JPS63162248A - Color separation image correction method and its apparatus - Google Patents

Abstract

PURPOSE:To get rid of skips of a correction value, to minimize an errot of the correction value, and to make the reproducibility of color good, by obtaining color separation image information corrected by selected pieces of color correction information. CONSTITUTION:Interpolation treatment is executed on the basis of color correction information (image data for color correction) expressed by the coordinate of each vertex of a space area of a regular hexahedron or a rectangular parallelopiped state containing its input image data. When, for convenience, expressed by one input-output system, an image data to be corrected in interpolated by before and after two points of preliminarily calculated color correction data (O mark) containing the image data (X mark) to be corrected. This eliminate the problem that the color correction data is corrected being dislocated from the points of preliminarily calculated color correction data, and any correction error and any skip in correction can be certainly avoided.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a color separation image correction method and apparatus suitable for use in color correction (color proofing) of video printers, digital color copies, etc.

[Background of the Invention] In video printers, digital color copiers, etc., 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.

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

There are two types of color masking methods used in such a color masking device 10: a linear masking method and a nonlinear masking method.

In the case of linear masking, the calculation formula shown in equation (1) is used, and in the case of nonlinear masking, the calculation equation shown in equation (2) is used.

Here, A and D are coefficient matrices.

In the case of linear operation, 3X3 as shown in equation (1)
This is a matrix operation, and the means to achieve this is as follows.
There are two possible cases: actually using a multiplier to perform calculations each time, or creating a table of the calculation results and referring to the table (look-up table (LUT)) to obtain color correction data.

The nonlinear operation of equation (2) may also use an arithmetic unit, or may use the above-mentioned LUT.

[Problem to be Solved by the Invention 1] By the way, since the correction value calculated in the above-mentioned linear calculation process is an approximate value by polynomial approximation, the obtained color correction data is also inaccurate. In particular, when calculating coefficient A, key color matching is performed, so even if it matches the key color relatively well, other colors, that is, colors that are outside the key color, may have different hue, saturation, brightness, etc. Put it away.

In particular, when converting image information from a TV monitor into a hard copy, the color reproduction system is different, in that the TV monitor is additive, while the hard copy on photographic paper is subtractive, and the color reproduction range is different. Due to these differences, color reproduction errors were large even when key color matching was performed.

On the other hand, when creating color correction data by performing non-linear processing, hue, saturation,
Since deviations in brightness and the like are relatively small, color reproducibility is good.

However, color correction using nonlinear processing has the disadvantage that the hardware required to implement it is extremely complex. On the other hand, when creating a table, the required memory capacity becomes enormous.

For example, when C, M, and Y image data are expressed as 8-bit data, the combination of each image data is 2 bits.
8.28.2B=224, and in order to obtain three color correction data, a huge memory capacity of 224×3=50.3 Mbytes is required.

For example, Japanese Patent Application Laid-open No. 61 (1983)
One such means is disclosed in Japanese Patent No.-60068 and the like.

An example of this means is shown in FIG.

The input image data is divided into upper bits and lower bits,
Each is supplied to the corresponding LUTI1, 12 as reference address data. The upper LUT II stores a plurality of pieces of color correction data calculated in advance at appropriate intervals as color correction data for the input image data of the upper bits.

On the other hand, the lower LUT 12 stores color correction data corresponding to a single correction curve.

Then, the image data referenced by the input image data of the upper bits and the color correction data referenced by the input image data of the lower bits are added in the adder 13, thereby obtaining new color correction data. .

In this way, by dividing the data into upper bits and lower bits and performing arithmetic processing, the required memory capacity can be significantly reduced compared to the conventional method.

However, this method has the following drawbacks.

In other words, when the output image data for the input image data is as shown by the curve L1 in FIG. As the value increases, the error in the output value tends to increase.

As color correction data, as shown by curve L3 in Figure B,
When using non-linear approximation color correction data (marked with O) that has the same change as the input image data, the characteristic straight line (or curve) of the color correction data stored in the lower LUT 12 has a single slope (shape). Therefore, the data (output value) after color correction is as shown by curve L4.

As a result, the color correction data skips where the slope of the input image data is small or large, resulting in a fatal drawback that continuous color correction cannot be performed.

Therefore, this invention was developed to solve these conventional problems, and it eliminates color correction errors and skipped color corrections, and also significantly reduces the capacity of the data table of color correction data. This paper proposes a color separation image correction method and device suitable for application to a color masking device and the like that can reduce the number of images.

[Technical Means for Solving the Problems] In order to solve the above-mentioned problems, in the color separation image correction method according to the present invention, the colors formed by the three-color separation image information that can be input for color correction are The space is divided into a plurality of spatial regions, and from the color correction information table having color correction information for the combination of color separation image information located at the apex of the space, the location at the apex of the spatial region including the combination point of the input color separation image information is determined. The present invention is characterized in that a plurality of pieces of color correction information are selected and color separation image information corrected by the plurality of selected pieces of color correction information is obtained.

Further, the color separation image correction device according to the present invention divides a color space formed by three color separation image information that can be input for color correction into a plurality of spatial regions, and three
A color correction information storage means having color correction information for a combination of color separation image information, and outputting weighting information for a plurality of color correction data selected from the color correction information storage means based on input three-color separation image information. and processing means for outputting color separation image information corrected based on the plurality of color correction information and weighting information selected from the color correction information storage means based on the input color separation image information. It is characterized by the fact that

[Operation] The color separation image information (hereinafter referred to as color data) to be corrected is
Image data (hereinafter referred to as input image data) of at least two vertices of a spatial region including input color separation image information (hereinafter referred to as input image data)
(two color correction data stored in a data table).

Specifically, interpolation processing is performed based on color correction information (image data for color correction) represented by the coordinates of each vertex of a cubic or rectangular parallelepiped spatial region containing the input image data.

For convenience, if it is expressed in a one-person output system, as shown in Figure 1, two images before and after the image data to be corrected (x mark)
This is interpolated using pre-calculated color correction data (0 mark) of the point.

According to this, the color correction data is not corrected to deviate from the point of the color correction data calculated in advance, and correction errors and jumps in correction can be reliably avoided.

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

FIGS. 1 and 2 are diagrams for explaining the case where an example of the color separation image correction method according to the present invention is applied to the above-mentioned color masking method, and FIG. An example of a specific means for realizing this, that is, an example of a color masking device 10 will be shown.

The color masking method according to this embodiment does not have an LUT for all color combinations, but has accurate color correction data for color combinations with determined values that are irregular. If the color is not that color, then from the image data of the surrounding points (color correction data that has already been calculated),
This is an attempt to interpolate using a weighted average.

For convenience, if we explain using the curve of one person's output system,
As shown in FIG. 1, when the curve L1 is a color correction curve for input image data, the 0 marks shown on this line are the discrete color correction data stored in the data table.

If we assume that X is the color correction data for which we are trying to find, then this color correction data
Interpolated by 2. As a result of such interpolation processing, the color correction data X to be obtained is always located on a straight line connecting the color correction data M1 and M2 calculated in advance. As a result, color correction errors can be suppressed to a minimum, and skipping of corrected colors can be eliminated.

A specific method of calculating corrected color data will be described next.

In this example, eight color correction data (C, M, .

A rectangular parallelepiped spatial region (2) formed by known calculated color correction data (P1 to P8) corresponding to Y is determined. spatial region W,
(2) Both use Pl as the reference point.

And for each color, 0.32.64, 96, 128, 160°192.22
4.255 It is assumed that there is a color correction value for the combination of colors at each point. That is, in this case, 8X8X8
=512 spatial regions.

At this time, the input image data R, G, B are respectively (100,
130, 150), it is interpolated using the color correction data of the vertices (lattice points) of the spatial area surrounded by the eight points shown below.

Here, Pi (i=1 to 8) on the left side indicates the coordinate value of each vertex of the spatial area ■, and the right side indicates the color correction data Ci at that time.
, Mi, and Yi.

Pl: (96,128,128)=(C1,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)
P6: (128, 128, 160) = (C6, M6.Y6
)Pl: (96,160,160)= (C7,M7.Y7)
P8: (128, 160, 160) = (C8, M8.Y8
) The relationship between the spatial area (2) having each of these vertices Pi and the spatial area W formed by the input image data is as shown in FIG.

In this invention, weighting coefficients for each vertex Pi of these spatial regions (2) are calculated.

There are several ways to calculate the weighting coefficient, but the simplest method is to calculate the weight at the point of the correction value to be calculated by calculating the volume of the rectangular parallelepiped spatial region created by the point X and the vertex opposite to the point of the correction value to be calculated. This is a coefficient.

Therefore, using the coordinates of Pl and the coordinates of The volume of the rectangular parallelepiped spatial region created by Pl is 4X2X22=176, which becomes the weighting coefficient of point P8.

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 Cx, Mx, Yx at point X are Cx=1/a (PIC1+P2C2+P3C3+P4
C4+P5C5+P6C6+P7C7+P8C8)Mx
-1/a (PIM1+P2M2+P3M3+P4M4
+P5M5+P6M6+P7M7+P8M8)Y x
=1/a (PIY1+ P2Y2+ P3Y3+
P4Y4+P5Y5+ P6Y6+ P7Y7+ P8
Y8). That is, if the correction values of a point X to be determined and the eight points surrounding it are Ci, Mi, and Yi, and the respective weighting coefficients are Ai, then Mx= (1/3Ai), +AiMi +''''1-' It can be expressed as I YX=(1/1≧+A i) genus AiYi.

Note that the above-mentioned color correction data is just an example, and in reality, the number of color correction data may vary depending on the ROM capacity, etc.
Set to a power of 2. Therefore, 256 bits of R
When using OM, each color can have 32 points of color correction data (323=32768 points for all three colors).

In this case, the number of divided space regions is (32-1)3=297
It becomes 91.

There are countless ways to obtain color correction data for grid points.

A simple method is to apply a conventional nonlinear masking method. That is, approximation is performed using a high-order polynomial that minimizes the error, and color correction data at each grid point is calculated using the polynomial. Since the polynomial at this time is unrelated to hardware and is calculated in advance, it does not matter if it contains any complicated terms (for example, reciprocal, n-th power, logarithm, etc.).

The polynomial when using the nonlinear masking method is expressed as a general formula: C=fC (B, G, R) M=fM (B, G, R) Y=fY (B, G, R) However, B, G, R is a grid point.

FIG. 3 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 a weighting information storage means (
24; a multiplication/accumulation means 30 that multiplies the referenced color correction data and the weighting coefficient and accumulates the resulting value; 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 a color space formed by three-color separation image information that can be input 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 of the space. information is stored.

The weighting coefficient storage means 24 outputs weighting information for a plurality of pieces of color correction data 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. 3 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 sequentially outputs Y in this order, for example.

Next, the simultaneous color masking device 1 in FIG.
The configuration of each part of 0 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 a UT.

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 signal 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 43 further include a controller 5.
A signal is supplied for the distribution of bits 0 to 1, 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 mentioned 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.
36 and accumulators 37-39.

Therefore, each multiplier 34 to 36 has a pit RO of 512.
M is used, and the corresponding color correction data (8 bits) and weighting coefficient Ai are supplied to perform the multiplication process of A1K1, and the multiplication output of the top 8 pits is sent to the subsequent accumulator ( ALU) 37 to 39, and the multiplication outputs are sequentially subjected to addition processing.

The accumulators 37 to 39 are operated with an accuracy of 16 pits,
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 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.

256 bit capacity ROM as LUT21~23
When using , 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=3
2768 points) of color correction data can be stored.

Therefore, when the input level is 256 gradations, 32
For example, the distribution of points is "8" starting from O, as shown below.
Divide into 0.8, 16. ...240,248, 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.

Note 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 because a general-purpose ROM with 8-bit 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 bits at a time as described above, 8 weighting coefficients Ai
The total is 8X8X8=512, but as mentioned above, a commercially available general purpose
If you try to use C, the weighting coefficient (
512), the number of elements increases, so in this example, an approximate value compressed to approximately 1/2 of the theoretical value is 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. 2, if X 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,
O, O, O), and the total sum of the weighting coefficients is 256.

Also, when X is between Pl and P3 and is 3 away from Pl (and therefore 5 from P3), then 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 (320,0,292,0,0,O,0,0), and each weighting coefficient is appropriately selected so that the total sum of the weighting coefficients in this case is also 256.

Similarly, if X is 3 away from the plane 21 to P4,
, 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 distribution (number g refers to the color correction data M1 and M2 before and after point X, if explained with reference to FIG.
This is a control signal for specifying.

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.

Now, when the level of the input image data is 100, the address signal (12°13) is outputted from the color correction data storage means 20 to output the previous and subsequent color correction data (96 and 104) including this human power level. need to be formed.

Therefore, when the signal is 0, the address signal (12) is such that when the signal is 0, the smaller color correction data (96) is referred to.
is output, and the distribution is controlled so that when the signal is 1, an address signal (13) is output so that the larger color correction data (104) is referred to.

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 color correction data is selected. Select color correction data (240 in this case).

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

By the way, when using a recording medium such as photographic paper,
Since there are differences in sensitivity depending on each lot, if such sensitivity differences are taken into consideration, it is necessary to have color correction data that can correct the sensitivity difference in f number 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. 5 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 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.

Corrected image data 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 this sensitivity correction LUT take human visual characteristics into consideration. If a sensitivity correction curve of input/output characteristics as shown in FIG. 6 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 9).

To do this, first, grid points are distributed in a mixed form of 8-bit spacing and 9-bit spacing. 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.

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

In other words, if the spacing between 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 (=8x8x9)
648 (=8X, 9X9), 729 (=9X9X9
) 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. 9 shows a color masking device 10 configured in a sequential manner.
This is a case where the present invention, particularly a configuration that fully uses 256 gradations, is applied, and parts corresponding to those in FIG. 3 are denoted by the same reference numerals, and their explanation will be omitted.

In this example, the maximum distance between grid points is 9 bits, so
As an address signal for referring to the weighting coefficient corresponding to this distance, 4-pit data is sent to the address signal forming means (BRI).
T) 40 and is supplied to the weighting coefficient storage means 24 side. From the address signal forming means 40, there are roughly 8-bit intervals and 9 bits.
A pit interval identification signal (1 bit configuration) is output and supplied to the weighting coefficient storage means 24.

The LUTs 21 to 23 for color correction data have their control terminals. For example, LUTs 21 to 23 are supplied with a control signal C to select a chip to lff, and Y to LFF.
After the color correction data is sequentially read out from each in the following order,
It is supplied to the multiplication and accumulation means 30.

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 (cumulative μ 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 has counted down the reference clock to 1/9 is supplied to the Zck terminal so that the final color correction data is output from the output terminal Z OUT at the next timing after the eight product-sum outputs are obtained. be done.

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 10 output) is executed. An O-level control pulse is generated every time the ninth reference clock is obtained, thereby resetting the product-sum output in preparation for the next color correction calculation process.

Therefore, during this reset, all O
This storage means 2407 is configured so that the weighting coefficient of
Reset No. 43 is supplied to the 1' terminal.

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

Next, other modifications of the invention will be explained.

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 that selects a certain output color, data that changes color tone depending on the type of illumination light, and color data. Data for special effects such as data for emphasis 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 in which black (shade) data and black data are stored in the color correction data storage means 2o. In this case, it is better to configure it as a sequential color masking device because the configuration can be simplified.

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

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.

Sixthly, in the above description, the method and device for correcting color separation information according to the present invention are applied to image processing devices such as color blueprints, video printers, and digital color copies.
(Y, M, C), (B, G.

R), (L”+ u”+ v”), (L”, aZ b”
), (X, Y, Z), etc. It is easy to understand that the present invention can be applied to an arithmetic device that converts color space coordinates such as (X, Y, Z).

[Effects of the Invention] As explained above, according to the present invention, the correction value of the point I can do it.

First, in conventional linear approximation, the error in the correction value becomes large, and in non-linear approximation, the correction value jumps, but according to this invention, the correction value is calculated by interpolation. Therefore, there is no jump in correction values, and perfect color reproduction is achieved at the pre-calculated color correction data point (in the example, a 32×32×32 point). Since the calculation process is performed by interpolation in other respects as well, the error in the correction value is small, and the color reproducibility is clearly better than that of the conventional method.

Second, the capacity of the color correction data storage means can be significantly reduced.

Incidentally, conventionally, a capacity of about 50 Mbytes is required, but according to the above-mentioned configuration, (256 and 3 pit colors)/8 bytes = 96 bytes, making it possible to realize a significant gradual reduction in memory capacity.

For this reason, the color separation image correction method according to the present invention can be applied to an image processing apparatus such as a color blueprint, a video printer, a digital color copy, or the above-mentioned (Y
, M, C), (B, G, R), (L*, u*
, v*), (L”, a”, b”), (X.

It is extremely suitable for application to an arithmetic device that converts color space coordinates such as Y, Z).

[Brief explanation of the drawing]

FIG. 1 is a characteristic curve diagram for explaining the present invention, FIG. 2 is an explanatory diagram of the color masking method according to the present invention, FIG. 3 is a system diagram of essential parts showing an example of a color masking device, and FIG.
5 is a diagram showing the distribution relationship of grid points, FIG. 5 is a schematic system diagram showing another example of the present invention, FIG. 6 is a diagram showing the sensitivity correction curve used at that time, and FIGS. Figure 8 is a diagram showing the relationship between distribution signals, color correction data, identification signals, etc., Figure 9 is a system diagram similar to Figure 3 showing still another example of the present invention, and Figure 10 is a color masking device. Explanatory diagram, 11th
The figure is a block diagram of a conventional color masking device, and FIG. 12 is a curve diagram for explaining the same. 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 X ...Color correction data patent applicant Konishi Roku Photo Industry Co., Ltd. Figure 1 Figure 2 Figure 5 Figure 6 Quantum RCA -- Figure 10 Figure 11 Figure 12 Weak A Figure 12 B Iriga

Claims (6)

[Claims] (1) Color correction information that divides the color space formed by three-color separation image information that can be input for color correction into a plurality of spatial regions, and has color correction information for the combination of color separation image information located at the apex of the space. From the table, select a plurality of pieces of color correction information located at the vertices of a spatial region including the combination points of input color separation image information, and obtain color separation image information corrected by the plurality of color correction information selected above. Characteristic color separation image correction method. (2) New color separation image information is calculated using eight pieces of color correction information read from the color correction information table, as set forth in claim 1. Color separation image correction method. (3) A patent characterized in that eight different pieces of color correction information are sequentially read out from the color correction information table, each is multiplied by a weighting coefficient, and subjected to product-sum processing to calculate new color separation image information. A color separation image correction method according to claims 1 and 2. (4) Color correction that divides the color space formed by three-color separation image information that can be input for color correction into a plurality of spatial regions, and has color correction information for the combination of three-color separation image information located at the apex of the space. information storage means; weighting information output means for outputting weighting information for each of the plurality of color correction information selected from the color correction information storage means based on the input three-color separation image information; and the input color separation image information. and processing means for outputting color separation image information corrected based on a plurality of pieces of color correction information and weighting information selected from the color correction information storage means based on the color separation image correction apparatus. . (5) Claim 4, characterized in that eight pieces of color correction information are used as the plurality of color correction information.
Color separation image correction device as described in section. (6) The processing means performs a calculation process of multiplying each of the eight pieces of color correction information sequentially read out from the color correction information storage means by a weighting coefficient and performing product-sum processing to calculate new color-separated image information. A color separation image correction apparatus according to claims 4 and 5, characterized in that the color separation image correction apparatus is configured to perform the following.