lattice interval (division Spacing) is 32, so in such a case the grid spacing
The algorithm is completed by sequentially repeating the convergence processing a total of five times of 16, 8, 4, 2, and 1.

As a result, the target value can be estimated with sufficient accuracy.

In the case where the color patch as shown in FIG. 11 is obtained by the interpolation process, in the first to fifth convergence processes, the calculation of the interpolation points (the vertices of the solid) is performed as shown in FIG. It can also be calculated by curve approximation in the case of interpolating △ and × marks from grid points indicated by black circles,
The following examples are all based on linear approximation.

 The interpolation processing by the linear approximation is as follows.

Assuming an interpolation point s as shown in FIG. 13, when the L ^* , u ^* , v ^* color system of the interpolation point s is Ls ^* , us ^* , vs ^* , the interpolation is An example of the equation is shown below.

The interpolated color system Ls ^* , us ^* , vs ^* is associated with the value of the Y, M, C coordinate system.

Mi is the volume of a rectangular parallelepiped including the diagonal vertices and including the interpolation point s, and in the case of FIG. 11, Becomes A specific example of the interpolation will be described in a color-divided image estimation device described later.

By the way, in the above description, the estimation processing when any of the target values T is inside the solid shown in FIG. 2 has been described. However, when the target value T exists outside the solid as shown in FIG. 14, the following processing is performed. Presumed. To simplify the explanation, Y,
M and C coordinate systems are not used.

The reason why the target value T ′ exists outside the solid is that the color reproduction range of the output system is narrower than the color reproduction range of the input system.

In this case, the color is moved in the achromatic color direction without changing the hue of the color, and the color of the point intersecting the straight line 1 in the achromatic color direction and the boundary of the color reproduction range is used as the target value T ^*. It is to be.

Also in this case, it is considered that the target value T ^* is on the line connecting the lattice points q1 and q2 in FIG.
The estimation is performed by dividing and converging q1 'and q2' (FIG. 14) while associating them with the Y, M, and C coordinate systems.

The following algorithm is added to the algorithm of this estimation operation in addition to the above-mentioned algorithm.

First, when any of Y, M, and C is 0 or the maximum, it is determined that the target value T 'is outside the solid, that is, outside the color reproduction range.

In this case, as shown in FIG. 15, a straight line passing through the target value T ′ and an achromatic axis (this is a point on the L ^* axis) is assumed.
The straight line (hereinafter referred to as a convergence line) l and the inclination θ with respect to the u ^* , v ^* plane are represented as follows.

1 = ar + b θ = arc tan (u _T ^* / v _T ^* ) Here, a and b are arbitrary real numbers, and are different from a and b in FIG.

When setting not to change the lightness in addition to the hue, 1 = LT ^* .

Next, cylindrical coordinates (θ, r, l) = (hue, saturation, lightness) of the sample points on the outer surface are calculated and stored in a memory.

Then, among the sample points of the outer surface stored in this manner (the lattice points indicated by black circles in FIG. 16), the smallest quadrilateral consisting of four sample points is assumed, and their cylindrical coordinates are assumed. Is represented by (θi, ri, li).

It is checked whether any of the four points satisfies the following conditional expression.

θ ≦ θi ≦ θ + 180 ° (i = 1~4) θ-90 ° ≦ θi ≦ θ + 90 ° (i = 1~4) θ-180 ° ≦ θi ≦ θ (i = 1~4 ) ar i + b-l i ≧ 0 (i = 1 to 4) ar _i + b−l _i ≦ 0 (i = 1 to 4) When these conditions are satisfied, the convergence line 1 passes through the set minimum quadrilateral. Probability is high.

Although there are countless such conditional expressions, the conditional expressions described above are examples in which any of them can be performed by simple calculations.

Next, this quadrilateral is obtained by averaging the weights from its vertices to obtain the midpoint indicated by a circle in FIG. 16, and the outer surface is divided into four.

Again referring to the above conditional expression for these four surfaces,
Thereafter, the same operation is repeated seven times. Then, the average value of the values of the Y, M, C coordinate systems corresponding to the seventh vertex is used as the substitute value T ^* of the target value T.

Next, an example of a color separation image correction apparatus (color masking apparatus) that embodies the above-described color separation image correction method according to the present invention will be described in detail with reference to FIG.

In this embodiment, the target value calculated as described above, that is, the color correction data is stored in the LUT (lookup table) in advance. For example, if the input system is color CR
In the case of T, the basic color coordinate system (No.
The color correction data of each grid point associated with the coordinate system (similar to the coordinate system in FIG. 11) is stored, and the color correction data other than the grid points is calculated by interpolation.

When there are few input gradations or output gradations, all color correction data can be stored in memory instead of such discrete color correction data.

The interpolation process of the corrected color data will be described with reference to FIG.

In this example, eight color correction data (C, M, Y) including a rectangular parallelepiped space W (interpolation point s is at diagonal vertices) determined by three input image data R, G, B A rectangular parallelepiped space region V formed by the known calculated color correction data P1 to P8) is determined. Each of the spatial regions W and V has P1 as a reference point. Then, it is assumed that each of the colors has a color correction value as described above for the combination color at each point of 0, 32, 64, 96, 128, 160, 192, 224, 255. At this time, the input image data R,
When G and B have values of (100, 130, 150), interpolation is performed using the color correction data of the vertices (grid points) of the space area surrounded by the following eight points.

Here, Pi on the left side (i = 1 to 8) indicates the coordinate value of each vertex of the space area V, and the right side is the color correction data Ci, M at that time.
i and Yi are shown.

P1: (96,128,128) = (C1, M1, Y1) P2: (128,128,128) = (C2, M2, Y2) P3: (96,160,128) = (C3, M3, Y3) P4: (128,160,128) = (C4, M4, Y4) P5: (96,128,160) = (C5, M5, Y5) P6: (128,128,160) = (C6, M6, Y6) P7: (96,160,160) = (C7, M7, Y7) P8: (128,160,160) = (C8, M8, Y8) Therefore, the relationship between the space region V having each of the vertices Pi and the space region W formed by the input image data is as follows.
It becomes as shown in FIG.

The weight coefficient for each vertex Pi in the space area V is calculated as follows.

As a method of calculating the weight coefficient, the above-described L ^* , u ^* , v
^The same calculation formula as in the color system of ^* can be used.

In this method, the volume of a rectangular parallelepiped space region W formed by the vertex opposite to the point of the correction value to be obtained and the interpolation point s is used as a weight coefficient at the point of the correction value to be obtained.

Therefore, using the coordinates of P1 and the coordinates of s, the weight coefficient of the point P8 is (100,130,150) − (96,128,128) = (4,2,22). Is 4 × 2 × 22 = 176, which is the weight coefficient of the point P8.

Similarly, the weight coefficients of the remaining points P1 to P7 are calculated.

P1 = 8400 P2 = 1200 P3 = 560 P4 = 80 P5 = 18480 P6 = 2640 P7 = 1232 P8 = 176 The sum of these weighting factors is the same as the volume of the cubic space region V. In this example, 32768 (a ). Accordingly, correction value Cs in s point, Ms, Ys becomes Cs = 1 / a (P1C1 + P2C2 + P3C3 + P4C4 + P5C5 + P6C6 + P7C7 + P8C8) Ms = 1 / a (P1M1 + P2M2 + P3M3 + P4M4 + P5M5 + P6M6 + P7M7 + P8M8) Ys = 1 / a (P1Y1 + P2Y2 + P3Y3 + P4Y4 + P5Y5 + P6Y6 + P7Y7 + P8Y8). That is, the correction value of a point s to be obtained and the eight points surrounding the point s is Ci, Mi, Yi (this is the interpolation value L of the color system).
s ^* , us ^* , vs ^* are values in the Y, M, and C coordinate systems) and each weighting factor is Ai, Can be represented by

 The point of the color correction data described above is an example.

Actually, the number of color correction data is set to a power of 2 in consideration of the capacity of the ROM and the like. Therefore, 256kbit RO
When M is used, 32 points of color correction data (32 ³ = 32768 points for all three colors) can be provided for each color.

 FIG. 18 shows an example of the color masking apparatus 10.

As is apparent from the above-described arithmetic expression, the color masking device 10 includes a color correction information storage unit (color correction data storage unit) 20 for storing a plurality of color correction data, and a weighting information storage unit (weight coefficient storage unit). 24, multiplication / accumulation means 30 for multiplying the referenced color correction data by the weighting coefficient and accumulating the values, and processing means comprising division means. Among them, the dividing means can be omitted depending on the configuration.

The color correction data storage unit 20 divides a color space formed by the three-color separation image information that can be input for color correction into a plurality of space areas, and performs color correction on a combination of the three-color separation image information located at the vertex. Information is stored.

The weighting coefficient storage means 24 outputs weighting information for each of a plurality of pieces of color correction information selected from the color correction information storage means based on the input three-color separation image information.

In the processing means, a plurality of color correction information selected from the color correction data storage means 20 based on the input color separation image information,
Based on the weighting coefficient, the corrected color separation image data to be finally obtained is calculated and output.

FIG. 18 shows a case where the present invention is applied to a simultaneous color masking apparatus for simultaneously obtaining three pieces of color correction data C, M and Y, and FIG. 24 shows three pieces of color correction data C, M and Y. To
For example, it was made to output sequentially in these order,
This is a case where the present invention is applied to a so-called sequential color masking apparatus.

Next, the simultaneous color masking device shown in FIG.
The configuration of each part of 10 will be described.

20 is a color correction data storage means, in this example, each color C, M, Y
Is stored in each of the LUTs 21 to 23. Numeral 24 is a weight coefficient storage means, which is also configured as an LUT.

A read address signal is supplied to the color correction data storage means 20 and the weight coefficient storage means 24, respectively. Therefore, the input image data B, G, R are once supplied to the address signal forming means 40, and an address signal corresponding to the input level is output. Address signal output means are also LUT41 ~ 43 respectively
It consists of. As the LUT, a bipolar ROM is preferable. These LUTs 41 to 43 are further supplied with a 1-bit distribution signal from the controller 50, the details of which will be described later.

The color correction data referred to by the address signal corresponding to the input level of the input image data and the data indicating the weighting coefficient (hereinafter simply referred to as weighting coefficient) are sequentially supplied to the multiplying and accumulating means 30 for a total of eight times.

As described above, the multiplication / accumulation means 30 uses AiKi (Ki is C, M, Y
) Are sequentially executed, and their sum is calculated. In this example, the multipliers 34 to 36 and the accumulator 37 are used.
~ 39.

Therefore, each of the multipliers 34 to 36 uses a 512-Kbit ROM, which is supplied with the corresponding color correction data (8 bits) and the weighting coefficient Ai, and executes a multiplication process of AiKi. The multiplied outputs of the upper 8 bits are supplied to the subsequent-stage accumulators (ALU) 37 to 39, and the multiplied outputs are sequentially added.

The accumulators 37 to 39 are operated with 16-bit precision, and the higher 8 bits are used as the cumulative calculation power (product sum output). As a result, the same output as obtained by dividing the cumulative calculation power by the weight coefficient Ai is obtained. That is, by doing so, the divider can be omitted.

The cumulative calculation power of the upper 8 bits is latched by latch circuits 45 to 47, respectively. The latch pulse is generated by the controller 50.

 The configuration of each unit will be described in more detail.

The color correction data storage means 20 stores each color C, M,
LUTs 21 to 23 that store accurate color correction data corresponding to Y
Is used.

When a 256 Kbit ROM is used as the LUTs 21 to 23, only 32 points are extracted from the minimum level to the maximum level of the input image data. With this, per color
The color correction data of 32 points (thus, 32 ³ = 32768 points for ^three colors) can be stored.

Therefore, when the input level is 256 gradations, the distribution of 32 points is divided into “8” in order from 0, for example, as shown below, and a total of 32 points of 0,8,16,. Distribute evenly so that it becomes an individual and get the 33rd point
Do not use from 249 to 255 points. Or 249-255
Is treated as 248.

The color correction data at each of these distribution points is accurately calculated, and the calculated plurality of color correction data is stored in each LUT2.
These are stored in 1 to 23.

If the distribution points are set to 32 in this way, a general-purpose ROM with 8-bit output can be used, so that there is an advantage that the storage means 20 can be configured at low cost.

The LUT 24 for the weight coefficient storage means stores the weight coefficient Ai at each distribution point. Now, as described above, 8
When bits are distributed, the total of the eight weighting coefficients Ai is 8 × 8 × 8 = 512, but as described above, a commercially available general-purpose IC having an output of 8 bits
If you are going to use, the number of elements will increase if you have the weighting factor as the theoretical value (up to 512), so in this example the approximate value obtained by compressing the theoretical value to almost half is used as the actual value. You.

In the example shown below, the sum of the eight weighting factors is always set to 256, and the maximum weighting factor of each is 255
And

In such a case, for example, in FIG. 17, when s is located at the same position as P1, the weighting factors of P1 to P8 are represented by their theoretical values in parentheses (P1, P2, P3, P4, P5). , P6, P7, P8 255, 0, 0, 0, 0, 0, 0, 1 (512, 0, 0, 0, 0, 0, 0, 0), and the total sum of the weighting coefficients is 256.

Also, s is halfway between P1 and P3, and P1 to 3 (accordingly, P3
, The weighting factors of P1 to P8 are as follows.

P1, P2, P3, P4, P5, P6, P7, P8 160,0,96,0,0,0,0,1 (320,0,192,0,0,0,0,0) Each weight coefficient is appropriately selected such that the sum of the weight coefficients is 256.

Similarly, s is separated from the plane of P1 to P4 by 3 and P1, P3,
If the plane is separated from the planes of P5 and P7 by 1 and the plane of P1, P2, P5, and P6 is separated by 5, the following weighting factors P1 to P8
Becomes

P1, P2, P3, P4, P5, P6, P7, P8 53,7,88,12,32,4,53,7 (105,15,175,25,63,9,105,15) and the weighting factor in this case Are appropriately selected such that the sum of the weights becomes 256.

The 1-bit distribution signal described above is a control signal for specifying color correction data before and after including the point s.

That is, for convenience of explanation, the relationship between 32 distribution points (grid points) and their corresponding address signals is set as shown in FIG.

Now, when the level of the input image data is 100, an address signal (12, 13) is output from the color correction data storage means 20 so that the color correction data (96 and 104) before and after including the input level is output. Need to be formed.

Therefore, when the distribution signal is 0, an address signal (12) that refers to the smaller color correction data (96) is output. When the distribution signal is 1, the larger color correction data (104) is output. Address signal (1
3) is controlled to be output.

However, when the allocation signal is 0 at the maximum value of the value to be used (248 in this case), the color correction data of its own value is selected, and when the allocation signal is 1, the smaller color correction data ( In this case, select 240).

 The distribution signal is also supplied to the weight coefficient storage means 24.

By the way, when a recording medium such as photographic paper is used, there is a sensitivity difference between lots. Therefore, if such a sensitivity difference is taken into consideration, a color that can correct a plurality of sensitivity differences according to each lot. It is necessary to have correction data. However, it is practically impossible to prepare the color correction data storage means 20 according to the sensitivity difference as described above, and it is not practical.

If the configuration is such that the color correction data storage means 20 is commonly used, it can be realized without much difficulty.

FIG. 20 is an example of a color masking device 10 suitable for use in such a configuration, and includes input image data B,
G and R are once supplied to the color masking device 10 via LUTs 55 to 57 for input value correction. The color correction data storage means 20 stores color correction data corresponding to one type of sensitivity.

The corrected image data is calculated from the color correction data from the color correction data storage unit 20 and the weight coefficient at that time. The corrected image data is used as sensitivity correction LUTs 61-63.
And a correction is made according to the sensitivity of the photographic paper to be used.

Here, a plurality of sensitivity correction values corresponding to the difference in sensitivity are stored in the sensitivity correction LUTs 61 to 63, and the correction value is selected according to the sensitivity of the photographic paper to be used.

The input / output characteristics of the sensitivity correction LUT take into account human visual characteristics. Then, the use of the sensitivity correction curve of the input / output characteristics as shown in FIG. 21 can minimize the occurrence of the false contour due to the quantization error.

By the way, in the above-mentioned example, the configuration is not made to use the 256 gradations in full. However, for example, by following the following idea, a color masking device using the 256 gradations in full can be realized. See Figure 24).

For this purpose, grid points are first allocated in a mixed form of 8-bit intervals and 9-bit intervals. By using the mixed type, an identification signal of an 8-bit interval and a 9-bit interval is prepared. Therefore, the relationship between the output of the address signal forming means 40, the grid points and the identification signals is set as shown in FIG.

As a result, for example, when the input is 216, the relationship between the output from the address signal forming means 40 and the output from the controller 50 is controlled as follows.

Address signal to the distribution signal 0 1 24 Address signal to the 6 3 20 26 27 Identification signal 1 1 Here, the value of the address signal to the weight coefficient storage means 24 is closest to the input 216 when the distribution signal is 0. The difference (= 6) from the smallest grid point 210 is selected, and when the distribution signal is 1, the difference (= 3) between the input 216 and the next grid point 219.
Is selected.

The identification signal 1 represents grid points at 9-bit intervals, and 0 represents 8
This represents a grid point at a bit interval, and an identification signal is required for the following reasons.

That is, if the intervals of the grid points are different, the spatial region where the grid points of the three colors are formed is not a cube but a rectangular parallelepiped, and its volume is 512 (= 8 × 8 × 8), 576 (= 8 × 8 × 9). ) 648 (= 8 × 9 × 9) and 729 (= 9 × 9 × 9). For this reason, an identification signal of whether one side is 8 bits or 9 bits is required.

Further, in the weight coefficient storage means 24, each weight coefficient is set in accordance with the identification signal so that the sum of the weight coefficients is also 256.

 For example, when the image data value of each color is (64,143,216), the result is as shown in FIG.

Therefore, the final color correction data is obtained from the weighting coefficients and the color correction data as shown in the figure, according to the above-described calculation formula.

By appropriately selecting the bit interval between grid points in this way, 25
Six gradations can be used fully. However, in this case, it goes without saying that the controller 50 is configured to generate the identification signal as described above.

FIG. 24 shows a color masking apparatus 10 constructed in a sequential manner.
In the case where the present invention, particularly, a configuration in which 256 gradations are fully used, is applied, portions corresponding to those in FIG. 18 are denoted by the same reference numerals, and description thereof is omitted.

In this example, since the maximum distance between lattice points is 9 bits, 4-bit data is used as an address signal for weighting coefficient reference corresponding to this distance.
LUT) 40 to the weight coefficient storage means 24 side. The address signal forming means 40 further outputs an identification signal (1 bit configuration) at an 8-bit interval and a 9-bit interval, and this is supplied to the weight coefficient storage means 24.

LUTs 21 to 23 for color correction data have their control terminals ▲
Control signals ▲ ▼, ▼, for sequentially selecting chips
▼ and デ ー タ are supplied, and color correction data is sequentially read from each of the LUTs 21 to 23, for example, and then supplied to the multiplication / accumulation means 30.

Also in the multiplying and accumulating means 30, the correction value calculation for each color is sequentially processed.

As shown in the figure, the multiplying and accumulating means 30 uses a multiplying and accumulating unit constituted by a single chip as shown in FIG.
Are sequentially output for each color of the upper 8 bits.

The controller 50 includes a ninth decimal counter 51 and a latch circuit 52 for adjusting output timing. The reference clock to the counter 51 is commonly supplied to the clock input terminals Xck and Yck of the accumulator 30.At this clock timing, the color correction data Ki and the weight coefficient Ai input to the X and Y terminals are calculated. Each data is processed. Then, at the next timing when the product-sum output over eight times is obtained, the output terminal ZOU
A clock obtained by counting down the reference clock to 1/9 is supplied to the Zck terminal so that the final color correction data is output from T.

When the level of the arithmetic processing control pulse supplied to the accumulate terminal ACC is 1, the product-sum processing of X · Y + Q (Q is the immediately preceding product-sum output) is executed. The 0-level control pulse is generated at each timing when the ninth reference clock is obtained, whereby the product-sum output is reset and prepared for the next color correction arithmetic processing.

Therefore, at the time of this reset, all 0
Of the storage means 24 so that the weight coefficient of
A reset signal is supplied to the terminal. As a result, Yin is data by the pull-down resistor R _P 0 becomes X · Y (=
0) is executed.

The embodiment described above can be modified as follows.

First, in the above description, the final color correction data is calculated from the color correction data of eight grid points, but may be interpolated from the color correction data of two diagonal vertices. Such an interpolation method is particularly suitable when color correction data of more points than the above is used as color correction data.

Secondly, in the above description, the color correction data is stored in the LUT having a ROM structure. However, a RAM is used as the color correction data storage means, and another memory (ROM) is used for storing the color correction data.
Or disk memory, etc.), and if necessary, read out the color correction data from this separate memory and write it to RAM for use.

According to this configuration, since the S-RAM can be used as the RAM, the speed of the arithmetic processing time can be increased.

In such a configuration where another memory is used and downloaded when necessary, the other memory stores color inversion data, data for selecting a certain output color, data in which the color tone is changed according to the type of illumination light, and color. Data for special effects such as emphasis data can be prepared. You can create special effects relatively easily by downloading and using them as often as you need them.

Third, when the color masking apparatus is applied for printing, it is only necessary to separately prepare an LUT storing black (sumi) data in the color correction data storage unit 20. In this case, it is advantageous to use a sequential color masking device because the configuration can be simplified.

Fourth, in the calculation method of the weight coefficient, the distance from the point Pi may be obtained as an inverse number (or its n-th power) instead of using the volume of the rectangular parallelepiped as the weight coefficient.

Fifth, if a latch circuit is connected between the stages of the color correction data storage means 20 and the multiplication / accumulation means 30, the processing between the stages can be separated from each other, so that high-speed arithmetic processing can be performed.

Sixth, the conversion of the color space coordinates is (B, G, R), (L ^* , a
^* , B ^* ), (X, Y, Z) etc. can be easily understood.

[Effects of the Invention] As described above, according to the present invention, when a plurality of color patches are used to calculate a corresponding color system value, the number of color patches to be measured is increased. And the required number of color patches can be obtained. Therefore, there is an effect that the color measurement time using an actual device can be significantly reduced.

In the case where the number of color patches is expanded and multiplied, interpolation is performed by curve approximation using three or more grid points in the present invention. Therefore, a color specification having a distorted solid as shown in FIG. Even in a system, interpolation points can be accurately calculated.

As a result, the accuracy in associating the values of the color system with the Y, M, C coordinate system and the like is improved, and the color reproducibility based on the obtained color correction data is significantly improved.

Therefore, according to the present invention, when a plurality of basic colors constituting a color separation image are mixed and an intermediate color of a certain color system is reproduced, a color system value close to a target intermediate color set in the color system is reproduced. A convergence operation is sequentially performed while associating with a value of a coordinate system composed of basic colors, and a target value of a coordinate system corresponding to a color system value closest to a target intermediate color is reproduced. The present invention is extremely suitable for application to a color estimation method using a color patch used in a color separation image correction device that corrects as a combination of colors.

That is, the present invention is extremely suitable for application to the case where color image information is recorded on photographic paper, printing, or the like.

[Brief description of the drawings]

FIG. 1 is an explanatory view of the Y, M, C coordinate system, and FIG. 2 is L ^* , u ^* , v ^*.
FIG. 3 is an explanatory diagram of a Y, M coordinate system which is a more simplified version of the coordinate system of FIG. 1, and FIG. 4 is an explanatory diagram of a color system showing lightness and saturation at that time. 5 and 6 are explanatory diagrams of a color estimation method using color patches according to the present invention, FIGS. 7 and 8 are diagrams showing an example of color patches, FIG. 9 is an explanatory diagram of curve approximation, FIG. 10 is an explanatory diagram of the sample point extension obtained at that time, FIGS. 11 and 12 are explanatory diagrams of the coordinate system and color system obtained by the sample point extension, FIG. 13 is an explanatory diagram of the interpolation process, FIG. 14 is an explanatory diagram when there is a target value outside the solid, FIG. 15 is a cylindrical coordinate diagram showing a color reproduction range in a color system, FIG. 16 is an explanatory diagram of a convergence operation, and FIG. FIG. 18 is an explanatory diagram of an interpolation process similar to the diagram, FIG. 18 is a system diagram of a main part showing an example of a color masking device, FIG. 19 is a diagram showing a distribution relation of grid points, and FIG. Other schematic lines showing an example diagram, FIG. 21 is a diagram showing a sensitivity correction curve used at that time, Figure 22 and Figure 23 is distributed signals, the color correction data,
FIG. 24 is a diagram showing the relationship between identification signals, etc., FIG. 24 is a system diagram similar to FIG. 18 showing still another example of the present invention, FIG. 25 is a configuration diagram of a conventional color separation image correcting apparatus, FIG. It is a spectral absorption density curve figure. 10 color masking device 20 color correction data storage means 30 multiplication accumulation means 40 address signal forming means 50 controller V spatial area W spatial area s interpolation point

Claims (2)

(57) [Claims] When estimating an intermediate color of a certain color system obtained by mixing a plurality of basic colors constituting a color separation image, a plurality of color patches are created in advance by a combination of the plurality of basic colors, For each of the coordinates of the color system, the number of color patches is increased by performing curve interpolation using the color system of the corresponding coordinates of the three or more color patches that have already been created. A color estimation method using a color patch, wherein a color of a point is estimated by a combination of basic colors other than the previously created color patch. 2. A color estimation method using color patches according to claim 1, wherein yellow Y, magenta M, and cyan C are used as the basic colors.