JPS63254889A - Color separation picture correcting method - Google Patents

Abstract

PURPOSE:To reproduce a natural color without changing a hue even at the time of changing a chroma and a brightness of color by compressing the value of an output system in the achromatic color direction of an output color specification system and correcting and using the value obtained by the compression as the value of the output color specification system. CONSTITUTION:In a simultaneous type color masking device 10, color correcting data to respective colors C, M, Y is stored in LUTs 21-23 in color correcting data storing means 20. Input picture data B, G, R are supplied to an address signal forming means 40 and an address signal corresponding to an input level is outputted. A division signal of one bit is supplied to LUTs 41-43 constituting the means 40 from a controller 50. The color correcting data referred by the address signal and data indicating a weight coefficient are supplied to a multiplying and accumulating means 30 eight times in total. The means 30 is constituted of multipliers 34-36, accumulators 37-39 and operated with the accuracy of 16 bits and the accumulated outputs of high order 8 bits are respectively latched by latch circuits 45-47.

Description

[Detailed Description of the Invention] [Industrial Application Field] This invention relates to color correction between different color systems, such as when making a hard copy of a television image signal using a video printer, digital color copying device, etc. The present invention relates to a color separation image correction method suitable for application to (color blueprints).

[Background of the Invention] When making a hard copy of a television image signal using a video printer, digital color copying device, etc., each color system is different, so in order to match the reproduced colors, it is necessary to Color separation image correction devices are often used for color correction such as color correction.

For example, a color masking device, which is one of the color separation image correction devices, cancels the side absorption of coloring materials (toner, ink, thermal transfer ink, pigments of photographic paper, etc.) to produce correct colors. This is a device that makes it possible to reproduce intermediate colors.

That is, a color image of a television image is constructed by an additive color method, and the R, G, B coordinate system of the phosphor is used as the color system. On the other hand, with photographic paper, etc., a color image is constructed using the subtractive color method, and its color system is L*, u
Color systems such as * and v* are used. In such a case, it is necessary to convert signal data (color correction) between these color systems.

For example, in the color masking device 10 shown in FIG. 26, new image data (color-corrected image data, in this example, Cyan, magenta M, and yellow Y) are formed, and a color image is recorded based on the new image data C, M, and Y.

In the figure, 11 is a television receiver, 12 is a color printer, and 13 is a recording medium such as photographic paper.

If you can accurately understand the color characteristics of a color printer, etc.
Since the combination of basic colors (three or four colors) that reproduces a specified color can be accurately determined, color conversion errors are minimized and color reproducibility is significantly improved.

The following two methods are conventionally known as methods for calculating a combination of basic colors (three or four colors) that reproduces a specified color.

When making hard copies using photographic paper, etc., the second
As shown in Figure 7, the spectral absorption density of each monochrome (Y, M, C) is d! 1 and calculate the overall absorption characteristic using concentration additivity. After that, X.

Y, Z, L6. Convert to a color system such as uIll or V*.

Density additivity refers to a method of calculation by adding the densities of each color at each spectral absorption density.

In printing, etc., basic color combinations are estimated using the Neugebauer equation.

[Problems to be Solved by the Invention] By the way, among the above calculation methods, in the case of photographic paper, density additivity does not hold in an actual system.

Therefore, the accuracy when estimating color reproducibility is low.

Even when the Neugebauer equation is used, since it is an approximate equation, there is a large discrepancy between the approximate equation and the actual value, and the accuracy of color reproducibility is also insufficient.

For example, if the color reproduction range of an output system such as photographic paper and the color reproduction range of an input system such as a color CRT are expressed by the same color system such as L*, Mv*, this color system The color reproduction range for the systems generally differs. In the case of the input/output system as described above, the color reproduction range of the output color system is narrower than the color reproduction range of the input system.

Therefore, when color image information that exceeds the color reproduction range of the output color system is input, there is no corresponding value in the output color system. As a result, in the past, color correction data related to color image information that exceeded the color reproduction range of the output color system was appropriately compressed within the color reproduction range.
The hue, saturation, or brightness changed in a direction different from human visual characteristics, which was extremely unnatural.

Therefore, this invention was developed to solve these conventional problems, and it reduces color correction errors, significantly improves color reproducibility, and widens the color reproduction range of the output color system. This allows natural colors to be reproduced even when inputting color image information that exceeds the required color range.

Technical means for solving the L problem 1 In order to solve the above-mentioned problem, in the color separation image correction method according to the present invention, the color reproduction range of the output system is narrower than the color reproduction range of the input system. Sometimes, when color separation image information that exceeds the color reproduction range of the output system is input, the corresponding values of the output system are compressed in the non-coloring direction of the output color system, and The values are modified and used based on the values of the output color system.

[Function] First, there is a step (first step) of outputting in advance a plurality of samples of tone close to the desired intermediate color.

Second, there is a step (second step) of checking the mixing amount of the basic colors of each sample and the corresponding color system value.

Thirdly, there is a step of determining whether or not the target value T' exists outside the color reproduction range of the output color system (third step).
.

Fourth, there is a step (fourth step) of compressing only one of the saturation and brightness of the target value T' without changing its hue.

Fifth, when compressing saturation and/or brightness,
There is a step (third step) of performing a convergence calculation to determine the degree of compression using the values of the color system of the sample.

Through this fifth step, the amount of mixture of basic colors that reproduces the intermediate color is calculated.

The samples in the first step are determined as follows.

It is actually printed on photographic paper by signals from n discrete points (the total is n'n'n points) regarding the basic colors in a specific color system, e.g. Y, M, C coordinate system. Print in color.

By measuring the color of a color print and plotting the measured data on the color system of photographic paper (for example, L", u", v" color system, the same applies hereinafter), the Y, M, C coordinate system can be calculated. The colors are mapped as values in the L'', u'', v'' color system.

This copied value becomes the sample value.

In order to convert the measured data into values of a specific color system, a specific conversion formula for that color system is used.

The third step is a step of determining a specific conditional expression, and the fourth and fifth steps are to move the target value T' toward the achromatic color of the output color system, and to intersect the boundary of the color reproduction range. The color of the point is used as the target value T9.

The target value TI is the mixing amount of the basic color (each mixing amount is Y,
M, C color correction data).

A plurality of these mixing amounts are prepared as color correction data, and these are referenced by input color information.

In the color separation image correction device, these color correction data can be converted into a table, and the corresponding color correction data can be referenced based on the input color separation image information. As a result, a color image can be recorded based on the modified color separation image information.

[Embodiment] Next, an example of a color separation image correction device according to the present invention will be described in detail with reference to FIG. 1 and subsequent figures.

First, the basic principle of this invention will be explained. That is, we will explain the correction method when color image production information that falls within the color reproduction range of the output color system is input, and then explain the correction method when it is outside the color reproduction range.

For convenience of explanation, a case will be explained in which three basic colors are Y, M, and C.

Intermediate colors on a recording medium can be expressed in an infinite number of ways by combining Y, M, and C densities, and the range of expression is shown three-dimensionally. When expressed in the Y, M, C coordinate system, the expression range becomes a cube as shown in FIG. When converting the Y, M, C coordinate system to another color system, for example, the X, Y, Z color system,
It becomes a solid as shown in Figure 2.

In the figure, each vertex A-H corresponds to A'-H'.

As is clear from FIG. 2, most of the solid objects that determine this expression range are distorted, each side is not necessarily a straight line, and each side is a complex curved surface.

Within this solid, a predetermined intermediate color can be reproduced by an appropriate combination of Y, M, and C. Therefore, color correction data must be created to fit within this three-dimensional space.

In this invention, Y, M, C (7)
This paper proposes a method for determining the amount of mixture.

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

Figure 3 shows the coordinate system of Y and M, which are called L* and u*.

■When mapped to the 6 color system, it becomes as shown in Figure 4.

The vertices B, C, G, and F of the square are B', C", and G".

Corresponds to F'.

Each intersection point in Figure 3 (in the example, 5x5=25 grid points)
The color level 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 batch.

Determine the actual color from the obtained color batch, convert the measured value to a color system value (sample value) using the color system conversion formula, and convert this to a color system value (sample value) for each grid point. Figure 4 shows the plot.

Although it is better to have a large number of color batches, since actual color measurement takes time, approximately 5×5=25 color batches are used in the embodiment.

More color batches may be used.

In that case, the number of color batches may actually be increased, or the number of color batches may be increased by interpolation processing. For example, when interpolating the middle of 5×5=25 color batches, this interpolation process extends the color batches to 9×9=81 color batches.

In the example shown below, m combinations of basic colors are determined by 5 x 5''25 color batches.

Here, as shown in FIG. 4, if a certain intermediate color is indicated by x (target value T'), then Y indicates this color.

The combination of M coordinate systems is estimated to be within the area surrounded by grid points a % d in FIG.

The calculation process for determining which grid point is closest is determined by converging the color system shown in FIG. 4 while correlating it with the coordinate system shown in FIG.

In this way, the reason for performing convergence calculations using only the color system in Figure 4 and not estimating the convergence results by associating them with the coordinate system in Figure 3 is to change the coordinate system in Figure 4 from the coordinate system in Figure 3. This is because although the conversion to the color system is known, the reverse conversion operation is very complicated, and the preferred conversion formula is not yet known.

For this reason, the target value T shown in the coordinate system of FIG. 3 is estimated by the following process. The estimation processing operation will be explained in detail with reference to FIGS. 5 and 6.

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

Actually, the grid point where the difference between the two is the minimum is calculated.

Assuming that this grid point is b', it can be estimated that the target value T is close to the grid point corresponding to grid point b' in FIG. 5 as well.

Next, a total of nine grid points (division points) surrounding the grid point are set at level intervals where the grid point spacing is 1/2, and these grid points are calculated by the weighted average of the surrounding grid points. .

For example, it is determined by weighted averaging of two or four surrounding grid points.

The value corresponding to this newly calculated grid point e~1 is plotted again on the color system of FIG. 6.

Then, from among the plotted grid points e' to 1' (9 in total), the grid point closest to the target value T' is found by the same method as described above, and that grid point (in this example, b
The grid point in FIG. 5 corresponding to ') and the eight grid points m to t including this can be calculated by further narrowing the grid interval to 1/2.

By repeating such grid division, the grid becomes progressively narrower and eventually converges. The target value T in FIG. 5 corresponding to the converged value of the grid point indicates the combination of basic colors (mixing 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 create a table of estimated target values and refer to the target values using the values of the input color separation image.

When actually applied to a color separation image correction device, etc.,
A lookup table will be used. An example of this will be described later.

Next, Toza's algorithm using three colors as basic colors will be explained.

It is assumed that Y, M, and C each have a level of 256 steps from 0 to 255. Among these levels, five levels can be extracted in this example. For example, Y, M,
For each of C, 0°64.128.192 and 25
Five levels of 5 are extracted. A color batch of all these combinations of colors (5×5×5=125) is created.

An example of a color batch is shown in FIG. The color system for each color batch is CIE's L*, u*.

V ” + L ” ra ” + b ” color system is appropriate.

Color batches do not necessarily have the same number of levels for each color. That is, in the case where a color batch is constructed taking into consideration the discrimination ability of the human eye, each color generally does not have the same number of levels. Then, the human eye has the highest discrimination ability for M (magenta) and the lowest for Y (yellow).
This is because it is conceivable that color batches may be made with a smaller amount of Y and a larger amount of M.

FIG. 8 shows an example of this, where Y-M-C=3×5×4. As a result, the number of color badges is reduced, and the actual color i1Q+1 time is correspondingly shortened.

Generalizing these relationships, the numbers of patches PY and PM of Y, M, and C are set so that the following relationships are satisfied.

All you need to do is set up your PC.

PY<PC≦PM When increasing the number of color batches by interpolation process 1,
Do as follows.

As a basic lattice, in the case of 5X5X5=125, L'', u
The ",v" color system is interpolated by curve interpolation shown in the calculation example below.

In this case, as shown in Figure 9, if the black circle is a grid point (sample point) and the Δ mark and the X mark are the points to be interpolated, there are two grid points before and after the Δ mark. Different interpolation formulas are used for cases where there are one point and three points before and after the X mark.

The color system of the point to be interpolated is Lm"*u♂,v2, and the color system of each sample point is L i"+ ui"+ vi"
When (i; 1 to 4), the former case is interpolated using the following interpolation formula.

L,”= −(1/16) Ll°+ (9/16)
L 2' + (9/16) 13' - (1/16)
L4"u,"=-(1/16) ul'+ (9/16)
u2”+ (9/16) u3” (1/16) u 4
゜V♂= −(1/16) vl”+ (9/16)
v2”+ (9/1(5) v3”(1/16) v4
゜In the latter case, the following interpolation formula is used:

L−= (5/16) Ll”+ (15/16) L
2" - (5/16) L3゜ - (1/16) L4" U♂ = (5/ 1B) u 1" + (15/16
) u 2°-(5/16) u 3°-(1/16)
u 4” v −” = (5/ 16) v 1°+ (15/
1B) v 2”-(5/16) v 3”-(1/
16) An example of the order of interpolation processing is shown in FIG. 10. Numbers I and II
, I11.

Through such interpolation processing, even though only 125 color batches are actually measured, the number of color batches can be expanded and multiplied to 729 by electrical processing, and the Y, M, C coordinate system at that time can be expanded and multiplied by electrical processing. The color batch indicated by is as shown in FIG.

Mapping this to the color system of Lm, ut, v* gives the first
The result will be as shown in Figure 2.

Figure A is the color system seen from the apex side of Figure 11, Figure B is the mapping on the L''+v'' side, and Figure C is the color system viewed from the vertex side of Figure 11.
``This is a mapping on the surface side.

Using a total of 729 color patches created by such interpolation processing, the above-mentioned target value T estimation processing is executed.

Here, in order to calculate which grid point the target value T' is close to, the following evaluation function ΔE may be used.

ΔE= I LT"-Li" l + l uv"-u
i" I+ I VT"-vi"l ΔE= [(LT"Li") 2+ (ut"-u
i'') 2+(v, @, i3) 2] Any of the 1/2 evaluation functions may be used.

When the final target value T is calculated entirely by convergence calculation processing, and as in the above example, when the basic lattice interval is divided by 64 quantization steps, the lattice interval (division interval) is calculated by the above-mentioned interpolation process. is 32, so in this case, the grid spacing is 16.
．． The algorithm is such that it is completed by sequentially repeating the convergence process a total of five times (8, 4, 2°1).

This allows the target value to be estimated with sufficient accuracy.

When a color patch as shown in Figure 11 is obtained by interpolation processing, the interpolation points (each vertex of the solid) are calculated as described above in the first to fifth convergence processing. Although calculation can be performed by curved approximation, the following examples are all based on linear approximation.

The interpolation process using linear approximation is as follows.

Assuming an interpolation point S as shown in Fig. 13, the L ” * u ” * v ” color system of the interpolation point S is
”.

An example of the interpolation formula when u s", v s" is shown below.

Ls”= (1/4M+)ΣMi−Li”μ^
1 塙 us”=(1/ΣM i ) ΣMi −ui”1
;^ 1t^ vs”= (1/L:M i)DMi −v 1
6pA ＾ The interpolated color system L s”, u s”, v s” is Y.

It is associated with the values of the M, C coordinate system.

Mi is the volume of a rectangular parallelepiped that includes the diagonal vertices and the interpolation point S, and in the case of FIG. 11, εMi=323 1:^. A specific example of interpolation will be explained in the color segmented image estimation device described later.

In this invention, when the target value T' exists outside the color reproduction range of the output color system, the corresponding alternative target value T is
′ is proposed. That is, when it exists outside the solid as shown in FIG. 14, it is estimated by the following process. To simplify the explanation, the Y, M, C coordinate system is 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, move the color in the achromatic direction without changing its hue, and use the color at the point where straight line 1 in the achromatic direction intersects the boundary of the color reproduction range as its target value T0. It is something to do.

In this case as well, the target value T'' is considered to be on the line connecting the lattice points Q1 and Q2 in FIG. (
(Fig. 14) is estimated by dividing and converging.

In addition to the above-mentioned algorithm, the following algorithm is added to the algorithm for this estimation operation.

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

In that case, as shown in Fig. 15, assume a straight line passing through the target value T' and the achromatic axis (this is one point on the L9 axis),
The straight line (hereinafter referred to as convergence line) 1 and u *, v
The slope θ with respect to the ts plane is expressed as follows.

1=ar+b θ=arc tan(u7”/VT”)Here, a
+b is an arbitrary real number and is different from a and b in FIG.

When setting not to change the brightness in addition to the hue, I=LT''.

Next, the cylindrical coordinates Ce of the sample points on the outer surface
, r, l) = (hue, saturation, brightness) and store it in memory.

Then, each sample point (
Among 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 (oi, ri.

1i).

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

θ≦θi≦0+180° (i=1~4)O-90'≦
O1≦θ+90' (i=1~4)e-1800:i
i; O:≦e (i=1-4) a r + + b
l+≧0(i=1~4)ar++b−It≦0(i
= 1 to 4) When these conditions are satisfied, there is a high possibility that the convergence M1 passes through the set minimum quadrilateral.

Incidentally, although there can be an infinite number of such conditional expressions, the above-mentioned conditional expression is an example that can be performed by a simple calculation.

Next, this quadrilateral is calculated by weighted average from its vertices,
Find the midpoint indicated by the circle in Figure 16 and divide the outer surface into four parts.

The above-mentioned conditional expressions are referred to again for these four surfaces, and the same operation is repeated seven times thereafter. Then, the average value of the values of the Y, M, and C coordinate systems corresponding to this seventh vertex is used as the substitute value T'- for the target value T.

Next, an example of a color-separated image estimating device (color masking device) embodying the above-described color-separated image correction method according to the present invention will be described in detail with reference to FIG. 17 and subsequent figures.

In this example, the target value calculated as described above,
In other words, 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 color correction data of each grid point associated with the basic color coordinate system determined by B, G, and R (the same coordinate system as in Fig. 11) is stored, and the color correction data of the grid points other than the grid points is stored. Data are calculated by interpolation.

When the number of input gradations or output gradations is small, all the color correction data can be stored in memory instead of the color correction data discontinuously like this.

Interpolation processing of corrected color data will be explained with reference to FIG. 17.

In this example, eight color correction data (corresponding to C, M, Y A rectangular parallelepiped spatial region (2) formed by known calculated color correction data P1 to P8) is defined. Both of the spatial regions W and ■ have Pl as a reference point. And for each color, 0.32, 64, 96, 128, 160°192.22
Assume that the color combinations at each point of 4.255 have color correction values as described above. At this time, input image data R
, G, and B each have a value of (100, 130, 150), interpolation is performed using the color correction data of the vertices (lattice points) of the spatial area surrounded by the eight points shown below.

Here, Pi (i Mi 1 to 8) on the left side indicates the coordinate value of each vertex of the spatial area V, and the right side indicates the color correction data C of that tosa.
i, Mi, Yi are shown.

Pl: (96,128,128)=(CI, Ml, Yl)P
2: (128, 128, 128) = (C2, M2.Y2)
P3: (96,160,128)= (C3,M3.Y3)P
4: (128, 160, 128) = (C4, M4.Y4)
P5: (96,128,160>= (C5,M5.Y5)P
(1 (128,128,160)= (C6,M6.Y6
)Pl: (96,160,160)= (C7,M?,Y7)
P8: (128, 160, 160) = (C8, M8.Y8
) Therefore, the relationship between the spatial region V having each of these vertices Pi and the spatial region W formed by the input image data is as shown in FIG.

The weighting coefficient for each vertex Pi of the spatial region V is calculated as follows.

As a method of calculating the weighting coefficient, the above-mentioned L6゜u*,
The same calculation formula as in the v* color system can be used.

This is to use the volume of a rectangular parallelepiped spatial region W created by the interpolation point S and the vertex opposite to the point of the correction value to be obtained as the weighting coefficient at the point of the correction value to be obtained.

Therefore, the weighting coefficient of point P8 is determined by using the coordinates of Pl and S, from (100, 130, 150) - (96, 128, 128) = (4, 2, 22), The volume of the rectangular parallelepiped spatial region created by is 4X2X22=176, which becomes the point P8% weighting coefficient.

Similarly, weighting coefficients for the remaining points P1 to P7 are calculated.

P1=8400 P2=1200P3=560
P4= 80P5=18480 P6=
2640P7=1232P8=17 The sum of these weighting coefficients is the same as the volume of the cubic spatial region (2), and in this example, it is 32768 (assumed to be a).

Therefore, the correction values Cs, Ms, Ys at point S are C5=1/a (PIC1+P2C2+P3C3+P4
C4+P5C5+P8CQ+P7C7+P8C8) Ms
=1/a (PIM1+P2M2+P3M3+P4M4
+P5M5+P(5M6+PlM?+P8M8)Y s
=1/a (PIYl+P2Y2+ P3Y3+P
4Y4+P5Y5+ P6Y6+ P7Y7+ P8Y
8). In other words, the correction values of a certain point S to be found and the eight points surrounding it are Ci, Mi, Yi (this is the interpolated value Ls'' of the color system, uSZ vs''L) and the corresponding Y,
M, C coordinate system values), and each weighting coefficient is Ai
Then, C5=(1/EΔi) I:A1C1 ・*I i:1 M5= (1/$:Ai)DAiMi 1=I i*I Ys= (1/4Ai)DAiYi 1*I i=1 It can be expressed as

The above-mentioned color correction data is just an example.

In reality, the number of color correction data is set to a power of 2, taking into account the capacity of the ROM, etc. Therefore, when using a 256-bit ROM, it is possible to have 32 points of color correction data for each color (323=32768 points for all three colors).

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

As is clear from the above equation, this color masking device 10 includes a color correction information storage means (color correction data storage means) 20 that stores a plurality of color correction data, and an information storage means (color correction data storage means) for weighting.
24; a multiplication/accumulation means 30 for multiplying the referenced color correction data and the weighting coefficient and accumulating the values; and a processing means consisting of a division means. Of these, the division means can be omitted depending on the configuration.

The color correction data storage means 20 divides the color space formed by the three-color separation image information that can be inputted for color correction into a plurality of spatial regions, and performs color correction on the combination of three-color separation image information located at the apex thereof. information is stored.

The weighting coefficient storage means 24 can output information on weighting of a plurality of color correction data that can be selected from the color correction information storage means based on the input three-color separation image information.

The processing means processes a plurality of pieces 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 coefficients, 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 device that attempts to obtain three color correction data C, M, and Y at the same time, and FIG.
This is a case where the present invention is applied to a so-called sequential type color masking device that outputs M and Y sequentially in, for example, these orders.

Next, the configuration of each part of the simultaneous color masking device 10 shown in FIG. 18 will be explained.

20 is a color correction data storage means, in this example, each color C, M
, Y are stored in the respective LUTs 21-23. 24 is a weighting coefficient storage means, which is also L.
It is configured as tJT.

Address signals for reading are supplied to the color correction data storage means 20 and the weighting coefficient storage means 24, respectively. Therefore, the input image data B, G, and R are once supplied to the address signal forming means 40, and an address No. 48 corresponding to the input level is output.

The address signal output means is also composed of LUTs 41 to 43, respectively. A bipolar ROM is suitable as the LUT. These LUTs 41 to 4; 3 are roughly supplied with one bit of a signal from the controller 50, the details of which will be described later.

The color correction data and data indicating weighting coefficients (hereinafter simply referred to as weighting coefficients) referenced by the address signal corresponding to the input level of the input image data are sequentially supplied to the multiplication/accumulation means 30 a total of eight times.

As described above, the multiplication/accumulation means 30 is for sequentially executing AiKi (Ki is a general term for C, M, and Y) and calculating the sum thereof, and in this example, the multipliers 34 to
36 and accumulators 37 to 39.

Therefore, each multiplier 34-36 has 512 bits of RO
M is used, and these are supplied with the corresponding color correction data (8 bits) and the weight coefficient 'CI A
1 multiplication processing is executed, and the multiplication outputs of the top eight pits are supplied to subsequent stage accumulators (ΔLU) 37 to 39, and the multiplication outputs are sequentially subjected to addition processing.

The accumulators 37 to 39 can perform calculations with 16-bit precision, but
The top eight pits are used as the cumulative output (sum-of-products output). By this, the cumulative output is changed to the weighting coefficient Ai
You will get the same output as dividing by . In other words, by doing this, the divider can be omitted.

The cumulative outputs of the top eight pits are latched by latch circuits 45 to 47, respectively. Latch pulse is controller 50
is generated.

The configuration of each part will be explained in more detail.

The color correction data storage means 20 stores each color C,
LU that stores accurate color correction data corresponding to M and Y
T21-23 are used.

As LUT21 to 23, RO with bit capacity is set to 256.
When M is used, only 32 points are extracted from the minimum level to the maximum level of the input image data. This gives 32 points per color (so for 3 colors, 323=
One color correction item (32,768 points) can be stored.

Therefore, when the input level is 256 gradations, 32
For example, the distribution of points is "8" starting from 0 as shown below.
Divide into 0.8.16. ...Φ240,248, total 3
Divide it evenly so that there are 2 pieces, and the 33rd point is 249.
Points above 255 points will not be used. Or 249~
The point 255 is treated as 248.

The color correction data at each distribution point is accurately calculated, and the calculated color correction data is applied to each LUT.
21 to 23.

It should be noted that setting the distribution points to 32 points in this way has the advantage that the storage means 20 can be constructed at low cost since a general-purpose ROM with 8-pit output can be used.

The weighting coefficient Ai at each distribution point is stored in the LUT 24 for weighting coefficient storage means. Now, when allocating 8 pits as described above, 8 weighting coefficients Ai
The total is 8X8X8=512, but as mentioned above, a commercially available general-purpose I
If you try to use C, the weighting coefficient (
512) increases the number of elements, so in this example, an approximate value compressed to approximately 1/2 of the theoretical value can be used as the actual value of the weighting coefficient.

In the example shown below, the sum of the eight weighting coefficients is always set to 256, and the maximum weighting coefficient of each is 256.
5.

In such a case, for example in FIG. 17, if S is at the same position as Pl, each weighting coefficient of P1 to P8 is ()
Pi, P2. P3.
P4. P5. P6. P7. P8255, O,
0,0,0,O,0,1 (512,O,0,0,0,0,O,O), and the total sum of the weighting coefficients is 256.

Also, when S is located between Pl and P3 and is 3 from Pl (and therefore 5 from P3), P
Each weighting coefficient of 1 to P8 is as follows.

Pl, P2. P3. P4. P5. P6. P
7. P8160, 0. 96. 0.0. O,
0, 1 (320, 0, 192, 0, 0, O, O, O), and each weighting coefficient is appropriately selected so that the total sum of the weighting coefficients in this case is also 256.

Similarly, S is separated by 3 from the plane of P1 to P4, and Pi
, P3. P5. 1 away from the plane of P7, and Pi,
P2. P5. If it is 5 away from the plane of P6,
The weighting coefficients P1 to P8 are as follows.

Pl, P2. P3. P4. P5. P6. P
7. P2S5, 7. 88. 12. 32. 4
．． 53. 7 (105, 15, 175, 25, 63,
9, 105, 15), and each weighting coefficient is appropriately selected so that the sum of the weighting coefficients in this case also becomes 256.

The above-mentioned 1-bit allocation signal is a control signal for specifying the color correction data before and after the point S.

That is, for convenience of explanation, the relationship between 32 allocation points (lattice points) and the corresponding address signals is set as shown in FIG. 19.

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

Therefore, the allocation is an address signal (12) such that when the signal is O, the smaller color correction data (96) is referred to.
is output, and the allocation is address 1 such that when the signal is 1, the larger color correction data (104) is referred to.
It is controlled so that No. 8 (13) is output.

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

The distributed signals can also be supplied to the weighting coefficient storage means 24.

By the way, when using a recording medium such as photographic paper,
Although there are differences in sensitivity depending on each lot, if such sensitivity differences are taken into consideration, it is necessary to provide color correction data that can correct a plurality of sensitivity differences according to each lot. However, it is practically impossible and impractical to prepare color correction data storage means 20 corresponding to sensitivity differences in this way.

If the configuration uses the color correction data storage means 20 in common, it can be realized without much difficulty.

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

The image data of the corrector is calculated from the color correction data from the color correction data storage means 20 and the weighting coefficient at that time. The corrected image data is sent to LUT61 for sensitivity correction.
-63, and corrections are made in accordance with the sensitivity of the photographic paper used.

Here, a plurality of types of sensitivity correction values corresponding to differences 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 used.

Furthermore, the input/output characteristics of the LLIT for sensitivity correction take into consideration human visual characteristics. If a sensitivity correction curve of input/output characteristics as shown in FIG. 21 is used, the occurrence of false contours due to quantization errors can be minimized.

By the way, although the above example does not have a configuration that makes full use of 256 gradations, for example, if the following idea is followed, it is possible to realize a color masking device that makes full use of 256 gradations. (See Figure 24).

To do this, first, lattice points are distributed using a mixture of 8-bit intervals and 9-pit intervals. By using a mixed type, identification signals with an 8-bit interval and a 9-bit interval are prepared. Therefore, the relationship between the output of the address signal forming means 40, the grid points, and the identification signal is set as shown in FIG. 22.

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.

The allocation is the signal 01 Address signal to 24 63 Address signal to 20 2627 Identification signal 11 Here, the value of the address signal to the weighting coefficient storage means 24 is the one closest to the input 216 when the signal is O. The difference between the smallest grid point 210 (=6) is selected, and when the signal is 1, the difference between the input 216 and the next grid point 219 (=6) is selected.
=3) is selected.

Identification signal 1 represents a lattice point with a 9-bit interval, and 0 represents a lattice point with an 8-bit interval.The identification signal is necessary for the following reasons.

In other words, if the spacing of the grid points is different, the spatial area created by the grid points of the three colors will not be a cube but a rectangular parallelepiped, and its volumes will be: 512 (=8X8X8), 576 (=8X8X
9) 648 (=8x9x9), 729 (=9x
9x9) can be done in 4 ways. Therefore, an identification signal is required to determine whether one side is 8 bits or 9 bits.

Further, in the weighting coefficient storage means 24, the respective weighting coefficients are set in accordance with this identification signal so that the total sum thereof becomes 256.

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

Therefore, from the weighting coefficients and color correction data as shown,
Final color correction data is obtained according to the above-mentioned calculation formula.

If the bit interval of the lattice points is selected appropriately in this way, 25
Six gradations can be fully used. 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 device 1 configured in a sequential manner.
This is a case in which the present invention, particularly a configuration that fully uses 256 gradations, is applied to FIG. 0, and parts corresponding to those in FIG.

In this example, the maximum distance between grid points is 9 pits, so
As an address signal for referring to the weighting coefficient corresponding to this distance, 4-bit data is sent to the address signal forming means (BRI LO).
T) 40 and is supplied to the weighting coefficient storage means 24 side. The address No. 18 forming means 40 further outputs identification signals (1 bit configuration) at 8-bit intervals and 9-bit intervals,
This is supplied to the weighting coefficient storage means 24.

LUTs 21 to 23 for color correction data include the @
The control signals σ, Y and Y for sequentially selecting chips are supplied to the m# child σT, and after the color correction data is sequentially read out from each of LUTs 21 to 23 in order, for example, the multiplication and accumulation is performed. Means 30 is supplied.

Also in the multiplication/accumulation means 30, correction value calculation for each color is sequentially processed.

As shown in the figure, the multiplication accumulator 30 uses a multiplication accumulator composed of a single chip, and outputs a sum of products (accumulation output).
The upper 8 bits of data are sequentially output for each color.

The controller 50 includes a 9-ary counter 51 and a latch circuit 52 for adjusting output timing. A reference clock to the counter 51 is commonly supplied to the clock input terminals Xck and Yak of the multiplication accumulator 30,
At this clock timing, the color correction data Ki and weighting coefficient Ai input to the X and Y terminals are processed. Then, a clock that is counted down to 1/9 of the reference clock is supplied to the Zck terminal so that the final color correction data is output from the output terminal Z0tlT at the next timing after the eight product-sum outputs are obtained. I can do it.

Note that 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 previous product-sum output) is executed. The O-level control pulse is generated every time the ninth reference clock is obtained, thereby resetting the product-sum output and preparing for the next color correction calculation process.

Therefore, during this reset, all O
' of this storage means 24 so that the weighting coefficient of '
A reset signal is supplied to the II terminal.

As a result, the data of Yin becomes O due to the pull-down resistor Rp, and a reset process of X-Y (=O) is executed.

The embodiment described above can also be modified as follows.

First, although the final color correction data is calculated from the color correction data of eight grid points in the above description, it may be interpolated from the color correction data of two diagonal vertices. Such an interpolation method is particularly suitable when using correction data for a larger number of points than those described above as color correction data.

Second, although the color correction data is stored in the LUT in the ROM configuration in the above, RAM is used as a storage means for this color correction data, and another memory (ROM, disk memory, etc.) is prepared for storing the color correction data. Then, when necessary, the color correction data is read from this separate memory and transferred to RAM.
It can also be written and used.

According to this configuration, since the 5-RAM can be used as the RAM, it is possible to speed up the calculation processing time.

In this configuration, which uses a separate memory and downloads it when necessary, this separate memory stores color inversion data, data for selecting a certain output color, data whose color tone changes depending on the type of illumination light, and color data. Data for special effects such as emphasis data can be prepared. You can create special effects relatively easily by downloading and using these as many times as you need.

Thirdly, when the color masking device is applied to printing, it is only necessary to separately prepare an LUT storing black (stain) data in the color correction data storage means 20. In this case, it is better to configure it as a sequential color masking device because the configuration can be simplified.

Fourthly, instead of using the volume of the rectangular parallelepiped as the weighting coefficient, the weighting coefficient may be calculated as the reciprocal of the distance from the point Pi (or its nth power).

Fifth, color correction data storage means 20. Multiplication accumulation means 30
By connecting a latch circuit between each stage, processing between each stage can be separated from each other, thereby enabling high-speed arithmetic processing.

Sixth, the transformation of color space coordinates is CB, G, R), (L”
, a", b"), (X, Y, Z), etc., it is easily understood.

The color T' outside the color reproduction range of the output system does not necessarily need to be compressed to the color T0 at the boundary of the color reproduction range of the output system, and can be replaced with a color slightly inside the boundary.

In this case, using the color T9 of the boundary surface, calculate the inner color (1-#, uI2°vo) by an appropriate amount based on this point, and use this as the target value for Y, M.

What is necessary is to make it correspond to the C coordinate system.

This is shown in FIG. 25. In this case, the color 'I' 1- on the boundary surface of the color reproduction range of the input system is the color T1° on the boundary surface of the color reproduction range of the output system. , and the inner colors outside the output system's color reproduction range T2=, T3−
are respectively replaced with colors within the color reproduction range of the output system.

In addition, in accordance with this, the colors near the boundaries within the color reproduction of the output system are also roughly replaced inward (in the direction of achromatic colors).

At this time, T2° and T3v' are determined based on the color of the boundary surface, so the color of the boundary surface (L `` Hu '' HV
') - It is necessary to grow a large tree.

As an example of this calculation formula, various calculation formulas can be set. For example, as shown in FIG. , dT
3′.

dTl", dT2°, and dT3°, d T1"= d Tl"-α (d Tl'-d T
i) Here, choose i = 2 + 3 α = positive number.

An appropriate α is determined so that dT1' does not become negative. This is because if dTlo becomes negative, the hue will be reversed.

In this way, all colors outside the color reproduction range of the output system are not transferred to the boundary surface, so that color changes are smoother and more natural color correction data can be formed.

[Effects of the Invention] As explained above, in the color separation image correction method according to the present invention, when the color reproduction range of the output system is narrower than the color reproduction range of the input system, the color reproduction range of the output system is When color separation image information that exceeds the input color is input, the values of the output system corresponding to this are compressed in the direction of the achromatic color of the output color system,
The values obtained by compression are used by modifying the values of the output color system.

According to this, since the alternative target value is calculated by changing only the saturation and/or the brightness without changing the hue, more natural alternative color correction data can be obtained. Therefore, even in such a case, since the hue is not changed, natural colors will be reproduced even though the saturation and brightness have been changed.

Of course, in the present invention, since the color correction data is obtained from the measured color data, the correction values are very accurate, and color reproduction can be performed with high precision.

For this reason, the present invention is extremely suitable for application to recording color image information on photographic paper or printing.

[Brief explanation of drawings]

Figure 1 is an explanatory diagram of the Y, M, C coordinate system, Figure 2 is L'', u
”, v' color system. Figure 3 is a further simplified version of the coordinate system in Figure 1, Y, M coordinate system. Figure 4 is a color system showing the brightness and saturation. An explanatory diagram of the system, Figures 5 and 6 are illustrations of interpolation processing, Figures 7 and 8 are diagrams showing an example of a color batch, Figure 9 is an illustration of curve approximation, and Figure 1 is an illustration of the interpolation process.
Figure 0 is an explanatory diagram of the sample point expansion obtained at that time, the first
Figures 1 and 12 are explanatory diagrams of the coordinate system and color system obtained by sample point expansion, Figure 13 is an explanatory diagram of interpolation processing, and Figure 14 is an explanatory diagram when the target value is outside the solid. , 1st
Figure 5 is a cylindrical coordinate diagram showing the color reproduction range in the color system, number 16.
Figure 17 is an explanatory diagram of the convergence operation, Figure 17 is an explanatory diagram of the interpolation process similar to Figure 13, Figure 18 is a system diagram of the main parts showing an example of a color masking device, and Figure 19 is the distribution of grid points. 20 is a schematic system diagram showing another example of the present invention, FIG. 21 is a diagram showing the sensitivity correction curve used at that time, and FIGS. 22 and 23 are distribution diagrams. FIG. 24 is a diagram showing the relationship among signals, color correction data, identification signals, etc., and FIG. 25 is a system diagram similar to FIG. 18 showing still another example of the present invention.
The figure is a diagram for explaining still another example of this invention.
FIG. 6 is a block diagram of a conventional color separation image correction device, and FIG. 27 is a spectral absorption density curve diagram. 10... Color masking device 20... Color correction data storage means 30... Multiplying and accumulating means 40... Address signal forming means 50... Controller ■... Spatial area W... Spatial area S ...Interpolation point patent applicant Konishiroku Photo Industry Co., Ltd. Figure 7 M MC=0
64 128192255 C=0 6
4 128192255 taste C ( 3rd figure 4th figure O thousand waves C4 5th figure 6th figure 8th figure C = 0 85 170255 C = 0 85 170255 17th figure 4th figure ) Fig. 13 U Saturation C'' Fig. 15 Self Fig. 20 Fig. 21 Quantum f(, (, i - Fig. 25

Claims (1)

[Claims] (1) When the color reproduction range of the output system is narrower than the color reproduction range of the input system, and when color separation image information exceeding the color reproduction range of the output system is input, the corresponding value of the output system A method for correcting a color separated image, characterized in that the image is compressed in the non-coloring direction of the output color system, and the values obtained by the compression are corrected and used as the values of the output color system.