JP2012039320A - Image processing system and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing system and an image processing method which predict specular glossiness of an image, which has multiple colors of pigment ink overlaid on a recording medium and is formed by an image forming apparatus.SOLUTION: A spectroscopy specular reflectivity on an image formed with a target color corresponding to an amount of pigment ink in multiple colors is calculated using a refractive index and an area rate of each color of the pigment ink. A convexoconcave component due to the surface unevenness and a thin film interference component due to coloring of specular light caused by thing-film interference of each color of the pigment ink are respectively predicted as fluctuation from an actual measurement value contained in the calculation value. A spectroscopy specular reflectivity against the image formed with the target color is highly accurately predicted by subtracting the convexoconcave component and the thin film interference component from the calculation value of the spectroscopy specular reflectivity, to calculate specular glossiness. By considering influence e1 of the convexoconcave component and influence e2 of the thin film interference component on a specular glossiness characteristic 301 calculated by only considering bronze, the specular glossiness characteristic can be brought close to a specular glossiness characteristic 501 which is actually measured.

Description

  The present invention relates to an image processing apparatus and an image processing method for predicting the specular gloss of a formed image formed by an image forming apparatus that forms an image by superimposing a plurality of color pigment inks on a recording medium.

  Image recording in an ink jet printer is performed by ejecting ink droplets onto a recording medium from a recording head. As a method of ejecting ink droplets from the recording head, a method using a piezoelectric element (piezo element) that generates mechanical distortion by applying a voltage, or a method in which ink is rapidly heated to vaporize, is generated at that time. A method using the high pressure of bubbles is widely used.

  As inks used in ink jet printers, dyes that are easily dissolved in water are often used, but in recent years, pigments are often used for the purpose of improving the weather resistance and water resistance of images. Pigment inks are known to prevent the coloring material from penetrating into the recording medium and overlap the recording medium. Therefore, when an image is recorded, the surface shape of the recording medium becomes complicated, and the glossiness of the surface is low. It varies depending on the amount of color material present on the recording medium. Here, the glossiness refers to the specular glossiness (for example, see Non-Patent Document 1).

  Here, FIG. 1 shows a schematic diagram of the image surface formed by the pigment ink superimposed on the recording medium. FIG. 1 (a) shows a state in which the image surface is formed of both the recording medium and the pigment ink having the height d1, and FIG. 1 (b) shows the image surface completely covered with the pigment ink having the height d1. It shows the state of being formed. FIG. 1 (c) shows a state where pigment ink is further ejected with respect to the state of FIG. 1 (b), and the pigment ink is further superimposed at a height d2.

  In addition, due to the property that the pigment ink covers the surface of the recording medium, the specularly reflected light is caused by bronze caused by selective reflection (wavelength dependence) of light on the pigment particle surface and thin film interference caused by the thin film structure formed by the pigment ink. The phenomenon of coloration also affects the gloss of the formed image. In particular, thin film interference is a phenomenon caused by the occurrence of a height difference d1 or d2 between the pigment color material surface and the recording medium surface, as shown in FIGS. 1 (a) to 1 (c).

  Here, referring to FIG. 2, the coloring of reflected light by thin film interference will be described. In FIG. 2, 201 denotes an air layer, 202 denotes an ink layer having a thickness d, and 203 denotes a recording medium. Reference numeral 204 denotes light incident on the ink layer 202 from the air layer 201, and reference numeral 205 denotes light incident on the recording medium 203 through the ink layer. Reference numeral 206 denotes light reflected from the surface of the ink layer 202, and reference numeral 207 denotes light emitted from the surface of the recording medium 203 through the ink layer 202 to the air layer 201. As shown in the figure, an optical path difference is generally generated by the difference in refractive index between the air layer 201 and the ink layer 202 and the thickness d of the ink layer 202. Due to the optical path difference, a phase difference occurs in the spectral reflectance between the light 206 reflected on the surface of the ink layer 202 and the light 207 that passes through the ink layer 202 and emerges into the air layer 201, so Reflected light appears to be colored due to an increase or decrease in reflectivity (thin film interference).

  As described above, when image formation using pigment ink is performed in an inkjet printer, gloss nonuniformity occurs in the formed image due to the influence of thin film interference or the like. As a method for solving this non-uniform glossiness, it is conceivable to control the glossiness by a profile for converting image data input to the printer into ink colors used in the printer. The input image data referred to here is image data such as RGB, and the ink colors are C: cyan, M: magenta, Y: yellow, K: black, Lc: light cyan, Lm: light. Each color of ink mounted on the printer such as magenta is shown. In creating such a profile, it is necessary to uniquely determine the amounts of C, M, Y, K, Lc, and Lm for one RGB value from a huge number of ink combinations. Here, as combinations of inks, for example, assuming that the number of gradations that can be expressed per color is 256 gradations (8 bits), there are combinations of 256 to the power of the number of inks (256 to the sixth power). In order to create a profile, it is practically impossible to print and measure patches corresponding to all of this enormous number of ink combinations on a recording medium. Therefore, in order to create a gloss control profile, a technique for predicting the gloss in the formed image by printing and measuring the smallest possible number of patches is essential.

  Hereinafter, a method for predicting gloss (mirror glossiness) in a formed image will be described using Non-Patent Document 1.

First, according to Non-Patent Document 1, the specular glossiness G _s (θ) with respect to the specified incident angle θ is calculated by the following equation (1).

In Expression (1), φ _s represents a reflected light beam from the sample surface with respect to the incident angle θ, and φ _os represents a reflected light beam from the standard surface with respect to the incident angle θ. G _os indicates the glossiness (%) of the standard surface used, and is calculated by the following equation (2).

In Equation (2), S _D (λ) represents the relative spectral distribution of the standard light D65, and V (λ) represents the reflected light beam from the standard surface with respect to the specified incident angle θ. ρ ₀ (θ) indicates the specular reflectance at an incident angle θ defined on the glass surface whose refractive index is a constant value of 1.567 over the entire visible wavelength range. ρ (θ, λ) is the refractive index n (λ) and represents the spectroscopic specular reflectance of the primary standard surface at the specified incident angle θ determined by the following Fresnel equation (3).

According to the specular gloss measurement conditions according to Non-Patent Document 1, the standard light D65 shown in Non-Patent Document 2 as the light source and the light receiver and the color matching function y ~ (λ) (y ~ Is described as using the same combination of spectral luminous efficiency as bar) above y.

In other words, if the spectroscopic specular reflectance of reflected light with respect to an incident angle θ on an arbitrary specular gloss measurement sample (hereinafter referred to as α (θ, λ)) is known, the reflected light beam φ _s from the sample surface in Equation (1) can be expressed as It can be simulated by the following equation (4).

  Similarly, the reflected light beam φos on the standard surface should also be simulated as in the following equation (5) using the specular specular reflectance ρ (θ, λ) of the standard surface shown in equation (2). Can do.

  That is, if the formula (1) is transformed using the formulas (2), (4), and (5), the specular surface reflectivity α (θ, λ) with respect to the angle θ of an arbitrary sample is used, and the mirror surface shown below The specular glossiness can be simulated by the glossiness calculation formula (6).

  As the method for calculating the spectroscopic surface reflectance of the reflected light with respect to the incident angle θ of the sample surface where the refractive index n (λ) is known, the Fresnel equation (3) described above can be applied. In other words, if the refractive index n (λ) of all pigment inks used in the ink jet printer can be obtained, the specular reflectance can be obtained from Fresnel's equation (3). The specular gloss of each ink can be predicted.

Here, FIG. 3A shows a calculation result of the specular gloss when a gradation is drawn on the recording medium having the refractive index n _p (λ) with the pigment ink exhibiting the refractive index n _i (λ). This calculation is performed using Fresnel's formula (3) and specular gloss calculation formula (6), and the calculation result is the specular gloss characteristic 301 shown in FIG. The gradation drawn here is a gradation from paper white to ink color (maximum ink absorption amount in the recording medium). In FIG. 3A, P on the vertical axis indicates the specular gloss calculated from the refractive index n _p (λ) of the recording medium, and I is the specular surface calculated from the refractive index n _i (λ) of the ink. Indicates glossiness. Here, the ink jet printer changes the number of dots per unit area (shown as hatched rectangles in the figure) as 401 → 402 → 403 → 404 → 405 shown in FIG. Tone expression (area gradation) is performed.

Therefore, in the region T1 in which the ink discharge amount is 0 to H in FIG. 3A, the specular glossiness depends on the area ratio of the refractive index n _p (λ) of the recording medium and the refractive index n _i (λ) of the ink. Change. In this case, the surface state is the floor completely covered with ink as shown in FIG. 1 (b) from the gradation in which the surface of the recording medium is formed of both the recording medium and ink as shown in FIG. 1 (a). Changes to the key. H on the horizontal axis in FIG. 3A indicates the ink discharge amount when the entire surface of the recording medium is uniformly covered with ink as shown in FIG. 1B. Further, in the subsequent gradation change, ink is further ejected onto the recording medium, and the surface shape changes as shown in FIG. 1C, but the refractive index n _i (λ of the ink overlapping the surface is changed. ) Is constant. Therefore, in the region T2 where the ink discharge amount is H or more in FIG.

Specular gloss measurement method (JIS Z 8741) Standard light and standard light source for colorimetry (JIS Z 8720) Color display method-XYZ color system and X10Y10Z10 color system (JIS Z 8701)

However, the specular gloss characteristic 301 shown in FIG. 3 (a) is calculated using the Fresnel equation (3) and the specular gloss calculation equation (6) based on the refractive index of the ink. The change in specular gloss due to the refractive index alone is shown. Therefore, the specular gloss characteristic 301 shown in FIG. 3A is the specular gloss characteristic when the same ink is actually printed on a recording medium and actually measured with a measuring instrument according to the measurement conditions described in Non-Patent Document 1. Is different. Here, FIG. 3B shows a specular gloss characteristic 301 calculated based only on the refractive index and a specular gloss characteristic 501 which is a result of actual measurement, and there is a large difference between them. I understand that. This is because when printing with pigment ink, the amount of specular reflection increases or decreases due to changes in the light scattering phenomenon due to the uneven shape of the recording surface, and bronze and thin film interference due to selective reflection (wavelength dependence) of pigment particle light. This is caused by the occurrence of multiple occurrences. That is, the specular reflection spectral reflectance calculated by the Fresnel equation (3) is calculated only by the refractive index n _i (λ) of the pigment particles of the ink. Limited to simulating the effects of. In other words, even if the Fresnel equation (3) is used, it is impossible to simulate the influence on the specular glossiness due to the unevenness of the recording surface and the thin film interference.

  In order to solve the above-described problems, an object of the present invention is to realize the following functions in an image forming apparatus that forms an image by superimposing pigment ink on a recording medium. That is, the specular glossiness in the formed image can be predicted with high accuracy by individually considering the influence of the unevenness of the surface and the coloring of the regular reflection light due to the thin film interference. Furthermore, the color separation profile of the image forming apparatus is generated so that the gloss in the formed image can be controlled by predicting the specular gloss with high accuracy.

  As a means for achieving the above object, an image forming apparatus of the present invention comprises the following arrangement.

  That is, an image processing apparatus for predicting the specular gloss of a formed image formed by an image forming apparatus that forms an image by superimposing a plurality of color pigment inks on a recording medium, For the formed image of the target color corresponding to one of the combinations of the ink amount data, using the refractive index of each pigment ink in the target color and the area ratio that the dots of each pigment ink cover the surface in a predetermined area, Specular specular reflectance calculating means for calculating spectroscopic specular reflectivity for the formed image, and spectroscopic specular reflectivity of the specular specular reflectance due to unevenness of the image surface formed by overlapping each pigment ink in the target color on the recording medium. Concavity and convexity component predicting means for predicting the fluctuation amount as the concavity and convexity component, and thin film interference generated by overlapping each pigment ink on the target color on the recording medium Thin film interference component predicting means for predicting fluctuations of the spectroscopic specular reflectance due to coloring of specular reflection light as thin film interference components, and removing the concave and convex components and the thin film interference components from the spectroscopic specular reflectance. A specular gloss calculation means for predicting a specular specular reflectance for the formed image with the target color and calculating a specular gloss on the formed image with the target color using the predicted spectroscopic specular reflectance. It is characterized by having.

  Further, the present invention is characterized by having means for generating a color conversion profile of the image forming apparatus by predicting the specular gloss as described above.

  According to the present invention, in an image forming apparatus that forms an image by superimposing pigment ink on a recording medium, the specular glossiness in the formed image is affected by the unevenness of the surface and coloring of specular reflection light by thin film interference. It is possible to predict with high accuracy in consideration of individual cases. Furthermore, it is possible to generate a color separation profile of the image forming apparatus that makes it possible to control the gloss in the formed image by predicting the specular gloss with high accuracy.

The figure which shows the difference in the fixing state of pigment ink, Diagram showing the principle of thin film interference, A diagram showing the change in specular gloss due to refractive index only and the actual change in specular gloss, The figure which shows the mode of the area gradation in an inkjet printer, 1 is a diagram showing a schematic configuration of an image forming system in an embodiment according to the present invention; Block diagram showing the main configuration of the PC in the present embodiment, FIG. 2 is a block diagram showing a functional configuration of an image forming system in the embodiment. The figure which shows the detailed structure of the halftoning part in this embodiment, The figure which shows the example of a storage of the image scanning in the quantization process of this embodiment, and error data, The flowchart which shows the quantization process in this embodiment, The figure which shows an example of the quantization result in this embodiment, The figure which shows the structural example of the print data in this embodiment. The figure which shows the example of the dot arrangement patterning process in this embodiment, The flowchart which shows the profile creation process in this embodiment, The figure which shows an example of the target glossiness setting screen in this embodiment, The figure which shows the characteristic of the specular glossiness with respect to the ink discharge amount, A flowchart showing gloss interpolation processing in the present embodiment, The flowchart which shows the gloss model calculation process in the specular gloss prediction process of this embodiment, The figure which shows the example of a patch used in the glossiness model calculation process of this embodiment, The figure which shows an example of the patch measurement environment in the gloss model calculation process of this embodiment, The figure which shows the example of the spectral reflectance calculated and measured in the gloss model calculation process of this embodiment, It is a figure which shows the difference of the calculated value and the measured value of the spectral reflectance in the gloss model calculation process of this embodiment.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. The following embodiments do not limit the present invention related to the scope of claims, and all combinations of features described in the present embodiments are essential to the solution means of the present invention. Not necessarily.

<First Embodiment>
Apparatus Configuration FIG. 5 shows a schematic configuration of the image forming system in the present embodiment. In the figure, reference numeral 601 denotes an ink jet printer (hereinafter simply referred to as a printer), and reference numeral 602 denotes a computer (PC) having both a printer controller and a client computer. The printer 601 and the PC 602 are connected by a connector cable 603 such as a network cable / SCSI cable or a USB cable.

  FIG. 6 is a block diagram showing the main configuration of PC 602 shown in FIG. In the figure, reference numeral 701 denotes an interface (I / F) for connecting a mouse and keyboard 711 and a PC 602 for a user to input various manual instructions. A CPU 702 controls the operation of each block in the PC 602 or executes a program stored therein. A ROM 703 stores a necessary image processing program and the like in advance. A RAM 704 temporarily stores a program and image data to be processed in order for the CPU 702 to perform processing. Reference numeral 705 denotes a display control unit that controls the display 712 that displays an image to be processed and displays a message to the user. An interface (I / F) 706 connects the PC 602 and the printer 601. Reference numeral 707 denotes a CD drive capable of reading or writing data stored in a CD (CD-R / CD-RW / DVD / DVD-R / DVD-RW) which is one of external storage media. Like 707, 708 is an FD drive that can read from and write to FD. Reference numeral 709 denotes a hard disk (HD) capable of storing in advance programs and image data to be transferred to the RAM 704 and the like and storing processed image data. If an image processing program or printer information is stored on a CD, FD, DVD, etc., these programs are first installed on the HD709 and transferred to the RAM 704 as necessary. , Controlled by the CPU 702. 710 is an interface that connects a computer system with an external input device 713 such as a modem or a network card that transmits various data stored in various places in the computer system to an external device and receives various data from the external device. I / F).

  FIG. 7 is a block diagram showing each functional configuration in the image forming system shown in FIG. The printer 601 in the present embodiment performs printing with pigment ink, and for this purpose, a recording head that discharges ink is used.

  As programs that operate on the operating system (OS) of the PC 602, there are applications and printer drivers. The application 801 creates image data to be printed by the printer 601. The input of image data to the application 801 is performed by taking it into the PC 602 via various media, for example. For example, image data in JPEG format or the like captured by a digital camera can be captured from an external input device 713 such as a flash memory via the I / F 710. Further, for example, image data stored in the HD 709 or image data stored in the CD-ROM 707 can be captured. Furthermore, it is also possible to capture image data on the web from the Internet via the NIC 713. The image data captured in the PC 602 in this way is displayed on the display 712 and subjected to editing, processing, and the like via the application 801, and then, for example, image data R, G, and B of the sRGB standard are created. The image data R, G, and B are transferred to the printer driver in response to a print instruction from the user.

  The printer driver of this embodiment includes a pre-processing unit 802, a post-processing unit 803, a γ correction unit 804, a halftoning unit 805, a print data creation unit 806, and LUTs 821, 822, and 823. Note that the LUTs 821, 822, and 823 may be stored in a common memory such as the RAM 704, for example.

  First, the pre-processing unit 802 performs gamut mapping, that is, color management, on the image data R, G, and B input from the application. Here, in order to map the color gamut reproduced by the image data R, G, B of the sRGB standard into the color gamut reproducible by the printer 601, refer to the three-dimensional LUT821 that holds the relationship between these color gamuts. To do. Further interpolation processing is used in combination with the LUT processing to convert 8-bit image data R, G, B into image data R, G, B in the printer color gamut. Next, in the post-processing unit 803, based on the image data R, G, and B on which the color management has been performed, for example, C, M, Y, K, Find color separation data such as Lc and Lm. At the time of this color separation process, a three-dimensional LUT 822 that is a color separation profile for the printer 601 is referred to, and an interpolation operation is further used for the LUT 822 grid point data. The γ correction unit 804 performs gradation value conversion for each color data of the color separation data obtained by the post-processing unit 803. Specifically, by using a one-dimensional LUT 823 corresponding to the gradation characteristics of each color ink of the printer 601, the color separation data is converted so as to linearly correspond to the gradation characteristics of the printer 601. In the halftoning unit 805, for example, the 8-bit color separation data C, M, Y, K, Lc, and Lm are each quantized to be converted into, for example, 4-bit data. Here, it is assumed that 8-bit data is converted into 4-bit data using an error diffusion method. This 4-bit data becomes an index (gradation information) for indicating an arrangement pattern in the dot arrangement patterning process in the printer 601. Finally, the print data creation unit 806 creates print data in which print control information is added to the print image data containing the 4-bit index data. Note that the processing in the PC 602 described above is executed by the CPU 702 in accordance with those programs. At that time, the program is read from the ROM 703 or HD 709 and used, and the RAM 704 is used as a work area when executing the processing.

  In the printer 601 to which the print data created as described above is input, the dot arrangement patterning processing unit 807 and the mask data conversion processing unit 808 perform processing on the print data. That is, the dot arrangement patterning processing unit 807 performs dot arrangement for each pixel corresponding to the actual print image according to the dot arrangement pattern corresponding to the input 4-bit index data. In this way, by assigning a dot arrangement pattern corresponding to the gradation value of each pixel represented by 4-bit data, dot on / off is defined in each of a plurality of areas in the pixel, Discharge data “1” or “0” is arranged for each area. The mask data conversion processing unit 808 performs mask processing on the 1-bit ejection data obtained in this way. That is, the ejection data for each scan for completing the recording of the scanning area of the predetermined width by the recording head 810 is generated by a process using a mask corresponding to each scanning. The ejection data C, M, Y, K, Lc, and Lm for each scan are sent to the head driving circuit 809 at an appropriate timing, whereby the recording head 810 is driven, and each ink is ejected according to the ejection data.

  Note that the above-described dot arrangement patterning process and mask data conversion process in the printer 601 are executed under the control of the CPU 702 constituting the control unit of the printer 601 using a dedicated hardware circuit for each. Note that the above processing may be performed by the CPU 702 according to a program, or may be executed by the printer driver in the PC 602, for example. It is clear from the following description that the form of these processes is not questioned when applying the present invention.

  Hereinafter, processing in each configuration illustrated in FIG. 7 will be described in detail.

Quantization process First, the quantization process in the halftoning unit 805 will be described. In the following description, a minimum unit that is an object of image processing for multi-value data represented by a plurality of bits is referred to as a pixel, and data corresponding to the pixel is referred to as pixel data. Note that the image processing for multi-valued data is, for example, C, M, Y, K, Lc, Lm corresponding to each color of ink that uses R, G, B 8-bit data in the printer 601 in the post-processing unit 803. Refers to color separation processing that converts each 8-bit data. In addition, the halftoning unit 805 quantizes 8-bit data of C, M, Y, K, Lc, and Lm into 4-bit data of C, M, Y, K, Lc, and Lm. Included in processing. From another point of view, the “pixel” in the present embodiment is a minimum unit that can express a gradation, and has gradation value information of a plurality of bits.

  FIG. 8 is a block diagram showing a detailed configuration of the halftoning unit 805 in the present embodiment. In this figure, 901 is an input terminal for pixel data, 902 is a cumulative error adding unit, 903 is a threshold setting terminal for setting a quantization threshold when converting the input pixel data to two or more gradation numbers, and 904 is a quantum setting terminal. The conversion unit 905 is an error calculation unit that calculates a quantization error. Reference numeral 906 denotes an error diffusion unit for diffusing the quantization error, 907 is an accumulated error memory for storing the accumulated error, and 908 is an output terminal for pixel data formed after a series of processing.

  Pixel data of pixels selected from all images by an image scanning unit (not shown) is sequentially input to the input terminal 901 of the halftoning unit 805. The halftoning unit 805 is configured to sequentially process each input pixel data and to output one pixel at a time from the output terminal 908. Here, FIG. 9A shows a state of image scanning in the image scanning unit. In the image scanning unit, pixels to be processed are selected one by one from image data configured by arranging a plurality of pixels, and the pixel data is input to the input terminal 901 of the halftoning unit 805. In FIG. 9 (a), each square indicates an individual pixel, 1001 indicates a pixel (start pixel) positioned at the upper left end of the image, and 1002 indicates a pixel (final pixel) positioned at the lower right end of the image. . Scanning of an image is started by first setting the start pixel 1001 at the upper left corner of the image area as a selected pixel (hereinafter referred to as a target pixel), and then, one pixel at a time in the right direction indicated by an arrow in the figure, The process proceeds while switching the target pixel. When the processing is completed up to the right end of the uppermost row, the target pixel is moved to the left end pixel of the pixel row one stage below. In this order, the process scan is advanced along the arrow in the drawing, and when the process reaches the final pixel 1002 at the lower right end, the process scan of the main image is completed.

  FIG. 10 is a flowchart showing the quantization process in the halftoning unit 805. When the quantization process is started, first, in S1101, image data to be processed is input from the image scanning unit to the input terminal 901 as described above. In step S1102, the cumulative error adding unit 902 adds the cumulative error value corresponding to the pixel position stored in the cumulative error memory 907 to the input pixel data. Here, error data stored in the accumulated error memory 907 and its storage form will be described with reference to FIG. The cumulative error memory 907 has 1 + W storage areas, and the quantization error E0 and E (x) (x = 1 to W) applied to the target pixel are stored in each area. . Note that W is the number of pixels in the horizontal direction in the image data to be processed. The value of the quantization error E (x) is obtained by a method to be described later, but it is assumed that all regions are initialized with an initial value 0 at the beginning of processing. In the accumulated error adding unit 902, the value of the error memory E (x) corresponding to the horizontal position x (0 <x ≦ W) of the pixel is added to the input pixel data. That is, assuming that the pixel data input to the input terminal 901 is I and the pixel data after adding the accumulated error in S1102 is I ′, this addition process is expressed by the following equation.

I '= I + E (x)
In step S1103, the quantization unit 904 compares the pixel data I ′ after addition of the accumulated error with the threshold value input from the threshold setting terminal 903, and performs quantization. In this embodiment, by comparing the pixel data I ′ after the cumulative error addition with eight threshold values, the quantized image data is divided into nine stages, and the value of the output pixel data to be sent to the output terminal 908 is determined. That is, assuming that the value of the pixel data input from the cumulative error adding unit 902 is an integer value in the range of 0 to 255, the output gradation value 0 is determined as follows according to I ′.

(Level 0) O = 0 (I '<16)
(Level 1) O = 32 (16 ≦ I ′ <48)
(Level 2) O = 64 (48 ≦ I ′ <80)
(Level 3) O = 96 (80 ≦ I ′ <112)
(Level 4) O = 128 (112 ≦ I ′ <144)
(Level 5) O = 160 (144 ≦ I ′ <176)
(Level 6) O = 192 (176 ≦ I ′ <208)
(Level 7) O = 224 (208 ≦ I ′ <240)
(Level 8) O = 255 (240 ≦ I ′)
Hereinafter, for convenience of explanation, each of the output gradation values O is referred to as levels 1-8.

  In step S1104, the error calculation unit 905 calculates a quantization error E as a difference between the pixel data I ′ after the cumulative error addition and the output pixel value O as shown in the following equation.

E = I'-O
In step S1105, the error diffusion unit 906 performs error diffusion processing according to the horizontal position x of the target pixel. That is, the quantization error to be stored in the storage areas E0 and E (x) is calculated according to the following equation and stored in the cumulative error memory 907.

E (x + 1) ← E (x + 1) + E × 7/16 (x <W)
E (x-1) ← E (x-1) + E × 3/16 (x> 1)
E (x) ← E0 + E × 5/16 (1 <x <W)
E (x) ← E0 + E × 8/16 (x = 1)
E (x) ← E0 + E × 13/16 (x = W)
E0 ← E × 1/16 (x <W)
E0 ← 0 (x = W)
Thus, the error diffusion process for one pixel input to the input terminal 901 is completed. Then, in S1106, it is determined whether or not each process of S1101 to S1105 has been performed on all pixels of the image. That is, it is determined whether or not the pixel selected by the image scanning unit has reached the final pixel 1002 shown in FIG. 9A. If the pixel has not reached the final pixel 1002, the arrow shown in FIG. The target pixel is advanced by one in the direction, and the process returns to S1101. On the other hand, when it is determined that all pixels have been processed, the quantization process is completed. In the present embodiment, the above quantization process is performed for each color of ink.

  FIG. 11 shows an example of an image having a predetermined gradation value before quantization and an image after quantization. In the figure, 1301 and 1302 indicate images before quantization created for cyan (C) and magenta (M), respectively, and 1303 and 1304 indicate images after quantization. In the C image 1301 before quantization, all the pixel values are uniformly 10, whereas in the C image 1303 after quantization, the pixel 1305 whose output gradation value O is 0 (level 0). And 32 (level 1) pixels 1306 are evenly distributed. Similarly, in the M image 1302 before quantization, the pixel values of all the pixels are 100, whereas in the M image 1304 after quantization, the pixels 1307 and 128 having an output gradation value of 96 (level 3) are displayed. The pixels 1308 at (level 4) are in an evenly distributed state. In either case, all the pixels in the pre-quantization image have the same pixel value, but after quantization, pixels of multiple levels (density) are dispersed. However, the entire image has a data value at the time of input. Is saved.

Print Data Creation Processing Hereinafter, print data creation processing in the print data creation unit 806 will be described. In the print data creation unit 806, the quantized image data is arranged in a predetermined format, and print data to be input to the printer 601 is generated.

  FIG. 12 shows the configuration of print data in the present embodiment. As shown in the figure, the print data is composed of print control information for controlling printing and print image information (also referred to as print image data). Further, the print control information includes “media information” for recording the image, “quality information” for printing, and “other control information” such as a paper feed method. The media information describes the type of paper to be recorded, and any one of plain paper, glossy paper, coated paper, etc. is defined. The quality information describes the quality of printing and defines either high speed printing or high quality printing. The print control information is formed based on the content specified by the user on the PC 602, for example. Furthermore, it is assumed that the image data after quantization described above is described in the print image information. The print data generated as described above is supplied to the printer 601 main body and subjected to dot arrangement patterning processing.

  In the above description, the quantization process and the print data generation process are performed by the printer driver installed in the PC 602 instead of the main body of the printer 601, but the present invention is not limited to this example. For example, even if the quantization process itself is executed in the printer 601, the effect of the present invention can be obtained equally.

● Dot Arrangement Patterning Processing Hereinafter, processing in the dot arrangement patterning processing unit 807 in the printer 601 will be described. In the quantization process described above, the number of levels is reduced from 256-level multi-value density information (8-bit data) to 9-level tone value information (4-bit data). However, information actually required for recording with the ink jet printer 601 of the present embodiment is binary information indicating whether or not to record ink. Therefore, in the present embodiment, in the dot arrangement patterning process, the multilevel print data of 0 to 8 (4 bits) input from the printer driver is reduced to the binary level that determines the presence or absence of dots. Specifically, in the dot arrangement patterning processing unit 807, for each pixel expressed by 4-bit data of levels 0 to 8 quantized by the halftoning unit 805, the gradation value (level 0 to 8) is set. A corresponding dot arrangement pattern is assigned. Thus, dot on / off is defined for each of a plurality of areas in one pixel, and 1-bit ejection data of “1” or “0” is arranged for each area.

  Here, FIG. 13 shows an example of an output pattern for the input level generated by the dot arrangement patterning process. Each level value shown on the left side in the figure indicates levels 0 to 8 of the output gradation output from the halftoning unit 805, and a matrix composed of 2 × 4 horizontal areas is quantized for each level. An area corresponding to the subsequent one pixel is shown. That is, each area in the matrix corresponding to one pixel corresponds to a minimum unit in which dot on / off is defined. In each matrix, circled areas indicate areas where dots are recorded (turned on), and the number of dots to be recorded increases by one as the number of levels increases. In the present embodiment, the density information of the original image is maintained by arranging dots according to the output gradation after quantization in this way. Further, (4n) to (4n + 3) shown on the upper side in the figure indicate pixel positions from the left end in the horizontal direction of the input image by substituting an integer of 1 or more for n. Since the dot pattern based on the matrix differs depending on the pixel position, it can be seen that a plurality of different patterns are prepared depending on the pixel position even at the same input level. That is, even when print data of the same level is input, four types of dot arrangement patterns shown in (4n) to (4n + 3) are circulated and assigned on the recording medium.

  In the dot pattern shown as a matrix in FIG. 13, the vertical direction corresponds to the arrangement direction of the ejection ports of the recording head, and the horizontal direction corresponds to the scanning direction of the recording head. Therefore, as described above, by enabling printing with a plurality of dot arrangements on the same level of print data, the number of ejections is distributed between the nozzles located at the upper and lower positions of the dot arrangement pattern. An effect is obtained. In addition, an effect of dispersing various noises peculiar to the printer 601 can be obtained.

  When the processing in the dot arrangement patterning processing unit 807 is completed, all dot arrangement patterns for the recording medium are determined.

Profile Creation Processing Hereinafter, the color separation profile (LUT822) creation processing referred to in the color separation processing in the subsequent processing unit 803 will be described with reference to the flowchart of FIG. In the present embodiment, this LUT 822 is created by applying specular gloss prediction, and hereinafter, the LUT 822 is simply referred to as a profile. Note that the profile creation process in this embodiment is the PC602.
Are executed by the CPU 702 in accordance with a profile creation program. At that time, the program is read from the ROM 703 or HD 709 and used, and the RAM 704 is used as a work area when executing the processing. Further, the program may be executed by the printer driver in the PC 602, for example.

  First, in S1601, an association process (color prediction process) between ink combinations and colors in the printer 601 is performed. That is, as described above, a combination of ink amount data that can be taken by the six colors C, M, Y, K, Lc, and Lm used in the printer 601 at the time of image formation (hereinafter referred to as output color) is actually A color value reproduced when an image is formed is predicted. Here, as output colors (combinations of ink amount data), for example, if each color has 256 gradation signals in 8-bit representation, there are 256 combinations of the sixth power. As the color prediction, a Neugebauer model or a cell division Yule-Nielsen spectroscopic Neugebauer model that is an extension of the Neugebauer model is used. Alternatively, a well-known technique such as Kubelka-Munk theory or an interpolation technique such as tetrahedral interpolation or cube interpolation from discrete patch measurement values can be applied. In the following, the description will be continued assuming that the printer 601 has six colors of ink, but the present invention is not limited to this example. That is, since the color prediction described above is a model that can cope with changes in the number of colors depending on the number of patches to be output, etc., it is within the scope of the present invention even if the number of colors of ink provided in the printer changes.

  In step S1602, an image signal (a target image signal) extracted as a grid point constituting the profile is input from among the image signals that can be input to the printer 601. In the present embodiment, the image signal input to the printer 601 is described as an RGB signal, but this may be a signal such as CIE L * a * b *, XYZ, or CMYK. The input image signal is stored in the RAM 704 or, if the capacity is large, stored in the HD 709 or the like.

  Next, in S1603, using the relationship between the output color and color predicted in S1601, the ink for realizing the color to be reproduced by the printer 601 according to the color exhibited by the target image signal input in S1602 is obtained. An output color indicating the combination is extracted. Here, the color to be reproduced by the printer 601 in accordance with the color of the image signal of interest is unique by executing color management between the display 712 and the printer 601 with different color gamuts performed in the pre-processing unit 802, for example. To be determined. There are various color management methods such as perceptual color reproduction, vivid color reproduction, and relative / absolute colorimetry, and the color management to be applied can be switched by switching the LUT821 referenced in the pre-processing unit 802. Can do. However, since colors are generally expressed in three dimensions such as CIE L * a * b * and XYZ, even if the colors are uniquely determined, six colors of ink as in this embodiment are used. In this case, there are a plurality of ink combinations (output colors) that can reproduce the color. Therefore, in S1603, for one color corresponding to the image signal of interest, a plurality of output colors that can be reproduced by the printer 601 are extracted from 256 6 combinations. A plurality of output colors as the extraction results are stored in the RAM 704, HD 709, or the like.

  Subsequently, in S1604, a target value (hereinafter referred to as target glossiness) of the specular glossiness of the printed material is set. Here, the specular gloss is a value calculated by the method described in Non-Patent Document 1, as described above. In general, if there is a large change in the specular gloss in one image, color unevenness occurs, leading to image quality degradation. Therefore, the specular gloss is preferably uniform. Therefore, in the present embodiment, the target glossiness is set when creating the color separation profile so that the specular glossiness in the formed image is uniform. In this way, by creating a profile in consideration of the target glossiness, the specular glossiness of the formed image using the profile is made uniform, and the specular glossiness according to the region of the image is also obtained. Can also be set. For example, it is possible to control such that the specular glossiness is high in a bright portion of the image and the specular glossiness is low in a dark portion.

  The target glossiness setting in S1604 is performed, for example, by performing display as shown in FIG. 15 on the display 712 and inputting by the user using the mouse and the keyboard 711 or the like. In the display screen of FIG. 15, when “Glossy arbitrary input” is selected by the user, it is necessary to specify a target glossiness for each input image signal used for profile creation, that is, for each input image signal. Arbitrary specular gloss can be set. On the other hand, if “Glossy constant (target value arbitrary generation)”, “Glossy constant (target value automatic generation)”, or “Gloss control by image brightness” is selected, the value once set as the target glossiness is set to RAM704. Or the like so that it is not displayed in the next loop. When “Glossy constant (automatic target value generation)” is selected, wait for the specular glossiness prediction for each output color in the next step (S1605), and automatically use the prediction result to set the target glossiness. Set. That is, in this case, a value common to each output color is automatically selected from the specular glossiness that can be taken by all the output colors, and this value is stored in the RAM 704, HD709, or the like as the target glossiness.

  Next, in S1605, specular gloss prediction processing, which is a feature of the present embodiment, is performed. Here, the specular gloss prediction process is a process of associating a plurality of output colors with the specular gloss, that is, predicting the specular gloss of the print surface for each of the plurality of output colors extracted in the output color extraction process of S1603. It is processing to do. In this embodiment, in addition to the selective reflection (bronze) of pigment particles in the ink, the influence of unevenness on the surface of the formed image and the coloring of specularly reflected light due to thin film interference resulting from the thin film structure formed by the pigment ink are considered. The specular glossiness is predicted with high accuracy. Details of the specular gloss prediction processing in this embodiment will be described later.

  Next, in S1606, an output color that satisfies the target glossiness set in S1604 is determined based on the predicted value of the specular glossiness corresponding to each output color calculated in S1605, and the determined output color is determined. Store in RAM704, HD709, etc. As an output color that satisfies the target gloss level, for example, an output color whose predicted value is closest to the target gloss level may be used, or the maximum color whose predicted value is equal to or lower than the target gloss level may be used as the output color. good.

  In step S1607, it is determined whether or not the processing in steps S1601 to S1606 has been performed on all grid points of the profile necessary for converting the image signal into the output color. That is, if the output color determination process of S1606 has been performed for all grid points, the process proceeds to the next S1608, but if there is an unprocessed grid point, the process returns to S1601 to start the process for the next grid point. Since the profile in this embodiment is generated in a general format such as ICC, LUT, conversion matrix, etc., here, a sufficient number of image signals and output colors can be associated with each other to create lattice points of the profile. Just do it.

  Finally, in S1608, a profile generation process is performed in which image signals and output colors are associated with all grid points constituting the profile created by a series of processes in S1601 to S1606. That is, a color separation profile (LUT 822) in a general format such as ICC or LUT is generated according to the output color determined for each of the image signals of all grid points.

  As described above, in the present embodiment, the LUT 822 for color separation is created after predicting the specular glossiness of the formed image with high accuracy. Therefore, by referring to the LUT 822 during color separation in the post-processing unit 803, it is possible to control gloss, such as improvement in gloss uniformity in a formed image.

Specular Gloss Prediction Prediction Processing The print surface specular gloss prediction processing for a plurality of output colors in S1605 will be described in detail below.

  In the present embodiment, by considering a dot arrangement pattern as shown in FIG. 13, the ink existing on the uppermost surface of the print and its area ratio (the dot of the ink covers the surface (uppermost surface) within a predetermined region). Area ratio) can be calculated. Therefore, if the refractive index n (λ) of the ink overlapping the surface is known, Fresnel's equation (3), for example, when cyan and magenta are mixed as shown in the following equations (7) to (9): Can be used to predict specular specular reflectance of specular reflection including a bronze component.

ρ _c (θ, λ): Spectral specular reflectance of C ink at incident angle θ n _c (λ): Refractive index of C ink ρ _m (θ, λ): Spectral specular reflectance of M ink at incident angle θ n _m (λ): Refractive index of M ink ρ _cm (θ, λ): Spectral specular reflectance when C and M are mixed at an incident angle θ r _c : Area ratio of C ink on the image surface r _m : M on the image surface In other words, according to the equations (7) and (8), the specular specular reflectances of the respective inks of C and M are obtained based on the Fresnel equation (3) using the refractive indexes acquired in advance. Is calculated. Then, the specular specular reflectivity for the formed image at the time of color mixing is calculated by adding the spectroscopic specular reflectivities of the C and M colors at a rate corresponding to the area ratio of each ink.

  Here, the outline of the specular gloss prediction in the present embodiment will be described using the specular gloss characteristics with respect to the ink discharge amount (gradation) shown in FIG. In this figure, 301 is the same as FIG. 3 (b) described above, and using the refractive index of the color material on the print surface, the equations (7) to (9) based on the Fresnel equation (3), and The characteristic of specular gloss with bronze calculated from the specular gloss calculation formula (6) is shown. Similarly to FIG. 3B, 501 also shows specular gloss characteristics when ink is actually printed on a recording medium and measured with a measuring instrument in accordance with the measurement conditions described in Non-Patent Document 1. As shown in FIG. 16, the actually measured specular gloss characteristic 501 is less than the specular gloss characteristic 301 calculated considering only bronze, and the effects e1 and e2 due to the overlapping of the pigment on the recording medium are reduced. is doing. e1 is the effect of surface irregularities due to the pigment being superimposed on the recording medium, and e2 is the effect of coloring of specularly reflected light due to thin film interference. Note that reference numeral 1801 in FIG. 16 indicates a characteristic obtained when the influence e1 is reflected on the specular gloss characteristic 301 calculated considering only bronze. That is, the measured specular gloss characteristic 501 is obtained by further reflecting the influence e2 on the characteristic 1801.

  Therefore, in the present embodiment, for the specular glossiness of a plurality of patches, the amount of reduction in the actual measurement value with respect to the calculated value by the calculation is the influence amount e1 due to surface unevenness and the influence amount e2 due to coloring of regular reflection light due to thin film interference. To separate. Then, an accurate calculation of the specular gloss is realized by executing a combination of the interpolation calculation for the component that generates the influence component e1 and the interpolation calculation for the component that generates the influence component e2. Therefore, when performing the gloss prediction process of the present embodiment, for a predetermined plurality of patches, first, a gloss model in which the difference between the actual measured value and the calculated value of each specular gloss is separated into the influence component e1 and the influence component e2. It is necessary to perform a gloss model calculation process to be calculated. Thereafter, gloss prediction is performed by performing gloss interpolation processing for calculating the specular gloss of an arbitrary image signal value by interpolation using the gloss model. As a result, in addition to selective reflection (bronze) on the surface of the pigment particles of the ink, the specular gloss of the image surface is highly accurate considering the influence of unevenness of the image surface and coloring of specular reflection light due to thin film interference. Can be predicted.

  FIG. 17 shows details of the specular gloss level prediction processing for a plurality of output colors in S1605. As described above, first, gloss model calculation processing is performed in S2400, and gloss interpolation processing is performed in subsequent S2401 to 2407. For convenience of explanation, in the present embodiment, the gloss model calculation process is described as being performed in S2400 of FIG. 17, but the calculation in the gloss model calculation process of the present embodiment is performed by a plurality of ink values selected in S1603 of FIG. This process does not depend on the combination. Accordingly, the gloss model calculation process is not limited to S2400, and may be executed once at any timing during the entire profile creation process before the gloss interpolation process (S2401 to S2407) described later is started. For example, it is desirable to execute before the loop of S1602 to S1607 in FIG.

  Hereinafter, each of the gloss model calculation process and the gloss interpolation process will be described in detail. In the following description, for the sake of explanation, the description will be continued assuming that arbitrary image signal values are inks of six colors C, M, Y, K, Lc, and Lm.

Gloss Model Calculation Processing The gloss model calculation processing (S2400) of this embodiment will be described below using the flowchart in FIG.

  First, in S1901, spectral reflectances (actually measured values) obtained by measuring the formed images are input for all patches used for gloss prediction. The spectral reflectance value (actually measured value) may be acquired in advance and held in the HD709 or the like, or may be measured in real time.

  Here, the gloss prediction patch is, for example, as shown in FIG. 19A, an 8-bit 256-gradation signal of C, M, Y, K, Lc, and Lm, which are output values of the post-processing unit 803. For example, images of six representative points, each of which is divided into five equal parts, are actually output by the printer 601. In other words, the gloss prediction patch is obtained by actually forming an image formed on the recording medium based on image signals corresponding to a plurality of grid points in a color space reproducible by the printer 601. After that, as shown in FIG. 20, using a measuring device in which the incident angle from the light source and the reflection angle at which the reflected light is measured by the spectral radiance meter are the same as the gloss angle θ to be predicted, Measure reflectivity. The calculation of the spectral reflectance performed here can be performed using black glass or the like as described in Non-Patent Document 1.

  For the sake of explanation, FIG. 19 (a) shows 36 grid points composed of 6 representative points obtained by dividing 256 grayscale signals of 8 bits for C and M into 5 parts as patches for gloss prediction. ing. However, since a 6-dimensional lattice point consisting of C, M, Y, K, Lc, and Lm is actually required, there are 46656 measurement points (patches) that are 6 to the 6th power. Further, the gloss prediction patch (grid point) has been described as having six dimensions C, M, Y, K, Lc, and Lm that are output values of the post-processing unit 803, but the present invention is limited to this example. For example, the grid points may be three-dimensional R, G, and B, which are input values of the post-processing unit 803. In this case, for example, as shown in FIG. 19B, a total of 36 representative points obtained by dividing the R and G 8-bit 256 gradation signals into 5 equal parts may be used as grid points. In this case as well, since it is actually three-dimensional data, there are 216 patches, which are 6 to the third power. 19 (a) and 19 (b) show an example in which 256 gradation signals are equally divided into five to set grid points, but the interval between the grid points is irrespective of whether they are equally divided or unequal. Arbitrary intervals may be used, and the case where lattice points (patches) are formed by representative points of less than 256 gradations is within the scope of the present invention. In the present embodiment, the patch for inputting the measurement value in S1901 is 5 for each of the 8-bit 256 gradation signals of C, M, Y, K, Lc, and Lm, as in the example shown in FIG. The description will be continued assuming that the lattice points are divided.

  The spectral reflectances (actually measured values) of all the gloss prediction patches input in S1901 are stored in the RAM 704, or HD709 is used when the capacity is large.

  In step S1902, an image signal corresponding to one of the spectral reflectances (actually measured values) of the gloss prediction patch input in step S1901 is read as a patch image signal of interest. The image signal referred to here refers to data obtained by dividing each 8-bit 256 gradation signal of C, M, Y, K, Lc, and Lm into five equal parts as described above. Hereinafter, the process proceeds with one of the lattice points shown in FIG. 19A as the target patch image signal. For example, if the target patch image signal is a point Q shown in FIG. 19A, the image signal value here is (C, M, Y, K, Lc, Lm) = (204, 51,0, 0,0,0). The read patch image signal of interest is stored in the RAM 704 for later processing.

  Next, in S1903, the spectral reflectance is calculated using the refractive index of the corresponding ink for the patch image signal of interest read in S1902. The spectral reflectance calculation using the refractive index is performed for the patch image signal of interest (C, M, Y, K, Lc, Lm) = (204,51,0,0,0,0) Will be described. It is assumed that the pigment inks of a plurality of colors used in the present embodiment have known refractive indexes.

  First, by considering the dot arrangement pattern as shown in FIG. 13, the top surface ink processed by the dot arrangement patterning processing unit 807 of the printer 601 and the area ratio of the patch image signal of interest can be known. Next, the spectral reflectance may be calculated as in the above formulas (7) to (9) based on the refractive index of the ink acquired in advance. The spectral reflectance (calculated value) calculated here is shown as 2201 in FIG. 21, for example. The calculated spectral reflectance of the uppermost surface is stored in the RAM 704 for later processing.

  Next, in S1904, a patch formed by the printer 601 based on the target patch image signal (C, M, Y, K, Lc, Lm) = (204, 51,0, 0, 0, 0) in S1902, The spectral reflectance actually measured by the measuring apparatus as shown in FIG. 20 is read. In other words, this process is a process of reading the spectral reflectance (actually measured value) of the patch image signal of interest input in S1901. The spectral reflectance (measured value) read here is shown as 2202 in FIG. 21, for example. As shown in FIG. 21, the measured spectral reflectance 2202 has a lower overall reflectivity than the spectral reflectance calculated 2201 calculated from the refractive index taking into account only the bronze component. In other words, for each of the calculated values 2201 and 2202 of the spectral reflectance, the specular gloss is calculated using the formula (6) that simulates the specular gloss, and the specular gloss is calculated to be lower in the actual value 2202. Is done. This is because, as shown in FIG. 16, the specular gloss characteristic 301 calculated by taking into account only the bronze component using the refractive index of the ink, the measured specular gloss characteristic 501 has an influence e1 or This is consistent with the phenomenon of color effects e2 due to thin film interference. The actually measured spectral reflectance value thus read is stored in the RAM 704 for later processing.

  In step S1905, the difference between the calculated spectral reflectance value 2201 calculated using the ink refractive index in step S1903 and the actual measured spectral reflectance value 2202 read in step S1904 is calculated. The difference calculation performed here is performed by subtracting the measured value 2202 from the calculated value 2201 for each wavelength of the spectral reflectance. FIG. 22 shows the result of the difference calculation. In the figure, 2301 is the difference between the calculated spectral reflectance value 2201 and the actual measurement value 2202, and it can be seen that a difference 2301 greater than or equal to a predetermined value occurs at each wavelength. This difference 2301 is stored in the RAM 704 for later processing.

  Next, in S1906, the difference 2301 between the spectral reflectance calculated value 2201 calculated in S1905 and the actual measured value 2202 is changed into a component caused by surface irregularities (hereinafter referred to as an uneven component), and the color of specularly reflected light by thin film interference Into components (hereinafter referred to as “thin film interference components”). This is because the difference between the calculated value 2201 and the measured value 2202 of the spectral reflectance, that is, the variation in the measured value 2202 from the calculated value 2201 is considered to be composed of the concavo-convex component and the thin film interference component. As this separation method, it is utilized that the uneven component has no wavelength dependency. That is, since the unevenness on the surface has an effect of a constant reflectance at each wavelength, the minimum value of the difference 2301 in the entire wavelength region is set as the unevenness component as shown in FIG. Then, the thin-film interference component at each wavelength is the remaining portion obtained by removing the uneven component from the wavelength difference 2301. The uneven component and the thin film interference component thus divided are associated with the image signal of the patch of interest read in S1902, and each is stored in the RAM 704 or HD709.

  Finally, in S1907, it is determined whether or not the operations in S1902 to S1906 have been performed for the measurement values of all the patches input in S1901. If all the patches have not been processed, the process returns to S1902, and the process for the next patch image signal of interest starts. If a series of processes have been completed for all patches, the gloss model calculation process ends. .

Gloss Interpolation Processing The gloss interpolation processing (S2401 to S2407) of this embodiment will be described below. As described above, the gloss interpolation process of the present embodiment is executed on the assumption that the above-described gloss model creation process (S2400) has been completed.

  First, in S2401, a plurality of output colors for predicting gloss are input. The output color here refers to a combination of a plurality of ink values such as C, M, Y, K, Lc, and Lm selected in S1603 of FIG. As described above, there are a plurality of output colors exhibiting colors represented by three-dimensional values such as X, Y, Z and L * a * b *. Therefore, in S2401, a plurality of ink amount data of combinations of C, M, Y, K, Lc, and Lm exhibiting the same color as the color value exhibited by the target image signal input in S1601 are input as output colors. The input output color is stored in the RAM 704 for later processing, or HD709 is used when the capacity is large.

  In step S2402, one of the plurality of output colors input in step S2401 is selected as a target color (hereinafter referred to as a target output color), and the selected target output color is stored in the RAM 704 for later processing. Is done.

In step S2403, spectroscopic specular reflectance calculation using the refractive index of the pigment ink is performed. First,
The target output color selected in S2402 is processed by the γ correction unit 804, the halftoning unit 805, and the print data creation unit 806 as the output of the post-processing unit 803 shown in FIG. Thereafter, based on the dot arrangement data determined by the dot arrangement patterning processing unit 807, the ink type ejected on the uppermost surface and the area ratio of each ink are calculated. Further, by referring to the refractive index of each pigment ink, the specular specular reflectance of regular reflection for the target output color is calculated as in the above formulas (7) to (9). The calculated specular specular reflectance (calculated value) is stored in the RAM 704 for later processing.

  Next, in S2404, a concavo-convex component prediction process is performed. That is, among the patches for gloss prediction in the gloss model created in S2400, the patches existing around the output color of interest selected in S2402 will be included in the measured spectroscopic specular reflectance. The uneven component is predicted by interpolation. The surface unevenness component for each patch is obtained by the gloss model calculation processing of S2400, and the interpolation calculation is realized by using known techniques such as tetrahedral interpolation, cube interpolation, polynomial interpolation for each wavelength. The The uneven component of the specular specular reflectance calculated here is stored in the RAM 704 for later processing.

  Next, in S2405, thin film interference component prediction processing is performed. That is, similarly to the interpolation calculation in S2404, the thin film interference component that will be included in the measured value of the specular specular reflectance is predicted by the interpolation calculation. The thin-film interference component for each patch is also obtained by the gloss model calculation process described above, and the interpolation calculation is also realized by using known techniques such as tetrahedral interpolation, cube interpolation, polynomial interpolation for each wavelength. . However, it is desirable to use the same interpolation method as in S2404 as the interpolation processing in S2405. The thin film interference component of the specular specular reflectance calculated here is stored in the RAM 704 for later processing.

Next, in S2406, using the specular specular reflectance (calculated value) calculated in S2403 and the unevenness component and thin film interference component of the specular specular reflectance calculated in S2404 and S2405, the gloss prediction for the target output color is performed. Do. Specifically, first, as shown in the following equation (10), the predicted spectroscopic reflectance ρ _est of the spectroscopic specular reflectance is calculated from the three spectroscopic specular reflectance values. According to equation (10), it can be seen that the spectroscopic specular reflectance predicted value can be obtained by removing the concavo-convex component and the thin film interference component from the spectroscopic specular reflectance calculation value.

ρ _est : Spectral specular reflectivity calculated in S2406 ρ _calc : Spectral specular reflectivity (calculated value) calculated in 2403
ρ _Unevenness : Surface unevenness component of specular specular reflectance calculated in S2404 ρ _Interference : Thin film interference component of spectroscopic specular reflectance calculated in S2405 And, further obtained by Equation (10) as shown in Equation (11) Then, the specular specular reflectance prediction value ρ _est is applied to the above equation (6) to calculate the specular gloss prediction value G _est (θ).

G _est : Predicted value of specular gloss calculated in S2406 As described above, the predicted specular gloss value calculated in S2406 is associated with the target output color selected in S2402 and stored in the RAM 704. HD709 is also used when the capacity is large.

  Finally, in S2407, it is determined whether or not the operation of S2402 to S2406 has been performed for all the measured values of the patch input in S2401, and if all output colors have not been processed, the process returns to S2402, and the next The processing for the target output color is started. On the other hand, if a series of processing has been completed for all output colors, the gloss interpolation processing is completed. Note that when the gloss interpolation process ends, the specular gloss level prediction process of S1605 ends.

  In the present embodiment, as described above, the specular glossiness of the image surface is added to the selective reflection (bronze) of the pigment particles, the influence e1 due to the unevenness of the image surface, and the influence e2 due to the coloring of the regular reflection light due to the thin film interference. By taking into consideration, it becomes possible to predict with high accuracy. By the prediction, for example, the specular gloss prediction 301 considering the influences e1 and e2 is further performed on the specular gloss characteristic 301 calculated considering only the bronze component shown in FIG. A characteristic close to the degree characteristic 501 can be calculated.

  As described above, according to the present embodiment, it is possible to predict the specular gloss of the image surface with high accuracy for an image formed by overlapping the pigment ink on the recording medium. By applying this specular gloss prediction when creating a profile for a printer, it is possible not only to improve gloss uniformity in a formed image, but also to be applied to high value-added printing using gloss.

<Other embodiments>
The present invention can also be realized by executing the following processing. That is, software (program) that realizes the functions of the above-described embodiments is supplied to a system or apparatus via a network or various storage media, and a computer (or CPU, MPU, or the like) of the system or apparatus reads the program. It is a process to be executed.

Claims (8)

An image processing apparatus for predicting the specular gloss of a formed image formed by an image forming apparatus that forms an image by superimposing a plurality of color pigment inks on a recording medium,
With respect to the formed image of the target color corresponding to one of the combinations of the respective ink amount data in the plurality of color pigment inks, the refractive index of each pigment ink in the target color and the dot of each pigment ink in the predetermined region Specular reflectance calculation means for calculating the spectroscopic specular reflectance for the formed image using the area ratio covering
Concave and convex component prediction means for predicting the fluctuation of the specular specular reflectance as the concave and convex component due to the concave and convex portions of the image surface formed by overlapping each pigment ink in the target color on the recording medium,
Thin film interference component prediction means for predicting, as a thin film interference component, fluctuations in the specular specular reflectance resulting from coloring of specularly reflected light caused by thin film interference generated by overlapping each pigment ink in the target color on a recording medium; ,
By removing the concavo-convex component and the thin-film interference component from the specular specular reflectance, the spectroscopic specular reflectance for the formed image by the target color is predicted, and the target color is calculated using the predicted specular specular reflectance. A specular gloss calculating means for calculating the specular gloss in the formed image by:
An image processing apparatus comprising:   The specular reflectance calculation means calculates a specular specular reflectance using a refractive index acquired in advance for each of the pigment inks in the target color, and calculates each spectroscopic specular reflectance of the pigment ink. The image processing apparatus according to claim 1, wherein a spectroscopic surface reflectance with respect to a formed image of the target color is calculated by adding at a ratio corresponding to each of the area ratios. Further, for each of the gloss prediction patches formed based on image signals corresponding to a plurality of grid points obtained by dividing the color space reproducible in the image forming apparatus at a predetermined interval, the uneven component and A gloss model creating means for creating a gloss model showing correspondence with the thin film interference component;
2. The unevenness component prediction unit and the thin film interference component prediction unit predict the unevenness component and the thin film interference component for the target color by performing an interpolation process using the gloss model. Or the image processing apparatus of 2. The gloss model creating means includes:
Setting means for setting one of the image signals corresponding to a plurality of grid points on which the gloss prediction patch is formed as a target patch image signal;
A calculation value acquisition means for acquiring a calculated value obtained by calculating a specular specular reflectance using the refractive index of each pigment ink used at the time of image formation based on the target patch image signal for the target patch image signal;
With respect to the target patch image signal, an actual value acquisition means for acquiring an actual measurement value of the specular specular reflectance in an image formed based on the target patch image signal;
Difference calculation means for acquiring a difference between the calculated value and the actual measurement value for the attention patch image signal;
A dividing unit that sets the minimum value in the difference as the unevenness component, and sets the remaining portion from which the unevenness component is removed for each wavelength of the difference as the thin film interference component;
The image processing apparatus according to claim 3, further comprising: Relationship between input image signal and ink amount data of each pigment ink output according to the image signal for an image forming apparatus that forms an image by superimposing a plurality of colors of pigment ink on a recording medium An image processing apparatus for creating a color separation profile to indicate a color separation profile,
Color prediction means for predicting colors reproduced at the time of image formation for output colors corresponding to combinations of ink amount data that can be taken by the plurality of color pigment inks at the time of image formation;
An input means for inputting an image signal corresponding to one of the lattice points constituting the color separation profile as an attention image signal;
Out of the output colors, output color extracting means for extracting a plurality of output colors predicted to reproduce the color reproduced by the target image signal by the color predicting means;
Target gloss setting means for setting a specular gloss to be reproduced in an image formed using the color separation profile as a target gloss;
Glossiness prediction means for predicting the specular glossiness of the formed image by each of the plurality of output colors extracted by the output color extraction means;
Output color determining means for determining an output color indicating a specular glossiness corresponding to the target glossiness among a plurality of specular glossinesses predicted by the glossiness prediction means as an output color corresponding to the target image signal; ,
After the grid points constituting the color separation profile are processed by the input unit and the output color extraction unit, the target gloss level setting unit, the gloss level prediction unit, and the output color determination unit, Profile generation means for generating the color separation profile so as to show the relationship between the image signal for each of the grid points and the output color determined by the output color determination means for the image signal;
An image processing apparatus comprising: The gloss prediction means includes
With respect to the formed image of the target color corresponding to one of the combinations of the respective ink amount data in the plurality of color pigment inks, the refractive index of each pigment ink in the target color and the dot of each pigment ink in the predetermined region Specular reflectance calculation means for calculating the spectroscopic specular reflectance for the formed image using the area ratio covering
Concave and convex component prediction means for predicting the fluctuation of the specular specular reflectance as the concave and convex component due to the concave and convex portions of the image surface formed by overlapping each pigment ink in the target color on the recording medium,
Thin film interference component prediction means for predicting, as a thin film interference component, fluctuations in the specular specular reflectance resulting from coloring of specularly reflected light caused by thin film interference generated by overlapping each pigment ink in the target color on a recording medium; ,
By removing the concavo-convex component and the thin-film interference component from the specular specular reflectance, the spectroscopic specular reflectance for the formed image by the target color is predicted, and the target color is calculated using the predicted specular specular reflectance. A specular gloss calculating means for calculating the specular gloss in the formed image by:
The image processing apparatus according to claim 5, further comprising: Formed by an image forming apparatus having a specular reflectance calculation means, a concavo-convex component prediction means, a thin film interference component prediction means, and a specular gloss calculation means, and forms an image by superimposing a plurality of colors of pigment ink on a recording medium An image processing method in an image processing apparatus for predicting the specular gloss of a formed image,
The specular reflectance calculating means has a refractive index of each pigment ink in the target color and a predetermined area for a formed image with the target color corresponding to one of the combinations of the ink amount data in the plurality of pigment inks. A specular reflectance calculating step for calculating a specular specular reflectance for the formed image using the area ratio of the dot of each pigment ink covering the surface;
The concavo-convex component predicting unit predicts, as the concavo-convex component, the amount of fluctuation in the specular specular reflectance resulting from the concavo-convex of the image surface formed by overlapping each pigment ink in the target color on the recording medium. Steps,
The thin-film interference component prediction means uses the fluctuation amount of the specular specular reflectance due to coloring of specular reflection light caused by thin-film interference generated when each pigment ink in the target color overlaps the recording medium as a thin-film interference component. A thin film interference component prediction step to predict;
The specular gloss calculation means predicts the specular specular reflectance for the formed image of the target color by removing the unevenness component and the thin film interference component from the specular specular reflectance, and the predicted specular specular reflection A specular gloss calculation step of calculating a specular gloss in the formed image of the target color using a rate;
An image processing method comprising:   A program for causing a computer to function as each unit of the image processing apparatus according to any one of claims 1 to 6 when executed by the computer.

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