JP3767189B2 - Color image processing method and apparatus - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a color image processing method and apparatus for converting a color signal of three colors to obtain a plurality of color image recording signals including black, and in particular, a color image processing method for obtaining an optimum black amount for a predetermined image quality, and Relates to the device.
[0002]
[Prior art]
Conventionally, when a color original image is recorded and reproduced, four-color printing is usually performed. That is, printing is performed through color separation plates for yellow, magenta, cyan, and black printing inks. The four-color printing is performed in this way. When the three-color printing of yellow, magenta, and cyan is performed, only a reproduced image with poor contrast is obtained because the ink does not have an ideal color development characteristic. This is because there is not.
When performing such four-color printing, so-called 100% under color removal may be performed on yellow, magenta, and cyan printing inks. This 100% under color removal is a method in which an image is reproduced with any two colors of yellow, magenta, and cyan and black. According to this method, the color reproduction region in the low brightness part can be widened, and the gray stability in the high brightness part can be maintained high. This method also has the advantage that the consumption of expensive color ink can be reduced and the running cost can be suppressed.
[0003]
There are various advantages in performing the undercolor removal by four-color printing in this way, but it is very difficult to determine the undercolor removal amount and the black amount according to the input image signal. Problems arise. For example, black generally has a higher contrast than other color inks, so that the roughness of the image is relatively conspicuous, and in particular, it is difficult to put in the human skin portion of the image. Also, when performing four-color printing, the recording positions of the four-color printing inks are likely to shift due to vibration of the image forming apparatus and deformation and movement of a recording medium such as paper during printing, and color misregistration is likely to occur. Problems arise. In order to prevent such color misregistration, a so-called rotation screen in which the angles of the nets of the respective colors are different is used. Usually, the occurrence of moire is prevented by separating the angles of the three colors of yellow, magenta, and cyan. However, since the ink is close in angle to any one of the above three colors, the ink is added. Therefore, there is a problem that moire tends to occur.
[0004]
In order to solve these problems, in the invention described in Japanese Patent Application Laid-Open No. 7-87346, an input three-color signal is converted into a three-variable color signal in a uniform color space, and a saturation signal is converted into a UCR (Under Color Removal). ) Rate is determined, and a plurality of color image output signals including black are determined from the three-variable color signal in the uniform color space and the UCR rate determined from the saturation signal. Japanese Patent Laid-Open No. 6-242523 discloses an image processing method in which a maximum black amount Kmax and a minimum black amount Kmin for reproducing a target color are obtained, and a value between Kmax and Kmin is set as a black amount. Are listed.
[0005]
[Problems to be solved by the invention]
The method of determining the inking amount according to the saturation of the input color signal described in the above-mentioned JP-A-7-87346 can improve the color reproducibility by reducing the inking amount in the high saturation portion, This is certainly effective in that the reproducibility of the character portion of the image mixed with pictograms can be improved by increasing the amount of inking in the gray portion. However, in this method, black is always applied to the gray portion of the highlight portion where the screen structure is easily perceived. Therefore, when an image forming apparatus using a rotation screen is used, the highlight portion is The problem of moiré occurs. In addition, in this method, since the inking amount is set from the saturation signal of the input color signal, black is mixed from the highlight portion in the gray portion, and the graininess of the highlight portion in the gray portion is deteriorated. Problem arises. Furthermore, in this method, as shown in Japanese Patent Laid-Open No. 6-242523, there is a region that cannot be used essentially among the maximum color gamut that can be reproduced by a four-color printer. The problem arises that the color reproducibility of the part is poor.
[0006]
In addition, the method disclosed in Japanese Patent Laid-Open No. 6-242523 discloses a color that the image forming apparatus has when reproducing four colors in order to determine the inking amount from the maximum black amount Kmax and the minimum black amount Kmin for reproducing the target color. It is certainly effective in that the reproduction range can be guaranteed and a sufficiently high maximum density can be obtained. However, in this method, nothing is indicated as to which value between the maximum black amount Kmax and the minimum black amount Kmin should be set, and is shown in the example of the publication. As described above, when the black amount is set to a constant rate between Kmax and Kmin, black is mixed in the highlight portion, resulting in a problem that the graininess is deteriorated and moire is generated.
[0007]
Furthermore, in the method disclosed in Japanese Patent Application Laid-Open No. 7-87346, it is necessary for the parameter designer of the color conversion apparatus to describe the functional relationship between the saturation of the input color signal and the inking rate. Even in the method disclosed in Japanese Patent No. 242523, it is necessary for the parameter designer of the color conversion device to describe the black amount adjustment parameter α, and in order to obtain good image quality characteristics when any method is executed. However, there is a problem that it takes a lot of man-hours because it is necessary to find various optimal function relations and parameters by conducting experiments while sequentially changing various function relations and parameters. Further, even if the above method is executed using optimized function relationships and parameters, there is no guarantee that an image with the highest image quality can be obtained.
An object of the present invention is to provide a color image processing method and apparatus capable of easily obtaining an optimum black amount for achieving a predetermined image quality when converting color signals of three colors into image recording signals. It is in.
[0008]
[Means for Solving the Problems]
In the color image processing method for converting the color signals of the three colors to obtain a plurality of color image recording signals including black, For a plurality of ink amounts, other than the ink corresponding to each ink amount Detecting an image recording signal; Based on each black amount and the image recording signal other than the black corresponding to each black amount, A step of predicting a predicted image quality value, and a black amount based on the predicted image quality value decide And a step of achieving the color image processing method.
Further, the above object is to provide a color image processing apparatus for converting a color signal of three colors to obtain a plurality of color image recording signals including black, For a plurality of ink amounts, other than the ink corresponding to each ink amount Candidate detection means for detecting an image recording signal; Based on each black amount and the image recording signal other than the black corresponding to each black amount, An image prediction means for predicting an image quality prediction value, and a black amount based on the image quality prediction value. decide This is achieved by a color image processing apparatus having a black amount optimizing means.
[0009]
DETAILED DESCRIPTION OF THE INVENTION
A color image processing method and apparatus according to an embodiment of the present invention will be described with reference to FIGS. First, a schematic configuration of a color image processing apparatus according to the present embodiment will be described with reference to FIG. FIG. 1 shows an example of a color image output system provided with the color image processing apparatus.
[0010]
The color image output system includes an image input device 100, an image processing device 200, and an image forming device 300.
The image input apparatus 100 takes in color images of various formats from the outside and outputs a color image signal. In the present embodiment, for each color data of R (red), G (green) and B (blue), a color image signal composed of RGB data of 8 bits, 256 gradations and a total of 24 bits is output.
[0011]
Specifically, the image input apparatus 100 reads a 35 mm color negative film, a positive film, or a silver salt photographic film typified by an APS film as RGB data by a CCD sensor, or a CD in the PhotoCD (trademark) format of KODAK. -Read image data from ROM and convert it to RGB data, or capture image data from a digital camera such as Canon DCS1c (trade name) and convert it to RGB data, or edit by a user using another computer Then, color image data saved in a recording medium represented by MO or Zip (storage media standard) is read from the recording medium and converted into RGB data, or an image transmitted from a device connected on the network information It converted to GB data, and has a function of transferring the RGB data to the image processing apparatus 200.
[0012]
The image forming apparatus 300 forms an image on a sheet based on an image recording signal (YMCK data in the present embodiment) input from the image processing apparatus 200. FIG. 2 shows a schematic configuration of an example of the image forming apparatus 300 of the present invention. In FIG. 2, a belt-like intermediate transfer member 50 is supported by rollers 5-1, 5-2, 5-3, 5-4 and a heating roll 2, and rotates in the direction of the arrow in the figure. . A heating roll 3 is disposed opposite to the heating roll 2. Four photoreceptors 1-1, 1-2, 1-3, and 1-4 are arranged around the intermediate transfer member 50. These four photoconductors 1-1, 1-2, 1-3, and 1-4 are uniformly charged by electrostatic latent image forming chargers 15, 16, 17, and 18. Based on the CMYK four-color image recording signals transferred from the image processing apparatus 200, the screen generator 390 performs pulse width modulation on the laser light. The laser light subjected to pulse width modulation is horizontally scanned on the four photoconductors 1-1, 1-2, 1-3, and 1-4 by the laser scanner scanning device 380. As a result, electrostatic latent images are formed on the four photoconductors 1-1, 1-2, 1-3, and 1-4.
[0013]
On the four photosensitive members 1-1, 1-2, 1-3, and 1-4 on which the electrostatic latent images are formed, a black developing unit 11, a yellow developing unit 12, a magenta developing unit 13, and a cyan developing unit 14 are provided. As a result, black, yellow, magenta, and cyan toner images are formed. These toner images are sequentially transferred to the intermediate transfer member 50 by the transfer units 50-1, 50-2, 50-3, and 50-4. As a result, a plurality of color toner images are formed on the intermediate transfer member 50.
Thereafter, the recording paper having the thermoplastic resin layer applied on the surface thereof is fed from the paper tray 6 by the paper feeder 7. The recording paper is heated while being wound around the heating roll 3 by the pin rolls 9-1 and 9-2 attached to the winding mechanism 8, and then the heating roll 2 and the heating roll 3 are in close contact with the intermediate transfer member 50. Is heated under pressure. As a result, the toner images of a plurality of colors on the intermediate transfer member 50 penetrate into the thermoplastic resin layer on the recording paper.
[0014]
The intermediate transfer body 50 and the recording paper heated and pressed by the heating roll 2 and the heating roll 3 are moved in close contact with each other and cooled by the cooling device 4. As a result, the toner that has penetrated into the thermoplastic resin layer is agglomerated and solidified to produce a strong adhesive force with the recording paper. Thereafter, in the roll 5-1 having a small curvature, the recording paper is separated from the intermediate transfer member 50 together with the toner by the stiffness of the recording paper itself, and is output to the outside. Since the toner image transferred and fixed on the recording paper is integrated with the resin layer on the surface of the recording paper, the surface of the recording paper becomes smooth and highly glossy.
[0015]
As the photoreceptors 1-1, 1-2, 1-3, and 1-4, various organic photoreceptors can be used in addition to various inorganic photoreceptors (Se, a-Si, a-SiC, CdS, and the like). it can.
As the toner, a known material composed of a thermoplastic binder containing pigments such as yellow, magenta, and cyan can be used. In the present embodiment, a polyester toner having a weight average molecular weight of 54000, a softening point of 113 ° C., and an average particle diameter of 7 μm is used. The amount of toner on the recording medium of each color varies depending on the pigment content of the toner, but is approximately 0.4 mg / cm. ² ~ 0.7mg / cm ² Is set as an exposure or development condition. In this embodiment, each color is 0.65 mg / cm. ² It is set to be.
[0016]
As a recording medium, a basis weight of 127.9 g / m, which is a commercially available cast coated paper ² The enamel-coated paper (Yonago Processed Paper Co., Ltd.) is coated with 7 μm thick polyester. In the present embodiment, a polyester having a weight average molecular weight of 12300, a number average molecular weight of 3270, and a softening point of 100 ° C. is used as the polyester to be applied.
[0017]
The intermediate transfer member 50 has a two-layer structure of a base layer and a surface layer. The base layer uses a polyimide film with a thickness of 70 μm to which carbon black is added, and the volume resistivity is changed by changing the addition amount of carbon black. ¹⁰ It is adjusted to Ωcm. As the base layer, for example, a sheet having a high heat resistance having a thickness of 10 to 300 μm can be used. More specifically, polyester, polyethylene terephthalate, polyethersulfone, polyetherketone, polysulfone, polyimide, Polymer sheets such as polyimide amide and polyamide can be used.
[0018]
As the surface layer, in this embodiment, when performing simultaneous transfer and fixing from the intermediate transfer member 50 to the recording paper, the intermediate transfer member 50 and the recording paper are in close contact with each other with the toner image interposed therebetween. Using a silicone copolymer having a rubber hardness of 40 degrees and a thickness of 50 μm, the toner image is transferred electrostatically from the photosensitive members 1-1, 1-2, 1-3, 1-4 to the intermediate transfer member 50 without image distortion. In order to achieve this, the volume resistivity of the silicon copolymer is 10 ¹⁴ It is adjusted to Ωcm.
Silicone copolymer has a characteristic that its surface is sticky to the toner at room temperature and has a property of easily separating the melted and fluidized toner, so that the toner is efficiently applied to a recording medium such as recording paper. It is ideal for the surface layer. As the surface layer, for example, a resin layer having a high releasability having a thickness of 1 to 100 μm can be used. More specifically, a tetrafluoroethylene-perfluoroalkyl vinyl ether copolymer or polytetrafluoroethylene is used. Etc. can be used.
[0019]
As the heating rolls 2 and 3, a metal roll or a roll having a heat resistant elastic layer such as silicon rubber can be used. A heat source is disposed inside the heating rolls 2 and 3, and the set temperature of the heat source is determined by the heat melting characteristics of the toner and the thermoplastic resin layer on the surface of the recording paper. In this embodiment, since the softening point of the toner> the softening point of the resin layer, the temperature of the heat source is set so that the set temperature of the heating roll 2> the set temperature of the heating roll 3. Specifically, the set temperature of the heat source of the heating roll 2 is set to 150 ° C., and the set temperature of the heat source of the heating roll 3 is set to 120 ° C. In this embodiment, the pressure between the heating roll 2 and the heating roll 3 during transfer / fixing is 5 kgf / cm. ² However, the pressure is not limited to this, for example, 1 kgf / cm ² -10kgf / cm ² It may be in the range. In the present embodiment, the outer diameters of the heating rolls 2 and 3 are set to 50 mm, and the rotation speeds of the heating rolls 2 and 3 are set so that the conveyance speed of the intermediate transfer member 50 is 240 mm / sec. ing.
In the present embodiment, the temperature of the surface of the recording medium in contact with the intermediate transfer member 50 becomes 70 ° C. when the recording medium such as recording paper is peeled off from the intermediate transfer member 50 by adjusting the air volume of the cooling device 4. I am doing so.
[0020]
In this embodiment, the tandem engine electrophotographic color printer is applied as the image forming apparatus 300. However, the image forming apparatus 300 is not limited to this, and a single engine system or a belt photoreceptor having heat resistance without using an intermediate transfer member. It is also possible to use a printer that employs a system in which toner images of a plurality of colors formed on a belt photoreceptor are directly transferred and fixed onto a recording sheet. Further, the image forming apparatus 300 is not limited to an electrophotographic color printer, and may be a color image forming apparatus such as a printing, ink jet system, thermal transfer system, and silver salt photographic system.
[0021]
The image processing apparatus 200 includes a first color conversion unit 210 and a second color conversion unit 220. The RGB data input from the image input device 100 is converted by the first color conversion unit 210 into data in the CIE · L * a * b * color space, which is one of the uniform color spaces. The L * a * b * data (first color signal) converted by the first color conversion unit 210 is converted into an image recording signal in the color space of the image forming apparatus 300 by the second color conversion unit 220, in the present embodiment. , Y (yellow), M (magenta), C (cyan), and K (black) are converted into data of the four colors (second color signal) and transferred to the image forming apparatus 300. In the present embodiment, the most common RGB data will be described as an example of an input color signal from the image input apparatus 100. However, other than the CMYK color space used in printing, the YCC color space used in PhotoCD, and the like. The color space data may be used.
[0022]
In the present embodiment, the first color conversion unit 210 converts an input color signal into a signal in the L * a * b * color space. However, the first color conversion unit 210 is not limited to this, and for example, an XYZ color space or L * The signal may be converted into a signal in another color space that does not depend on a device such as the u * v * color space. The first color conversion unit 210 is more preferably one that converts signals into a uniform color space such as L * u * v *.
Further, as the first color conversion unit 210, a matrix operation type color conversion circuit or a neural network type color conversion circuit widely used as a color conversion circuit can be used. A look-up table type color conversion circuit is used.
[0023]
The color conversion coefficient of the first color conversion unit 210 can be obtained by the following method. First, a color measurement value (L * a * b *) of a color image input to the image input apparatus 100 is measured with a commercially available colorimeter, and the color measurement value (L * a * b *) of the input color image is obtained. Corresponding RGB data is obtained, and the color conversion characteristics of the output data (RGB) with respect to the input colorimetric values (L * a * b *) are modeled. For such a color conversion model, a high-order polynomial or a neural network is generally used, but in this embodiment, a neural network is used. Then, a nonlinear optimization method is applied to the neural network model and solved in reverse to obtain output L * a * b * color data corresponding to the address of each input RGB data, and these are output to the color of the first color conversion unit 210. Set as conversion factor.
[0024]
Next, the second color conversion unit 220, which is the main part of the present invention, will be described in detail with reference to FIG.
The maximum black amount determination unit 221 and the minimum black amount determination unit 222 include an L * a * b * prediction unit, a CCM (Computer Color Matching) unit, and a binary search unit, and input colorimetric values (L * Kmax representing the maximum black amount and Kmin representing the minimum black amount for a * b *) are determined and sent to the black amount optimizing unit 224.
The L * a * b * prediction unit is configured by a neural network. This neural network is obtained by preparing a plurality of pairs of CMYK and L * a * b * of an image forming apparatus 300 such as a printer that performs image formation, and learning these pairs as teacher data. The relationship between CMYK and L * a * b * can be expressed by the following function.
(L *, a *, b *) = F (C, M, Y, K) (1)
Here, normally, the inverse function of the function F is not obtained. However, if the value of L * a * b * is given and one variable in CMYK is appropriately determined, the remaining three variables can be obtained from equation (1). For example, given the value of K, the value of CMY can be determined.
The CCM unit efficiently calculates the value of CMY from the value of L * a * b * and the value of K by a known method called CCM based on the following equation.
(C, M, Y) = G (L *, a *, b *, K) (2)
The binary search unit swings the value of K used for calculation by the CCM unit by the binary search algorithm, and determines whether or not the CMY value obtained by the CCM unit satisfies the following expression (3): Kmax and Kmin that satisfy Equation (3) are efficiently obtained.
0 ≦ C, M, Y ≦ 100% (3)
Here, the largest K value that satisfies Equation (3) is the maximum black amount Kmax, and the smallest K value is the minimum black amount Kmin.
[0025]
The image quality predicting unit 223 has a CCM unit similar to the above, and the color of the color from the L * a * b * data obtained from the first color converting unit 210 and the black amount K obtained from the black amount optimizing unit 224. The image recording signal CMY of the image forming apparatus 300 at the time of combination is determined. Here, the candidate detection means referred to in the claims is mainly composed of this CCM section. Further, the image quality prediction unit 223 obtains an image quality prediction value Q by substituting the black amount K and the value of the image recording signal CMY into the equation (4), and sends the image quality prediction value Q to the black amount optimization unit 224. .
Q = H (C, M, Y, K) (4)
Here, H is an image quality prediction function for obtaining a predicted value (image predicted value Q) for a predetermined image quality of an image output by the black amount K and the image recording signal CMY.
[0026]
In the present embodiment, the image quality prediction unit 223 predicts the graininess and moire in the image quality. As a psychophysical quantity representing graininess and moire, the winner spectrum of an image is widely known. As for the winner spectrum, see, for example, Journal of the Japan Printing Society Vol. 28, No. 6 (1991) pp. 53-pp. 58. The smaller the value of the Wiener spectrum, the better the granularity of the image and the less the moire. In the present embodiment, the inverse of the Wiener spectrum is used as the predicted image value Q.
[0027]
In the present embodiment, the image quality prediction function H used in the image quality prediction unit 223 is configured by a neural network. This neural network was created as follows. That is, a sample is printed out based on the combination of CMYK by a target image forming apparatus 300 (for example, a printer), the sample is measured with a micro densitometer, a winner spectrum is calculated from the measured value, and the reciprocal of the winner spectrum is obtained. The image quality prediction value Q is obtained, and a plurality of pairs of CMYK and image quality prediction value Q are prepared. Then, the neural network is made to learn these plural pairs as teacher data. In this embodiment, the image quality prediction function H is configured by a neural network. However, the present invention is not limited to this, and any image quality prediction value Q can be obtained from four CMYK input parameters. You may comprise with an up table etc.
The parameter input unit 225 sets the image quality prediction function H of the image quality prediction unit 223.
[0028]
The black amount optimizing unit 224 calculates the maximum black amount Kmax obtained from the maximum black amount determining unit 221 and the minimum black amount Kmin obtained from the minimum black amount determining unit 222 from the maximum black amount Kmax expressed by Expression (5). The value of the black amount K existing up to the minimum black amount Kmin is sent to the image quality prediction unit 223.
Kmin ≦ K ≦ Kmax (5)
Here, the value of Kmin may be changed to 0 which means a case where no ink is used. In this case, it is not necessary to provide the minimum black amount determination unit 222. However, in order to appropriately utilize all of the color reproduction range of the image forming apparatus 300, it is desirable to provide the minimum black amount determination unit 222 and use the minimum black amount Kmin.
[0029]
Further, the black amount optimization unit 224 obtains the image quality prediction value Q corresponding to each black amount K sent to the image prediction unit 223 from the image quality prediction unit 223, and the corresponding image quality prediction value Q is the largest, that is, granular The black amount K when no sexuality or moire occurs or is predicted to be minimal even if it occurs is determined as the optimal black amount Kopt, and the optimal black amount Kopt is determined by the CMY determining unit 226 and the CMYK output unit 227. To send.
[0030]
The CMY determining unit 226 includes a CCM unit similar to the above, and includes the three-color signal L * a * b * obtained from the first color conversion unit 210 and the optimum black amount Kopt obtained from the black amount optimization unit 224. Then, the optimum image recording signal CoptMoptYopt of the image forming apparatus 300 is determined, and these optimum image recording signals CoptMoptYopt are sent to the CMYK output unit 227.
The CMYK output unit 227 outputs the three-color image recording signal CoptMoptYopt obtained from the CMY determination unit 226 and the black amount Kopt obtained from the black amount optimization unit 224 to the image forming apparatus 300.
[0031]
Next, the operation of the second color conversion unit 220, which is the main part of the present invention, will be described with reference to FIG. The maximum black amount determination unit 221 determines Kmax representing the maximum black amount for the L * a * b * data input from the first color conversion unit 210, sends the Kmax to the black amount optimization unit 224, and sets the minimum black amount. The black amount determination unit 222 determines Kmin representing the minimum black amount for the L * a * b * data input from the first color conversion unit 210, and sends the Kmin to the black amount optimization unit 224 (step S1). . The black amount optimization unit 224 sequentially sends the black amount K between the maximum black amount Kmax and the minimum black amount Kmin to the image quality prediction unit 223.
[0032]
The image quality prediction unit 223 uses the image recording signal CMY of the image forming apparatus 300 based on the L * a * b * data input from the first color conversion unit 210 and the black amount K input from the black amount optimization unit 224. (Step S2), an image predicted value Q is obtained based on the black amount K and the determined image recording signal CMY, and the image quality predicted value Q is sent to the black amount optimizing unit 224 (step S3).
Next, the black amount optimizing unit 224 determines the black amount K where the obtained image quality prediction value Q is the largest as the optimal black amount Kopt (step S4), and outputs the optimal black amount Kopt to the CMY determining unit 226 and the CMYK output. To the unit 227.
[0033]
The CMY determining unit 226 calculates the optimum image recording signal CoptMoptYopt of the image forming apparatus 300 from the three-color signal L * a * b * obtained from the first color converting unit 210 and the optimum black amount Kopt obtained from the black amount optimizing unit 224 (step S5) is determined and sent to the CMYK output unit 227. The CMYK output unit 227 outputs the three-color image recording signal CoptMoptYopt obtained from the CMY determination unit 226 and the black amount Kopt obtained from the black amount optimization unit 224 to the image forming apparatus 300.
[0034]
In this way, it is possible to determine the amount of black that can prevent or minimize the occurrence of image quality graininess and moire while ensuring the maximum color reproduction range of the image forming apparatus. As a result, it is possible to reliably obtain a print having an optimum image quality. Further, it is not necessary to obtain parameters such as the inking function and the inking rate as in the conventional case, and it is not necessary to repeat trial and error (trial and error) such as experiments.
[0035]
The present invention is not limited to the above embodiment, and various modifications can be made.
For example, in the above embodiment, the image quality is predicted with respect to graininess and moire, but it may be an image quality element that changes depending on the amount of black, for example, glossiness, line reproducibility, in-plane uniformity. Etc. may be predicted. Further, as the image quality prediction value Q, a sensory evaluation result obtained by observing a sample by a human may be used. If a value related to performance other than image quality is used instead of the image quality prediction value Q, the amount of ink that satisfies the performance used as the value can be determined. For example, if the amount of toner used is used instead of the image quality prediction value Q, the cost of toner can be reduced.
[0036]
In addition, the second color conversion unit 220 of the above embodiment may be configured with a 3-input 4-output direct lookup table. This direct look-up table may be configured to calculate an image recording signal CMYK by performing an interpolation operation by cubic interpolation using a value obtained by dividing each axis of the input L * a * b * by 16 as an input address, for example. it can. As the interpolation method of the direct lookup table, the cubic interpolation method is applied, but other methods such as a triangular prism interpolation method and a tetrahedral interpolation method may be applied as long as they are known interpolation methods. As table values for the input addresses L * a * b * of the direct lookup table, the optimum black amount Kopt and the optimum image signal CoptMoptYopt obtained by executing the same processing as in steps S1 to S5 described above. Should be set.
In this way, if the second color conversion unit 220 is configured with a direct lookup table, in addition to the effects of the above-described embodiment, it is possible to increase the speed of image processing. If configured, real-time processing can be realized.
[0037]
In addition, the second color conversion unit of the above embodiment may be configured to apply a known color conversion method capable of performing 3-input 4-output color conversion. For example, other colors such as a neural network type may be used. A configuration to which a conversion method is applied may be used.
In the above embodiment, the first color conversion unit 210 and the second color conversion unit 220 may be configured by a color converter such as one direct lookup table. The color conversion characteristics in this case can be obtained by determining the color conversion parameters of the first color conversion unit 210 and the second color conversion unit 220 and then combining the color conversion parameters.
[0038]
【The invention's effect】
As described above, according to the present invention, an optimal black amount for achieving a predetermined image quality can be easily obtained when converting color signals of three colors into an image recording signal.
[Brief description of the drawings]
FIG. 1 is a diagram showing an example of a color image output system having a color image processing apparatus according to an embodiment of the present invention.
FIG. 2 is a diagram illustrating an example of a color image forming apparatus according to an embodiment of the present invention.
FIG. 3 is a diagram illustrating a schematic configuration of a second conversion unit of the color image processing apparatus according to the embodiment of the present invention.
FIG. 4 is a diagram illustrating an example of an image processing method of a color image processing apparatus according to an embodiment of the present invention.
[Explanation of symbols]
1-1 to 1-4 photoconductor
2 Heating roll
3 Pressure roll
4 Cooling device
5-1-5-4 Roller
6 Paper tray
7 Paper feeder
8 winding mechanism
9-1, 9-2 Pin roll
11 Black developer
12 Yellow developer
13 Magenta developer
14 Cyan developer
15-18 Charger for forming electrostatic latent image
50 Intermediate transfer member
50-1 to 50-4 transfer device
100 Image input device
200 Image processing apparatus
210 First color converter
220 Second color conversion unit
221 Maximum black amount determination unit
222 Minimum ink amount determination part
223 Saturation determination unit
224 Ink amount determination unit
225 Parameter input section
226 CMY decision unit
227 CMYK output section
300 Image forming apparatus
380 Laser scanner scanning device
390 screen generator

Claims (10)

In a color image processing method for converting a color signal of three colors and obtaining an image recording signal of a plurality of colors including black,
Detecting a non-black image recording signal corresponding to each black amount for a plurality of black amounts ;
Predicting an image quality prediction value corresponding to each black amount based on each black amount and the image recording signal other than the black corresponding to each black amount ;
A color image processing method comprising: determining a black amount based on the image quality prediction value. The color image processing method according to claim 1.
And a step of obtaining a maximum black amount that can be used to reproduce the colors indicated by the three color signals.
The color image processing method characterized in that, in the step of obtaining the black amount, the black amount is obtained within a range equal to or less than the maximum black amount. The color image processing method according to claim 1 or 2,
A step of obtaining a minimum black amount that can be used to reproduce the colors indicated by the three color signals;
The color image processing method characterized in that, in the step of obtaining the black amount, the black amount is obtained in a range equal to or larger than the minimum black amount. The color image processing method according to any one of claims 1 to 3,
The step of predicting the image quality prediction value is executed by a neural network that has learned the relationship between the image recording signal and an image quality prediction value related to the image quality of an image printed out based on the image recording signal. A color image processing method. The color image processing method according to any one of claims 1 to 3,
The step of predicting the image quality prediction value is executed using a direct lookup table in which an image quality prediction value related to the image quality of an image printed out based on the image recording signal is set at an address corresponding to the image recording signal. A color image processing method. In a color image processing apparatus for converting a color signal of three colors and obtaining an image recording signal of a plurality of colors including black,
Candidate detection means for detecting an image recording signal other than the black corresponding to each black amount for a plurality of black amounts ;
Image prediction means for predicting an image quality prediction value corresponding to each black amount based on each black amount and the image recording signal other than the black corresponding to each black amount ;
A color image processing apparatus comprising: a black amount optimizing unit that determines a black amount based on the image quality prediction value. The color image processing apparatus according to claim 6.
Furthermore, it has a maximum black amount determination means for obtaining a maximum black amount that can be used to reproduce the colors indicated by the three color signals,
The color image processing apparatus, wherein the black amount optimization means obtains a black amount within a range equal to or less than the maximum black amount. The color image processing apparatus according to claim 6 or 7,
And a minimum black amount determining means for obtaining a minimum black amount that can be used to reproduce the colors indicated by the three color signals.
The color image processing apparatus, wherein the black amount optimization means obtains a black amount within a range equal to or larger than the minimum black amount. The color image processing apparatus according to any one of claims 6 to 8,
The color image processing apparatus, wherein the image quality prediction means includes a neural network that learns a relationship between the image recording signal and an image quality prediction value relating to an image quality of an image printed out based on the image recording signal. . The color image processing apparatus according to any one of claims 6 to 8,
The color image having a direct look-up table in which an image quality prediction value relating to the image quality of an image printed out based on the image recording signal is set at an address corresponding to the image recording signal. Processing equipment.

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