JP3445887B2 - Image data conversion method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method for converting data of black and three primary colors into data of three primary colors.

[0002]

2. Description of the Related Art Conventionally, a color digital copying machine has been used to make a copy of a color image.
The color digital copying machine reads a document image and outputs image data, an image processing unit that processes image data output by the scanner unit, and forms an image based on the image data processed by the image processing unit. And an image forming unit. The scanner unit includes, for example, a color CCD (charge coupled device) that outputs three primary color signals of an additive method of red (R), green (G), and blue (B);
A color conversion unit for converting the output signal of the CD into color image data of three primary colors of a subtractive color method of cyan (C), magenta (M) and yellow (Y). The image forming unit forms a color image on paper by using, for example, four color toners of cyan, magenta, yellow, and black by an electrophotographic method.

A color digital copying machine is sometimes used for intentionally processing a document in addition to a purpose of faithfully reproducing a color document image. One mode of manuscript processing is color adjustment. Color adjustment refers to adjusting brightness, hue, or saturation. By color adjustment, an image different in brightness, hue, or color vividness from a document image can be obtained. A typical example of saturation adjustment is complete desaturation. By the achromatic processing, a monochrome reproduced image is obtained from the color original image. This color adjustment process corrects each data of cyan, magenta and yellow. Based on the corrected three primary color data, the fourth color black data is created.

On the other hand, a color digital copying machine may be provided with an external image data input terminal. An external device such as a personal computer can be connected to the external image data input terminal. Therefore, for example, DTP (DeskTop
Publishing) software to input image data, the color digital copying machine can function as a color printer.

[0005] A DTP system in which DTP software and a personal computer are combined is sometimes used to create a composition for creating a color print. The DTP system creates black, cyan, magenta, and yellow data corresponding to a color copy.

[0006]

At the stage of creating a composition,
Normally, print output is repeated many times for confirmation. However, if the black, cyan, magenta, and yellow data are input to the external image data input terminal of the color digital copying machine to check the layout of the composition, a color image is naturally printed. become.

However, in many cases, color output is not always desired at the stage of creating a composition. That is, since color output is costly, monochrome output is rather desired. It is considered that a monochrome output can be realized by applying the above-described color adjustment processing to achromatic an image. However, as described above, the color adjustment processing is performed before the generation of black data. That is, color adjustment is performed based on the three primary color data of cyan, magenta, and yellow before the black generation processing. For this reason, the black data and the three primary color data output from the DTP system cannot be subjected to the achromatic processing.

Therefore, if the primary three primary color data can be restored based on the black data and the three primary color data, it is considered that a monochrome output can be made using the color adjustment processing circuit provided in the color digital copying machine. But,
The method of generating black data is often regarded as know-how,
In addition, since the method differs for each DTP software, and the method cannot be known from the print output result,
There is no known technique for reproducing primary three primary color data from black data and three primary color data.

It is an object of the present invention to solve the above-mentioned technical problems and to provide a method for converting black data and three primary color data into three primary color data.

[0010]

According to a first aspect of the present invention, there is provided an image processing apparatus for converting black data and three primary color data representing a color image into predetermined black data by predicting black data generation processing. An image data conversion method for creating three primary color data before generating black data by substituting into a conversion formula ,
If the predetermined conversion formula is black data K representing a color image,
And three primary color data C, M and Y, and three primary color data
Data MAX (CM) of data C, M and Y
Y), the three primary color data C _T , M before black data generation
(F2) for calculating _T and Y _T respectively
An image data conversion method characterized by the formulas (1), (F22) and (F23) . C _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 − {MAX (CMY) −C} ... (F21) M _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 − {MAX (CMY) −M} ・ ・ ・ ・ ・ (F22) Y _T = [K ² + {MAX (CMY)｝ ² ] ^{1/ 2-} {MAX (CMY) -Y} ..... (F23)

According to this method, by using a predetermined et transform equation to predict the black data generation processing, it is possible to create a black data generation before the three primary data.

[0012]

[0013]

[0014] In addition, in particular to apply the above conversion formula
This can compensate for the lack of density when the value of the black data is small.

The second aspect of the present invention represents a color image.
Black data and three primary color data are scheduled for black data generation processing.
Measured and substituted into a predetermined conversion formula, the black data
An image data conversion method that creates three primary color data before generation
In this case, the predetermined conversion formula is such that the black data K representing the color image and the three primary color data C, M, and Y, and the maximum data MAX among the three primary color data C, M, and Y
Based on (CMY), three primary color data C before black data generation
(F) for calculating _T , M _T and Y _T respectively.
31), especially the (F32) and (F33) Shikidea Rukoto
This is a featured image data conversion method .

C _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 / (2 ^1/2 ) − {MAX (CMY) −C} (F31) M _T = [K ^{2 + {MAX (CMY)}} 2] 1/2 / (2 1/2) - {MAX (CMY) -M} ····· (F32) Y T = [K 2 + {MAX (CMY)} ² ] ^1/2 / (2 ^1/2 ) − {MAX (CMY) −Y} (F33) When this conversion formula is applied, the converted three primary color data C _T ,
M _T and Y _T do not exceed the upper limit that these data can take. That is, three primary color data C _T after conversion, M _T and Y _T can be prevented from saturation.

[0017]

Embodiments of the present invention will be described below in detail with reference to the accompanying drawings. FIG. 1 is a simplified sectional view showing the internal configuration of a digital color copying machine to which an embodiment of the present invention is applied. The digital color copying machine 200 includes a scanner unit 2 for optically reading a document image and an image processing unit 4 for processing an image read by the scanner unit 2 in a copying machine body 1.
And an output unit 3 for reproducing a document image on a recording sheet based on image data created by the image processing unit 4.

The scanner section 2 includes a scanning reading section 21 which can be reciprocated along arrow A below a transparent document table 5 on which a document is placed. The scanning reading unit 21 includes a light source 22 for illuminating the document, a color CCD element 23 for detecting reflected light from the document and performing photoelectric conversion, and a light source 22 for forming an optical image of the document on the CCD element 23. It includes a selfoc lens 24 and a conversion circuit 25 for converting the output of the CCD element 23 into digital color image data. The color CCD element 23 has, for example, red (R), green (G), and blue (B) color filters for each pixel, and outputs an analog image signal of each color component of RGB for each pixel. I do. The conversion circuit 25 is a CCD
The analog image signal output from the element 23 is converted into digital color image data representing the density of each color component of cyan (C), magenta (M), and yellow (Y) and output.

Cyan is a complementary color of red, magenta is a complementary color of green, and yellow is a complementary color of blue. Therefore, if each color component is represented by image data of 256 gradations (8 bits) from 0 to 255, the RGB color component and the CMY color component are expressed by the following equations (1), (2) and There is a relationship expressed by equation (3). C = 255-R (1) M = 255-G (2) Y = 255-B (3) The output unit 3 uses an electrophotographic method to produce cyan. , Magenta,
An image is formed using four color toners of yellow and black (K). More specifically, the output unit 3 includes a drum-shaped photoconductor 31, a laser scanning unit 32 for forming an electrostatic latent image on the surface of the photoconductor 31, and an electrostatic latent image on the surface of the photoconductor 31. Developing device 33 for developing a toner image into a toner image;
And a transfer drum 34 to which the toner image on the first surface is transferred.

At the time of image formation, the photosensitive member 31 is indicated by an arrow B in FIG.
The transfer drum 34 is rotated at a constant speed in the direction of arrow C in FIG. On the other hand, the laser scanning unit 32
The surface of the photoconductor 31 is exposed with a laser beam modulated according to image data provided from the image processing unit 4. The surface of the photoconductor 31 before the exposure is uniformly charged by the main charger 35. Therefore, an electrostatic latent image corresponding to an image to be formed is formed by selective exposure with a laser beam. This electrostatic latent image is transferred to the developing device 33
Then, the toner image is developed by the transfer device 36, and is transferred onto the paper wound around the transfer drum 34 by the operation of the transfer device 36. Reference numerals 61 and 62 denote paper feed cassettes, from which recording paper is supplied toward the transfer drum 34.

The laser scanning section 32 includes cyan, magenta,
The four images corresponding to yellow and black are sequentially written on the photoconductor 31 one by one. Correspondingly, the developing device 3
3 develops each electrostatic latent image with cyan, magenta, yellow, and black toners by a cyan developing unit 33C, a magenta developing unit 33M, a yellow developing unit 33Y, and a black developing unit 33K.

The toner images of the four colors are transferred onto one sheet of paper wound around the transfer drum 34 in a superimposed manner. The paper on which the four color toner images have been transferred is separated from the transfer drum 34 by the functions of the separation discharger 37a and the separation claw 37b, and is guided to the fixing device 39 via the transport belt 38.
The fixing device 39 heats and pressurizes the toner particles on the paper to fix it on the paper, and then discharges the paper out of the copying machine main body 1.

FIG. 2 is a block diagram for describing an electrical configuration of the color digital copying machine 200. The C, M, and Y color image data output from the scanner unit 2 for each pixel is input to the color adjustment circuit 41 in parallel.
The color adjustment circuit 41 includes a CPU (central processing unit) 100
Performs color adjustment for changing the brightness, hue, or saturation of the image based on the instruction from The image data after the color adjustment is input to the black generation circuit 42. Black generation circuit 42
Detects the minimum value of the image data of each of the C, M, and Y color components, and sets the minimum value as a correction coefficient (for example, 0.5 to 1.0).
To generate K component image data. A value obtained by multiplying the minimum value by a correction coefficient is subtracted from the image data of each of the C, M, and Y color components (under color removal processing).

C, M, Y and K from the black generation circuit 42
Are further input to the color correction circuit 43.
The color correction circuit 43 performs a color correction process on the image data of each of the C, M, and Y color components in consideration of the spectral characteristics of the color filters of the CCD element 23 and the spectral characteristics of the C, M, and Y color toners. . C, from the color correction circuit 43
The M, Y and K image data are output to an output color selection circuit 4.
4 is input. The output color selection circuit 44 selects the image data of each color one by one in the order of C, M, Y, and K, outputs the colors in order, and supplies the output data to the output control circuit 48. Output control circuit 48
Generates a laser emission signal to be supplied to the laser scanning unit 32 provided in the output unit 3.

The CPU 100 centrally controls each part of the image processing unit 4 from the color adjustment circuit 41 to the output control circuit 48. The CPU 100 includes a copier main body 1
An operation unit 10 provided on the upper surface of the display unit (see FIG. 1) is connected. The operation unit 10 includes a start key for instructing the start of copying, a numeric keypad for inputting the number of copies, a color adjustment input key for color adjustment (brightness adjustment, hue adjustment, and saturation adjustment). I have.

The color digital copying machine 200 includes:
An external data input terminal unit 201 for inputting color image data from an external device is provided. The external data input terminal 20 1, combining DTP software 302 for example to the personal computer 301 D
From the TP system 300, three primary color data of C, M and Y and K data corresponding to black are input. The input data are inside the data conversion unit 105 of the color digital copying machine 200, the raw three primary colors data C _T before creating K data are converted into Y _T and M _T. The converted data C _T , Y _T and M _T are input to the color adjustment circuit 41. Thus, the color digital copying machine 200 can function as a color printer.

The color adjustment circuit 41 has the function of adjusting the saturation as described above. Therefore, if the color adjustment circuit 41 performs a complete achromatic process, it is possible to input color image data and print out a monochrome image. Next, processing contents in the data conversion unit 105 will be described. Processing for generating black data from three primary color data depends on the DTP software 302,
It is not easy to know the contents of the processing as described in the section of “Problems to be Solved by the Invention”. However, whatever DTP software, cyan,
A minimum under color removal correction coefficient (for example, 50% to 80%) is added to the minimum value MIN of each of the magenta and yellow data.
%) Is black data K, and the process of subtracting the value of the black data from each of the cyan, magenta, and yellow data to create each of the C, M, and Y data is an essential process. It is estimated to be. This is because the component of the minimum value MIN in each of the cyan, magenta, and yellow data corresponds to an achromatic component in a color image. Based on this fact, the data conversion unit 1
In the calculation in 05, any one of the first conversion formula, the second conversion formula, and the third conversion formula described below is applied. <First conversion formula> C, M output by the DTP system 300
It is assumed that each data of Y and Y is data obtained by subtracting K data from original data. Then, the three primary color data C _T , M _T and Y _T before the generation of the black data are represented by the following (F11), (F12) and (F1)
It is obtained by the expression 3).

C _T = C + K (F11) M _T = M + K (F12) Y _T = Y + K (F13) Then, the data conversion unit 105 is input. C, M, Y
(F11), (F1
2) and (F13) performing an operation according to equation to obtain the three primary colors data C _T, M _T and Y _T. (F11), (F1
The processing by the expressions 2) and (F13) has an advantage that the calculation is simple.

Although this conversion formula is very simple, the C, M, Y, and K data created by DTP software whose black generation processing is unknown is input to the data conversion unit 105, and furthermore, the color adjustment circuit 41 It has been confirmed that a good monochrome image can be obtained when the coloring process is performed. <Second conversion equation> The second conversion equation is as follows (F21), (F2
It is as in the expressions 2) and (F23). MAX (CM
Y) represents the maximum data among the three primary color data C, M, and Y.

[0030]   C_T= [K^Two+ {MAX (CMY)}^Two]^1/2− {MAX (CMY) −C}                                         ..... (F21)   M_T= [K^Two+ {MAX (CMY)}^Two]^1/2− {MAX (CMY) −M}                                         ..... (F22)   Y_T= [K^Two+ {MAX (CMY)}^Two]^1/2− {MAX (CMY) −Y}                                         ..... (F23) That is, the data conversion unit 105 receives the input C, M, Y
(F21), (F2)
2) and (F23) are calculated to obtain three primary color data.
TA C_T, M_TAnd Y_TGet. [] In the first term on the right side
+ ｛MAX (CMY)｝ ^TwoIf the concentration is low due to the introduction of
(In the case where K = 0) can be compensated for the insufficient density.
<Third Conversion Equation> The third conversion equation is as follows (F21), (F2
It is as in the expressions 2) and (F23).

[0031]   C_T= [K^Two+ {MAX (CMY)}^Two]^1/2/ (2^1/2) − {MAX (CMY) −C}                                         ..... (F31)   M_T= [K^Two+ {MAX (CMY)}^Two]^1/2/ (2^1/2) − {MAX (CMY) −M}                                         ..... (F32)   Y_T= [K^Two+ {MAX (CMY)}^Two]^1/2/ (2^1/2) − {MAX (CMY) −Y}                                         ..... (F33) That is, the data conversion unit 105 receives the input C, M, Y
(F31), (F3
2) and (F33) are calculated and the three primary color data
TA C_T, M_TAnd Y_TGet. [] In the first term on the right side
+ ｛MAX (CMY)｝ ^TwoIf the concentration is low due to the introduction of
The point where the density shortage (when K = 0) can be compensated.
Is the same as in the case of the second conversion equation. In addition, the right side
Term denominator 2^1/2Gives C_T, M_TOr Y_TIs saturated
Can be prevented.

For example, the processing by the first conversion formula has a problem that the converted data C _T , M _T and Y _T are easily saturated. In other words, when the values removed by the undercolor removal process when creating the C, M, and Y data are small, the addition of the K data may exceed the upper limit value of “255”. Therefore, for relatively small values of C, M, and Y, the converted data C _T , M _T, and Y _T may exceed the upper limit value “255”.

In the above-mentioned second conversion equation, C _T , M _T or Y _T after conversion also tends to be slightly saturated.
On the other hand, (F31), (F32) and (F
33), the converted data C _T , M _T
Or, Y _T does not saturate. This means that, for example, in equation (F31), K = 255, MAX (CM
Y) = 255 and, for the case of MAX (CMY) -C = 0, apparent by calculating the value of C _T. That is, as apparent from the following calculation, in the above case, the C _T = 255. This gives C _T ,
M _T, the upper limit of Y _T is understood to be 255.

C _T = [255 ² +255 ² ] ^1/2 / (2 ^1/2 ) -0 = [2 × 255 ² ] ^1/2 / (2 ^1/2 ) = 255 FIG. 3 mainly shows color adjustment. 4 is a flowchart for explaining the flow of a saturation adjustment process by the operation of a circuit 41. In adjusting the saturation, the operator operates the operation unit 10 to input a saturation adjustment coefficient β (step S1). The saturation adjustment coefficient β is provided to the color adjustment circuit 41 via the CPU 100. The saturation adjustment coefficient β is set to a negative value when it is desired to reproduce colors vividly, and is set to a positive value when performing achromatic processing by reducing the vividness of colors. When the saturation adjustment coefficient β is set to 0.5, complete achromatization is performed.

Next, of the C, M and Y color image data, the largest data MAX and the smallest data M
IN is obtained (step S2). That is, MAX = MAX (CMY) (4) MIN = MIN (CMY) (5) However, as described above, MAX () represents the maximum value of the data in parentheses, and MIN () represents the minimum value of the data in parentheses. Data having an intermediate value is represented by S.

Next, based on the saturation adjustment coefficient β, the maximum image data MAX, the intermediate image data S and the minimum image data MIN, the image data C ″ after the saturation adjustment processing is obtained.
M ″ and Y ″ are calculated (step S3). Thereby, the saturation adjustment processing is completed. In the saturation adjustment in step S3, the following equation (6) is established. That is, image data C, M, and Y before saturation adjustment
And the total sum of the image data C ″, M ″ and Y ″ after the saturation adjustment.

C + M + Y = C ″ + M ″ + Y ″ (6) This makes the lightness equal before and after the saturation adjustment.The saturation adjustment processing will be described more specifically. 7 is a diagram for explaining a process (achromatic processing) for reducing the vividness: the smaller the difference between the maximum image data MAX and the minimum image data MIN, the smaller the saturation, and the colorless ( Therefore, the maximum image data MAX is reduced by Δ, and the minimum image data MIN is reduced.
Is increased by Δ, thereby achieving achromatization. That is, the achromatic data MAX 'and MIN' are obtained by the following equations (7) and (8).

MAX ′ = MAX−Δ (7) MIN ′ = MIN + Δ (8) Δ is the maximum image data MAX and the minimum image data MI
This is the value of the following equation (9) obtained by multiplying the difference from N by the correction coefficient β. Δ = β (MAX−MIN) (9) Δ is not set to a constant value, but to a value proportional to the difference between the maximum image data MAX and the minimum image data MIN, This is to prevent the magnitude relationship between the data and the data before achromatization from being reversed. That is, if the magnitude relationship between the C, M, and Y image data changes, the hue (hue) changes, and an image completely different in color from the original image is reproduced.

FIG. 5 is a diagram for explaining the saturation adjustment for increasing the saturation and making the image colorful. When increasing the saturation, the saturation correction coefficient β takes a negative value. Therefore, the adjusted data M obtained according to the above equation (7)
AX 'takes a value larger than the original data MAX by | Δ |. Similarly, the adjusted data MIN ′ obtained according to the above equation (8) is larger than the original data MIN by | Δ |
Take only small values.

FIG. 6 is a diagram for explaining the adjustment of the intermediate value data S. The intermediate data S is (MAX-
The ratio between (S) and (S-MIN) is the same ratio (MAX'-S ') :( S'-MIN') for the adjusted data.
Is corrected to be equal to That is, in FIG. 6, the following equation (10) should be satisfied. From a: b = a ': b' (a + b): b = (a '+ b'): b '(10) where a = MAX-Sb = S-MIN a' = MAX ' −S ′ b ′ = S′−MIN ′.

Therefore, the adjusted data S 'is given by the following equation (11).

[0042]

(Equation 1)

Further, the above equations (7), (8) and
From the equation (9), the following equation (12) is obtained. S ′ = (1-2β) (S−MIN) + MIN + β (MAX−MIN) (12) By the way, as a result of the above processing, the adjusted value MA is obtained.
X ′ or MIN ′ may exceed the maximum value that the image data can take or fall below the minimum value. For example, if the image data is 8 bits,
A value of 5 can be taken. In this case, in the example of FIG. 7, as a result of increasing the saturation, the adjusted maximum data MAX ′ exceeds 255, and in the example of FIG. 8, the adjusted minimum data MIN ′ is less than 0. .

Therefore, when the adjusted maximum data MAX 'obtained by the equation (7) exceeds 255 (when MAX'> 255), the image data is further corrected as follows. That is, the maximum data MAX 'is expressed by the following (13)
As in the formula, 255 is forcibly set. Then, the minimum data MIN 'is set to a value obtained by subtracting (255-MAX) from MIN as in the following equation (14).

MAX ′ = 255 (13) MIN ′ = MIN− (255−MAX) (14) By substituting these into the equation (11), the following (15) ) Is obtained.

[0046]

(Equation 2)

On the other hand, when the adjusted minimum data MIN 'obtained by the equation (8) is less than 0 (when MIN'<0), the image data is further corrected as follows.
That is, the minimum data MIN 'is forcibly set to 0 as in the following equation (17). Then, the maximum data MAX '
Is expressed as MIN (= MIN) in MAX as in the following equation (16).
−0).

MAX ′ = MAX + MIN (16) MIN ′ = 0 (17) By substituting these into the equation (11), the following equation (18) is obtained.

[0049]

(Equation 3)

Incidentally, in the above equation (18), S = M
If AX is set, the right side is (MAX + MIN). If S = MIN, the right side becomes 0. Therefore, the above equation (18) can also be used for the maximum data MAX 'and the minimum data MIN'. Similarly,
The expressions (12) and (15) can also be applied to the maximum data MAX 'and the minimum data MIN'. Therefore, the maximum data, minimum data, and intermediate data after adjustment are represented again as S ', and the maximum data, minimum data, and intermediate data before adjustment are represented again as S, as follows.

S ′ = (1-2β) (S−MIN) + MIN + β (MAX−MIN) (Equation) However, if S ′ <0 when S = MIN in the equation, The following equation applies.

[0052]

(Equation 4)

When S = MAX in the equation, S ′
If> 255, the following equation is applied.

[0054]

(Equation 5)

In the above formulas, formulas and formulas, MAX: maximum value of CMY MIN: minimum value of CMY β: saturation adjustment coefficient S: input CMY data S ′: CMY data after saturation adjustment processing Just correcting the saturation
The brightness may differ between before and after the adjustment, and therefore, the saturation adjustment intended by the user is not always performed. In particular, with respect to red, an image that is brighter than intended by the user can be obtained when achromatization is performed. Therefore, for example, when an achromatic process is performed on a document image in which a yellow portion and a red portion are mixed according to the above-described process, the yellow portion and the red portion are reproduced with substantially the same brightness. To the human eye, yellow is relatively bright,
Since red appears to be relatively dark, the lightness of red must originally be reproduced lower.

FIGS. 9 and 10 are diagrams for explaining the reason why the above problem occurs. For the red image,
The C, M, and Y image data generally have a magnitude relationship as shown in FIG. To completely achromatize this image,
The color image data may be corrected to an intermediate equal value.
Since the spectral spectrum of the red image is substantially as shown in FIG. 10 (a), the image data representing the densities of C, M and Y is as shown by the solid line in FIG. 10 (b). When all the image data is corrected to an intermediate equal value, the corrected data is as shown by a two-dot chain line in FIG. Therefore, the sum of the image data of C, M, and Y decreases in the area D and increases in the area I. Since the area D is larger than the area I, as a result, the total sum of the C, M, and Y image data decreases. That is, the density decreases and the brightness increases.

In the present embodiment, further adjustment is performed in order to prevent the above-described change in lightness due to the adjustment of saturation. Specifically, the sum of the image data C, M, and Y before the saturation adjustment, the image data C ″ after the saturation adjustment,
The above formulas, formulas, and formulas are corrected so that the sum of M ″ and Y ″ becomes equal. More specifically, the following (19)
The final image data C ″, M ″ and Y ″ after the saturation adjustment are obtained from the expressions (20) and (21). The result of adding the right sides of these expressions is C + Y + M. It will be clear that they will be equal.

[0058]

(Equation 6)

Therefore, the data MAX ″ of the maximum data MAX of C, M, and Y after the saturation adjustment processing, the data S ″ of the intermediate data S after the saturation adjustment processing, and the saturation of the minimum data MIN The data MIN ″ after the adjustment processing is the following (2)
It is given by the equations (2), (23) and (24).

[0060]

(Equation 7)

By substituting the values of the above equations into the above equations (22), (23) and (24), the following equations (25) and (24) are obtained.
Equations (26) and (27) are obtained.

[0062]

(Equation 8)

By adding the left and right sides of the above equations (25), (26) and (27), it can be easily confirmed that MAX "+ S" + MIN "= MAX + S + MIN. That is, the (25)
If the saturation adjustment is performed by converting the image data according to the equations (26) and (27), an image having the same brightness as the original image but different in the saturation can be obtained.

In the above equation, when S = MIN, S '<0
Is obtained, the following equations (28) and (2) are substituted for the equations (22), (23) and (24).
Equation 9) and Equation (30) are obtained.

[0065]

(Equation 9)

When the left side and the right side of the above equations (28), (29) and (30) are added together, it can be easily confirmed that MAX ″ + S ″ + MIN ″ = MAX + S + MIN. Further, when S = MAX and S ′> 255 in the equation, by substituting the equation into the above equations (22), (23) and (24), the following equation (31) is obtained. Equations (32) and (33) are obtained.

[0067]

(Equation 10)

By adding the left side and the right side of the above equations (31), (32) and (33), it is easily confirmed that MAX "+ S" + MIN "= MAX + S + MIN. Step S3 of 3
In the processing in, the input image data C, M, Y
Expression (5), Expression (26), Expression (27), Expression (28), Expression (29), Expression (3)
This is a process of converting the image data C ″, M ″, and Y ″ after the conversion by the conversion formulas (0), (31), (32), and (33).

The above-described saturation adjustment processing can also be applied to the image data C _T , M _T and Y _T output from the data conversion unit 105. Therefore, the saturation adjustment coefficient β (that is, β =
0.5), the DTP system 300
A monochrome image corresponding to the C, M, Y and K data created by the above can be printed out.

Thus, when checking the layout or the like in the middle of the preparation of the color plate, instead of a color image,
A monochrome image can be formed. As a result, cost can be reduced. Although the description of the embodiment of the present invention is as described above, the present invention is not limited to the above embodiment. For example, in the above description of the embodiment, an example in which the color digital copying machine 200 is provided with the data conversion unit 105 has been described. It may be connected to the outside. Further, the same processing as the processing in the data conversion unit 105 may be executed on the personal computer 301. However, in terms of processing speed,
As in the case of the above embodiment, it is preferable to use a data conversion unit having a hardware configuration.

The simplified saturation adjustment process described in the above embodiment is merely an example, and another method of saturation adjustment may be applied. Further, in the above embodiment, an example in which the present invention is applied to a digital color copying machine has been described. However, the present invention is directed to a print output having a configuration for color adjustment, such as a color facsimile apparatus or a color printer. It can be combined with the device.

In addition, various modifications can be made within the scope of the technical matters described in the claims.

[0073]

Effects of the Invention According to the first aspect of the present invention, by using a predetermined et transform equation to predict the black data generation processing, it is possible to create a black data generation before the three primary data. Therefore, if the created three primary color data is processed by, for example, an apparatus having a configuration for achromatic processing, good monochrome image data can be obtained.

Further , the above conversion formula is obtained by the above (F21),
(F22) and (F23)
This makes it possible to compensate for insufficient density when the value of the black data is small. According to the second aspect of the invention, there is an advantage that the insufficient density when the value of the black data is small can be compensated, and that the converted three primary color data does not exceed the upper limit that these data can take. is there. That is, saturation of the converted three primary color data can be reliably prevented.

[Brief description of the drawings]

FIG. 1 is a simplified sectional view showing an internal configuration of a digital color copying machine to which an embodiment of the present invention is applied.

FIG. 2 is a block diagram showing an electrical configuration of the digital color copying machine.

FIG. 3 is a flowchart illustrating a saturation adjustment process.

FIG. 4 is a diagram for explaining a process of lowering the saturation (achromatization process).

FIG. 5 is a diagram for explaining a process for increasing the saturation (a process for making the image vivid).

FIG. 6 is a diagram for describing processing for data having an intermediate value.

FIG. 7 is a diagram for explaining processing when the value of the maximum data after the saturation adjustment exceeds the maximum value that can be taken by image data;

FIG. 8 is a diagram for explaining processing when the value of the minimum data after the saturation adjustment processing is smaller than the minimum value that can be taken by image data;

FIG. 9 is a diagram illustrating a change in lightness when a red image is achromatic.

FIG. 10 is a diagram illustrating spectral characteristics of a red image (a) and corresponding image data before and after saturation adjustment (b).

[Explanation of symbols]

3 Output section 4 Image processing unit 41 Color adjustment circuit 42 black generation circuit 100 CPU 105 Data conversion unit 200 color digital copier 300 DTP system 301 Personal computer 302 DTP software

Claims (2)

(57) [Claims] 1. A method according to claim 1, further comprising the steps of:
Data at a predetermined location in anticipation of the black data generation process.
Substituting the three primary color data before black data generation
An image data conversion method to be created, wherein the predetermined conversion formula is black data K and three primary color data C, M, and Y representing a color image, and maximum data MAX (CM) among the three primary color data C, M, and Y.
Y), the three primary color data C _T , M before black data generation
(F2) for calculating _T and Y _T respectively
1), (F22) and (F 23) images data conversion way to being a formula. C _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 − {MAX (CMY) −C} (F21) M _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 − {MAX (CMY) −M} (F22) Y _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 − {MAX (CMY) −Y}・ ・ (F23) 2. Black data and three primary color data representing a color image.
Data at a predetermined location in anticipation of the black data generation process.
Substituting the three primary color data before black data generation
An image data conversion method to be created, wherein the predetermined conversion formula is black data K and three primary color data C, M, and Y representing a color image, and maximum data MAX (CM) among the three primary color data C, M, and Y.
Y), the three primary color data C _T , M before black data generation
(F3) for calculating _T and Y _T respectively
1), (F32) and (F33) images data conversion way to being a formula. C _T = [K ² + {MAX (CMY)｝ ² ] ^1/2 / (2 ^1/2 ) − {MAX (CMY) −C} (F31) M _T = [K ² + ｛ ^{MAX (CMY)} 2] 1/2} / (2 1/2) - {MAX (CMY) -M} ····· (F32) Y T = [K 2 + {MAX (CMY)} 2] 1 ^{/ 2} // (2 ^1/2 )-{MAX (CMY) -Y} (F33)