JP5011703B2 - Image processing apparatus, image processing method, program, and storage medium - Google Patents

Description

  The present invention relates to a technique for correcting density unevenness in an apparatus that outputs a dot matrix.

  An image forming apparatus having a droplet discharge mechanism, such as an ink jet printer, has a plurality of nozzles that discharge ink in order to increase printing speed. Here, ideally, it is desirable that all the nozzles are arranged in a line at a uniform interval. However, in reality, there is a certain variation in the nozzle interval due to a problem in manufacturing technology. Also, there may be variations in the amount of ink ejected from the nozzles. When printing is performed using such a print head, the ink ejected from the head varies in landing positions and sizes due to variations in nozzle spacing. That is, the image (dot) formed on the paper reflects the nozzle variation. In particular, in a one-pass type image forming apparatus only in the paper feeding direction such as a line head type ink jet printer, such nozzle variation causes a so-called banding phenomenon.

As a technique for suppressing the banding phenomenon caused by the nozzle variation, there is a technique for compensating the nozzle variation by image processing (see, for example, Patent Documents 1 to 3). Patent Document 1 discloses a technique for compensating for uneven printing density due to nozzle variation using a correction table. That is, the correction coefficient obtained based on the print density when printing a so-called solid pattern is stored in the image forming apparatus in advance, and density unevenness is corrected by multiplying the gradation value of the pixel by the correction coefficient during printing. Is. Patent Document 2 discloses a technique for correcting gradation characteristics in a straight line in addition to the technique described in Patent Document 1. Patent Document 3 discloses a technique for correcting density unevenness using a plurality of correction tables.
Japanese Patent Laid-Open No. 1-129667 Japanese Patent Laid-Open No. 3-162977 Japanese Patent Laid-Open No. 5-57965

  However, all of the correction tables described in Patent Documents 1 to 3 focus only on the characteristics of the nozzles to be corrected, and do not consider the influence of adjacent nozzles. Therefore, there is a problem in that accurate density correction cannot be performed due to the influence of adjacent nozzles, and the image quality of the printed image is deteriorated. Here, the influence of adjacent nozzles refers to a problem as described below.

  FIG. 26 is a diagram for explaining the influence of adjacent nozzles when a correction table is created. FIG. 26 shows two dots (dots 2401 and 2402) formed on a sheet (recording material) by two adjacent nozzles (nozzles 2403 and 2404). For example, it is assumed that the dots 2401 and 2402 are dots formed by output data having a gradation value of 120, and the density of the dot 2401 is measured as 110 and the density of the dot 2402 is measured as 130 before correction. In this case, the dot 2401 is corrected so as to have a density of 120 (so that it becomes dark), and the dot 2402 is corrected so as to have a density of 120 (so that it becomes light). However, the fact that the density of the dot 2401 is measured as 110 is influenced by the fact that “the density of the dot 2402 is 130”. In FIG. 26, the dot 2402 overlaps with a part of the dots 2401, and the density of the dot 2401 is measured as 110 due to this overlap. However, the amount of ink actually ejected from the nozzle 2403 is smaller than the amount corresponding to the density 110. For this reason, even if correction is performed to set the density 110 to 120, the density of the dots 2401 is not intended. This is because the influence of adjacent nozzles is not taken into account, and attention is paid only to the characteristics of a single nozzle to be corrected. In addition to this, an error in the mounting position of the nozzles can also affect adjacent nozzles.

  The present invention has been made in view of the above circumstances, and provides an image processing technique capable of performing correction in consideration of the influence of pixels other than a pixel to be corrected, such as a pixel formed by an adjacent nozzle. With the goal.

In order to solve the above-described problem, the present invention provides an input pixel value of a self-pixel to be corrected among a plurality of pixels constituting input image data including an input pixel value for each pixel, and a reference adjacent to the self-pixel. Table storage means for storing a density correction table in which an input pixel value of a pixel and an output pixel value of the own pixel are associated; a density correction table stored in the table storage means; and an input pixel value of the own pixel; When the input pixel value of the reference pixel is given to the image data using the density correction table for the required output pixel value calculation means for calculating the required output pixel value of the own pixel based on Image correction means for performing correction processing for determining a correction value of the own pixel so that the required output pixel value of the own pixel and the output pixel value of the own pixel are equal, and the image corrected by the image correction means Data output means for outputting data to an image forming means having a plurality of pixel output means for forming an image according to the corrected pixel value, and the density correction table is predetermined for the own pixel and the reference pixel. An image processing apparatus characterized by being created using a density in an intermediate region between the own pixel and the reference pixel, which is measured from a result of outputting the obtained test pattern.
According to this image processing apparatus, the pixel value is corrected based on the input pixel values of the own pixel and the reference pixel. That is, it is possible to perform correction in consideration of the influence of pixels other than the pixel to be corrected.

  In a preferred aspect, in the image processing apparatus, the pixel output unit may include a plurality of nozzles that eject ink. According to the image processing apparatus of this aspect, it is possible to perform correction in consideration of the influence of pixels other than the pixel to be corrected on the image output from the image output unit that discharges ink from a plurality of nozzles.

  In another preferred embodiment, in the image processing apparatus, the pixel output unit may include a display device that generates visible light. According to the image processing apparatus of this aspect, it is possible to perform correction in consideration of the influence of pixels other than the pixel to be corrected on the image output from the image output unit having a display device that generates visible light.

  In still another preferred embodiment, in the image processing apparatus, the table storage unit stores at least two density correction tables, and the own pixel and the reference pixel in one density correction table of the at least two density correction tables are stored. The connecting straight line and the straight line connecting the own pixel and the reference pixel in another density correction table may be orthogonal to each other. According to the image processing apparatus of this aspect, it is possible to perform correction in consideration of reference pixels in two directions.

Further, the present invention provides an input pixel value of a self pixel to be corrected among a plurality of pixels constituting input image data including an input pixel value for each pixel, and an input pixel value of a reference pixel adjacent to the self pixel. Based on the reading step of reading out the density correction table from the table storage means storing the density correction table in which the output pixel value of the own pixel is associated, and the input pixel value of the density correction table and the own pixel A required output pixel value calculating step of calculating a required output pixel value of the own pixel, and the required output pixel value of the own pixel and an output pixel value of the own pixel using the density correction table for the image data An image correction step for performing a correction process for determining a correction value of the own pixel so as to be equal to each other, and image data corrected in the image correction step And a data output step for outputting to the image forming means having a plurality of pixel output means for performing image formation according to the above, wherein the density correction table outputs a predetermined test pattern to the own pixel and the reference pixel. An image processing method characterized by being created using a density in an intermediate region between the self pixel and the reference pixel measured from the result.
Furthermore, the present invention provides a program for causing a computer device to execute the above-described image processing method, and a storage medium storing the program.
According to the image processing method, the program, and the storage medium, the pixel value is corrected based on the input pixel values of the own pixel and the reference pixel. That is, it is possible to perform correction in consideration of the influence of pixels other than the pixel to be corrected.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
<1. First Embodiment>
<1-1. Image forming system>
FIG. 1 is a block diagram showing a functional configuration of an image forming system 1 according to the first embodiment of the present invention. The image forming system 1 includes an image forming apparatus 200 and a PC (Personal Computer) 100. The image forming apparatus 200 is an apparatus that forms an image on a sheet (recording material) by ejecting ink according to control data. The PC 100 is a computer device that controls the image forming apparatus 200. The PC 100 includes an application 108 such as a word processor and image processing software, and a device driver 109 for controlling the image forming apparatus 200. The application 108 delivers the image data to the device driver 109 in response to a user instruction input or the like. The device driver 109 controls the image data to be processed (RGB (red, green, blue) color multi-value) for injecting ink from the nozzles for each color of CMYK (cyan, magenta, yellow, black). And having the function of outputting the control data to the image forming apparatus 200.

  The device driver 109 has the following functions in detail. The resolution conversion unit 101 converts the input color multivalued image data into a resolution that can be processed by the image forming apparatus 200. The color space conversion unit 102 converts image data in RGB format into image data in CMYK format. The density correction unit 103 performs density correction processing on the image data using the density correction table TB1. Here, the density correction table TB1 is obtained by reading the density correction table TB1 stored in the image forming apparatus 200 and storing it in the PC 100. Details of the density correction table TB1 will be described later. The quantization unit 104 performs a binarization process for converting the multivalued CMYK data into binary CMYK data. The rasterizing unit 105 generates control data from the binary CMYK data. The image forming unit 250 of the image forming apparatus 200 ejects CMYK inks according to the control data. Thus, the image forming system 1 forms an image on a sheet (recording material).

  FIG. 2 is a block diagram illustrating a hardware configuration of the image forming apparatus 200. In the present embodiment, the image forming apparatus 200 is a line head type ink jet printer. A CPU (Central Processing Unit) 210 reads and executes a print processing program stored in a ROM (Read Only Memory) 220. The ROM 220 stores a density correction table TB1 unique to the image forming apparatus 200 (details of the density correction table TB1 will be described later). The ROM 220 is preferably a rewritable EEPROM (Electronically Erasable and Programmable Read Only Memory). A RAM (Random Access Memory) 230 functions as a work area when the CPU 210 executes a program. The I / F 240 is an interface for transmitting and receiving data and control signals to and from other devices such as the PC 100. The RAM 230 also stores data received via the I / F 240. The image forming unit 250 forms an image on a sheet according to the nozzle control data under the control of the CPU 210. The above components are connected to each other via a bus 290. When the CPU 210 executes the application 108 and the device driver 109, the image forming apparatus 200 has functions corresponding to the functional components shown in FIG.

  As illustrated in FIG. 2, the image forming unit 250 further has a configuration described below. The line head 251 is a print head having a plurality (z) of nozzles (not shown) that eject ink. The nozzle may be of any structure, such as a piezo type that discharges droplets with a piezoelectric body, or a heating type that discharges by heating. The line head 251 has a size that is equal to or larger than the maximum width of paper that can be printed by the image forming apparatus 200. The ink tank 252 supplies ink to the nozzles, and is provided for each color of CMYK. In this embodiment, the image forming apparatus 200 forms an image using four colors of ink. However, the image forming apparatus 200 may be configured to use six colors, seven colors, or more colors. The page buffer 257 is a memory that stores nozzle control data for one page of an image. The head drive circuit 253 outputs, to the line head 251, a control signal for causing ink droplets to be ejected from a specified nozzle among a plurality of nozzles mounted on the line head 251 under the control of the control unit 254. . In this way, ink droplets are ejected from the designated nozzle onto the paper. The ink droplets ejected from the nozzles form dots on the paper. Hereinafter, for convenience of description, discharging ink droplets from the nozzles is expressed as “dots on” and not discharging ink droplets from the nozzles as “dots off”. For example, “data for designating ON / OFF of dots” means data for designating whether or not to eject ink droplets for a designated nozzle. “Dot” means an ink droplet ejected from a nozzle or an image formed on the paper by the ink droplet.

  Since the line head 251 has a size equal to or larger than the paper width, dots for one line can be formed. The motor 255 is a motor that moves the paper in a predetermined direction (paper feed). The motor drive circuit 256 outputs a drive signal to the motor 255 under the control of the control unit 254. When the motor 255 moves the paper by one line, the next line is drawn. In this way, the image forming apparatus 200 can form an image on one sheet only by scanning in one direction (paper feeding).

  FIG. 3 is a block diagram illustrating a hardware configuration of the PC 100. The CPU 110 is a control unit that controls each component of the PC 100. The CPU 110 reads and executes a control data generation program (device driver) stored in an HDD (Hard Disk Drive) 150. The RAM 130 functions as a work area when the CPU 110 executes a program. The ROM 120 stores a program and the like necessary for starting up the PC 100. The I / F 140 is an interface for transmitting and receiving data and control signals to and from other devices such as the image forming apparatus 200. The HDD 150 is a storage device that stores various data and programs. The HDD 150 stores a density correction table TB1 read from the image forming apparatus 200. The keyboard 160 and the display 170 are user interfaces for the user to perform operation input to the PC 100. The above components are connected to each other by a bus 190. When the CPU 210 executes the print processing program, the PC 100 has functions corresponding to the functional components shown in FIG. Although not shown, the PC 100 and the image forming apparatus 200 are connected to each other via a wired or wireless connection via the I / F 140 and the I / F 240.

  FIG. 4 is a flowchart showing the operation of the image forming system 1. When a power supply (not shown) of the image forming apparatus 200 is turned on, the CPU 210 reads a print processing program from the ROM 220 and executes it. When the print processing program is executed, the CPU 210 waits for input of control data. In the PC 100, when a print instruction is input from the application 108, the CPU 110 reads the device driver 109 of the image forming apparatus 200 from the HDD 150 and executes it. First, the CPU 110 reads out image data to be processed from the HDD 150 and stores it in the RAM 130 (step S100). In the present embodiment, the input image data is RGB color multivalued image data. The image forming apparatus 200 is an ink jet printer that forms an image with CMYK four color inks. Therefore, the image forming apparatus 200 needs to convert the color space of the image data from RGB to CMYK. The input image data has a gradation value for each pixel, but the ink ejected from the nozzles of the image forming apparatus 200 is dot on / off (dot hitting / shotting) for a dot of a certain size. The intermediate gradation cannot be expressed with only two gradations. Also, there are three types of dot sizes S, M, and L that can be formed by the image forming apparatus 200. Therefore, in the image forming apparatus 200, one pixel of input image data is associated with a dot matrix of a dot × a dot, and gradation expression is performed by the number of dots drawn in the dot matrix. Therefore, it is necessary to convert the input image data into data that designates dot on / off. For this purpose, as described below, the processing for converting the resolution of the image data into a resolution corresponding to the number of nozzles, and the two-gradation designating the on / off of the dots in the multi-gradation image data It is necessary to convert it to data. The dot sizes that can be formed by the image forming apparatus 200 are not limited to three types, and may be larger or smaller.

  Subsequently, the CPU 110 determines the resolution of the input image data. If the resolution of the input image data is different from the resolution that can be processed by the image forming apparatus 200, the CPU 110 performs a resolution conversion process that converts the input image data to a resolution that can be processed by the image forming apparatus 200 (step S110). The CPU 110 stores the image data after resolution conversion in the RAM 130. Subsequently, the CPU 110 converts the RGB format image data into the CMYK format image data in order to adapt the resolution-converted image data to the color space of the image forming apparatus 200 (step S120). The CPU 110 stores the color-converted image data in the RAM 130. Subsequently, the CPU 110 performs density correction processing on the image data after color conversion (step S130). Details of the density correction processing will be described later.

  Subsequently, the CPU 110 performs binarization (quantization) processing on the image data after density correction by a dither matrix method, an error diffusion method, or the like (step S140). The CPU 110 stores the image data after density correction in the RAM 130. The CPU 21 performs a rasterization process for generating control data from the image data after density correction (step S150). CPU 110 outputs the generated control data to image forming apparatus 200. The image forming unit 250 of the image forming apparatus 200 forms an image on a sheet according to the control data. The image forming apparatus 200 forms an image whose density has been corrected in this way on a sheet.

<1-2. Generation of density correction table>
Next, a method for generating the density correction table TB1 will be described. Here, black ink (K) will be described as an example, but a density correction table is created for each color. The density correction table includes the pixel value (luminance) of the target nozzle to be corrected, the pixel value (luminance) of the reference nozzle that is referred to when correcting the own nozzle, and the output pixel value (output) that is actually output. Luminance or density data) in association with each other. In the present embodiment, an adjacent nozzle adjacent to its own nozzle is employed as the reference nozzle.

  FIG. 5 is a block diagram showing a functional configuration of the density correction table generation system 2 according to the present embodiment. The density correction table generation system 2 includes an image forming apparatus 200, a PC 300, and a scanner 400. Although not shown, the PC 300 and the image forming apparatus 200, and the PC 300 and the scanner 400 are connected by wire or wirelessly. The PC 300 stores a test pattern 301 for generating a density correction table. The image forming unit 250 of the image forming apparatus 200 outputs the image D according to the test pattern 301. The scanner 400 reads the image D and generates a scanned image. The scanner 400 outputs the generated scan image to the PC 300. The PC 300 stores the received scan image as the scan image 304. The density measurement unit 303 of the PC 300 calculates the density of the scan image 304 output from the scanner 400. The density correction table generation unit 302 generates a density correction table based on the density measurement result by the density measurement unit 303. The image forming apparatus 200 stores the density correction table generated by the PC 300 as the density correction table TB1.

  FIG. 6 is a diagram illustrating a hardware configuration of the PC 300. Since the hardware configuration of the PC 300 is basically the same as that of the PC 100, a detailed description thereof will be omitted, and only differences from the PC 100 will be described. The HDD 350 stores a test pattern 301 for generating a density correction table. The HDD 350 stores a density correction table generation program for generating a density correction table.

  FIG. 7 is a flowchart showing an outline of the density correction table generation process. When the user instructs generation of a test pattern by a method such as operating the keyboard 360, the CPU 310 of the PC 300 reads out the density correction table generation program from the HDD 350 and executes it. First, the CPU 310 generates a test pattern (step S200). That is, the CPU 310 reads the test pattern 301 from the HDD 350. The CPU 310 outputs the read test pattern 301 data to the image forming apparatus 200 via the I / F 340.

  FIG. 8 and FIG. 9 are diagrams illustrating a test pattern 301 (part). FIG. 8 shows a basic pattern of test patterns output from eight nozzles (sequentially written as nozzles # 00 to # 07). The nozzles are arranged in the vertical direction in the figure, and the horizontal direction in the figure is the paper feed direction. The present invention sets the correction value so that the output pixel value of the own pixel becomes equal to the requested output pixel from the pixel value (luminance) of the own pixel to be corrected and the pixel value of the reference pixel that is a pixel other than the own pixel. It is about how to decide. Here, in the present embodiment, a mode in which the reference pixel is a pixel formed by a nozzle adjacent to the nozzle that forms the self pixel will be described. The test pattern 301 is a test pattern for generating a density correction table for performing such correction processing.

  In the basic pattern shown in FIG. 8, the four nozzles # 00, # 02, # 04, and # 06 have a pattern having a single luminance (luminance 0 in the example of FIG. 8). Note that the luminance means the brightness of the pixel. The point indicating the output value of the pixel is synonymous with gradation, but when the luminance is the maximum value, the gradation has the minimum value, and when the luminance is the minimum value, the gradation has the maximum value. For the four nozzles # 01, # 03, # 05, and # 07, a combination of a plurality of different luminance patterns such as luminance 0, 51, 102, 153, 204, and 255 in order from the left in the figure. It has become. In FIG. 8, when nozzle # 01 is a correction target nozzle (hereinafter referred to as “self nozzle”), a nozzle adjacent to the self nozzle (hereinafter referred to as “adjacent nozzle”) is nozzle # 00. That is, as shown in FIG. 8, the basic pattern is composed of a pattern formed by adjacent nozzles fixed at a certain luminance and a pattern formed by own nozzles changed to a plurality of luminances.

FIGS. 9A to 9F are diagrams showing six basic patterns used in the present embodiment. The basic pattern shown in FIG. 9A is the same as the basic pattern shown in FIG. 9A to 9F, the brightness of adjacent nozzles is different. That is, in the basic patterns of FIGS. 9A to 9F, the luminances of the adjacent nozzles are 0, 51, 102, 153, 204, and 255, respectively. That is, by using the six basic patterns shown in FIGS. 9A to 9F, correction data can be created for 36 combinations of the own nozzle 6 gradations × adjacent nozzle 6 gradations. That is, in order to create correction data for c ^two combinations of the own nozzle c gradation × adjacent nozzle c gradation, c basic patterns are required.

  8 and 9, the minimum unit of an area output with a certain luminance is referred to as a “unit pattern”. For example, in the basic pattern of FIG. 8, the nozzle # 01 pattern is composed of six unit patterns.

  FIG. 10 is a diagram for explaining gradation expression in a unit pattern. FIG. 10A shows the dot size that can be formed by one nozzle of the image forming apparatus 200. The image forming apparatus 200 can divide dots of three sizes, S size (density 40%), M size (density 70%), and L size (density 100%). FIG. 10B shows a unit pattern corresponding to a density of 0%, 20%, 40%, 60%, 80%, 100% (in the case of 256 gradations, luminance 255, 204, 153, 102, 51, 0). Shows a method of performing gradation expression. As shown in FIG. 10B, the unit pattern is composed of six dots. When gradation expression of 0% density is performed, no dot is formed on any dot. When expressing gradation with a density of 20%, dots of S size (density 40%) are formed every other dot. The average of 6 dots gives a density of 20%. When a gradation of 40% density is expressed, M size dots are formed for all dots. Similarly, for each gradation, dots are arranged so as to obtain a desired density when averaged over the unit pattern.

  In the above description, the size of the unit pattern is described as 6 dots, but the size of the unit pattern is not limited to this. For example, the measurement accuracy may be improved by setting the size of the unit pattern to 50 dots. In addition, it may be determined by binarization processing at which position in the unit pattern the dot is to be hit.

  The description will be given with reference to FIGS. 5 and 7 again. When the test pattern 301 data is received, the image forming apparatus 200 prints the test pattern on the sheet according to the received data (step S210). Since this test pattern is for generating a density correction table, the density correction processing is not performed when the test pattern is printed. Therefore, the test pattern is printed in a state including printing unevenness due to the physical characteristics of the nozzles.

  Subsequently, the scanner 400 reads the image D of the printed test pattern (Step S220). In order to measure the luminance value for each nozzle in the subsequent processing, reading is performed at a resolution higher than the printing resolution when reading the image. For example, when printing is performed at a resolution of 720 dpi (dot per inch), reading is performed at a resolution of 2880 dpi. In this case, four points of density data can be acquired for one printing dot. The scanner 400 outputs the read image D data to the PC 300. The CPU 310 of the PC 300 stores the input image data as a scan image 304 in the HDD 350.

  Subsequently, the CPU 310 associates density data in the scanned image 304 with each nozzle. There are several methods for associating density data with nozzles. In this embodiment, the CPU 310 associates density data of “between nozzles” with each nozzle. In the following description, an area for associating density data with a nozzle is referred to as a “unit area”.

  FIG. 11 is a diagram illustrating the definition of density data between nozzles. The example of FIG. 11 shows a pattern in which dots having ideal sizes are formed at ideal positions. The density between “nozzles” means the density between the centers of two adjacent dots with respect to the ideal dot formation position. In other words, if the midpoint of the line segment connecting the centers of two adjacent dots is defined as the boundary point between two adjacent dots, the “inter-nozzle” density is the center of the dot, that is, the boundary point. The density in a region having a length equal to the ideal dot pitch is expressed as follows.

  As another method for associating density data with nozzles, there is a method using density for each nozzle. The “between nozzles” density means a density between two adjacent boundary points. The density correction table generated using the density data for each nozzle has the following problems. In the test patterns illustrated in FIGS. 8 and 9, the luminance of two nozzles adjacent to a certain nozzle is the same. For example, the brightness of nozzle # 00 and nozzle # 02 adjacent to nozzle # 01 is the same. Therefore, when correction is performed using the density correction table generated using the density data for each nozzle, if both adjacent nozzles have the same input luminance, the correction data is reliable. If the input luminance is different, the reliability is not compensated. For example, let us consider a case where a flight curve occurs in nozzle # 02. In this case, the dots formed by the nozzle # 01 are greatly affected by the dots formed by the nozzle # 02, but are hardly affected by the dots formed by the nozzle # 00. At this time, there are many cases where the correction values are different between the case where correction processing is performed in ascending order of the nozzle numbers, that is, from the nozzle # 00, and the case where correction processing is performed from the lowest nozzle numbers, ie, from the nozzle # 02. As described above, when the density correction table generated using the density data for each nozzle is used, there is a problem that the correction value may not be calculated accurately.

  On the other hand, if a density correction table generated using density data between nozzles is used, the correction value can be accurately calculated because the nozzle and the correction data can be uniquely associated. In addition, since banding caused by flight bending occurs between nozzles, a density correction table generated using density data between nozzles that can accurately calculate and correct the luminance between nozzles is useful.

  FIG. 12 is a diagram illustrating unit areas. For example, the area between the nozzles in the density data is specified as follows. The CPU 310 identifies the position corresponding to the data whose density is below a predetermined threshold as the end of the test pattern. In this way, the CPU 310 specifies data corresponding to, for example, the left corner of the test pattern. The CPU 310 leaves two margins from the specified left corner, and uses the density data corresponding to the pixel (nozzle) at the left corner of the test pattern, that is, the density data corresponding to the vertical corner 4 pixels × 4 horizontal points = 16 points, ie, the unit area Specify as concentration data. The same applies to the other nozzles.

  Subsequently, the CPU 310 generates a density correction table based on the scanned image 304 (step S230). Here, first, the details of the density correction table generation processing will be described using nozzle # 01 and nozzle # 02 of FIG. In FIG. 8, the area indicated by the dotted line is the printing range of nozzle # 01. The CPU 310 calculates the average brightness of the unit area from the scanned image 304. In the following description, the luminance of the coordinates (x, y) in the scanned image 304 is expressed as C (x, y). The positive direction of x is the right direction in FIG. 8, and the positive direction of y is the downward direction in FIG.

The coordinates of the upper left corner of the unit area and _{(x 1 + 2, y 1} +2). Here, the size of the unit area is equal to the size of the unit pattern described above. As described above, the unit pattern is composed of dots of 1 vertical dot × 6 horizontal dots. In this embodiment, reading is performed at a resolution four times the printing resolution (vertical 4 points × horizontal 4 points per dot). Therefore, the unit area is read at a pitch of 4 vertical points × 24 horizontal points. That is, the coordinates of the unit areas the lower-left corner _{(x 1 + 2, y 1} + 6), the coordinates of the upper-right corner _{(x 1 + 22, y 1} +2), the lower right corner coordinates _{(x 1 + 22, y 1} + 6 ). The average density P is calculated by the following formula (1).
P = ΣC (x, y) / m _D (1)
Here, m _D indicates the number of density data included in the unit area (4 × 24 = 96 in the present embodiment). Further, in the present embodiment because it is _{x = x 1 + 2~x 1 +} 22, y = y 1 + 2~y 1 + 6, in the range C (x, y) is summed.

  FIG. 13 is a diagram illustrating a method for generating a density correction table for nozzle # 01. Here, the density correction table for nozzle # 01 is a density correction table in which the correction target nozzle is the nozzle # 01 and the adjacent nozzle that is the reference nozzle is nozzle # 00. Therefore, the density correction table is obtained from the density measured in each unit region between nozzle # 00 and nozzle # 01. Hereinafter, unless otherwise described, the density correction table for nozzle #N is defined as that obtained from the unit area between nozzle #N and nozzle # N−1. Therefore, in this case, the own nozzle is nozzle #N, and the adjacent nozzle is nozzle # N-1.

  The basic patterns shown in FIGS. 13A and 13B are the same as the basic patterns shown in FIGS. 9A and 9B. That is, FIG. 13A shows a basic pattern in which the adjacent nozzle luminance is 0, and FIG. 13B shows a basic pattern in which the adjacent nozzle luminance is 51. First, the CPU 310 calculates the average brightness P of each unit region when the adjacent nozzle brightness is 0 (FIG. 13A). In the present embodiment, the average brightness is calculated to be 23, 33, 40, 66, 76, 120 for the unit areas of the own nozzle input brightness 0, 51, 102, 153, 204, 255. Next, the CPU 310 calculates the average luminance P of each unit region when the adjacent nozzle luminance is 51 (FIG. 13B). In the present embodiment, the average luminance is calculated to be 31, 38, 54, 79, 97, 132 for each unit region. In the same manner, the average brightness of each unit region is calculated for the basic patterns with adjacent nozzle brightnesses 102, 153, 204, and 255. The CPU 310 stores the calculated average brightness in the RAM 330.

  FIG. 14 is a diagram illustrating a method for generating the density correction table for nozzle # 02. The basic patterns shown in FIGS. 14 (a) and 14 (b) are also the same as the basic patterns shown in FIGS. 9 (a) and 9 (b). First, the CPU 310 calculates the average luminance P of each unit region when the adjacent nozzle luminance is 0 (FIG. 14A). It should be noted that the nozzles # 02, # 04, and # 06 have a relationship in which the brightness of the own nozzle is fixed and the brightness of the adjacent nozzles changes. That is, in the example of FIG. 9, the odd-numbered nozzle has a fixed brightness of the adjacent nozzle and the brightness of the own nozzle changes, but the even-numbered nozzle has a fixed brightness of the own nozzle and the brightness of the adjacent nozzle changes. It has become. First, the CPU 310 calculates the average luminance P of each unit region when the own nozzle luminance is 0 (FIG. 14A). In the present embodiment, the average luminance is calculated to be 19, 26, 29, 41, 55, 77 for the unit area where the input luminance of the adjacent nozzles is 0, 51, 102, 153, 204, 255. The Next, the CPU 310 calculates the average luminance P of each unit area when the own nozzle luminance is 51 (FIG. 14B). In the present embodiment, the average luminance is calculated to be 25, 31, 40, 56, 74, and 97 for each unit region. In the same manner, the average brightness of each unit area is calculated for the basic patterns having the own nozzle brightness of 102, 153, 204, and 255. The CPU 310 stores the calculated average brightness in the RAM 330.

  Since nozzle # 00 is a nozzle located at the end, that is, there is no adjacent nozzle, the density correction table is created by a method different from the method for other nozzles. Since nozzle # 00 has no adjacent nozzle, it is not necessary to consider the influence of the adjacent nozzle. Therefore, the density data of all nozzles is averaged for each field of the density correction table, and a table (average table) storing the calculated average value is used as the density correction table for nozzle # 00. Thereby, it becomes possible to perform the correction process according to the tendency of other nozzles.

  The CPU 310 calculates the average luminance P of each unit area for all the nozzles # 00 to # 07 in the same manner as described above, and stores it in the RAM 330. The CPU 310 combines the average luminances stored in the RAM 330 and generates a density correction table. The CPU 310 stores the generated density correction table in the RAM 330 as a density correction table TB1. The CPU 310 transmits a table update request for requesting an update of the density correction table and the density correction table TB1 to the image forming apparatus 200. When receiving the table update request, the CPU 210 of the image forming apparatus 200 stores the received density correction table TB1 in the ROM 220. In this way, the image forming apparatus 200 stores the density correction table TB1 for correcting density unevenness peculiar to its own nozzle.

  FIG. 15 is a diagram illustrating the density correction table TB1 created by the method described above for the three nozzles # 00 to # 02. The density correction table TB1 includes a density correction table for each nozzle. That is, when there are eight nozzles # 00 to # 07, the density correction table TB1 includes eight density correction tables. Here, the horizontal direction of the table indicates the input luminance of the own nozzle, and the vertical direction indicates the input luminance of the adjacent nozzle. The value of the intersection of the own nozzle and the adjacent nozzle indicates the output luminance (average luminance). For example, for nozzle # 00, if the input luminance of the own nozzle is 51 and the input luminance of the adjacent nozzle is 102, the output luminance is 45.

Here, among the highest luminance in each nozzle (in the example of FIG. 15, the own nozzle luminance 255 and the adjacent nozzle luminance 255), the lowest luminance is represented as MaxMin. In the example of FIG. 15, MaxMin = 241 since the luminance 241 of the nozzle # 01 is the lowest. Similarly, among the lowest luminances in each nozzle (the own nozzle luminance is 0 and the adjacent nozzle luminance is 0 in the example of FIG. 15), the highest luminance is expressed as MinMax. In the example of FIG. 15, since the luminance 23 of nozzle # 01 is the highest, MinMax = 23. The brightness that can be output by all nozzles is limited to this range. That is, in this case, the output luminance range that can be output by all the nozzles is 23 to 241.
Similarly, density correction tables for each color of cyan, yellow, and magenta are created.

<1-3. Density correction processing>
Next, density correction processing using the density correction table TB1 generated as described above will be described. The density correction process described here is details of the density correction process in step S130 of FIG. The outline of the density correction process is as follows. The processing is performed by sequentially specifying “own pixels” to be processed among the pixels constituting the image data one by one. The correction value of the own pixel is calculated using the density correction table TB1 so that the output pixel value of the own pixel becomes equal to the requested output pixel value when the pixel value of the reference pixel other than the own pixel is given. Is done. The “reference pixel” refers to a pixel that is different from the own pixel and that satisfies a predetermined positional relationship with the own pixel. In the present embodiment, a pixel adjacent to its own pixel is used as a reference pixel. Although only the process relating to the black ink (K) will be described, the density correction process is similarly performed for the other color components (cyan, yellow, magenta).

  FIG. 16 is a flowchart showing details of the density correction processing according to the present embodiment. First, the CPU 110 of the PC 100 calculates an output luminance range that can be output from all nozzles (step S301). That is, MaxMin and MinMax are calculated from the density correction table TB1. In the following, for the sake of simplicity, description will be made in consideration of only the three nozzles # 00 to # 02. The density correction table for nozzles # 00 to # 02 is shown in FIG. Therefore, MaxMin = 241 and MinMax = 23.

  Next, the CPU 110 initializes parameters x and y indicating positions in the image (step S302). The parameters x and y are position parameters for specifying the own pixel. x is a parameter indicating the position in the image width direction (paper feed direction), and y is a parameter indicating the position in the image height direction (direction perpendicular to the paper feed direction) (ie, nozzle number). In the present embodiment, the CPU 110 initializes x and y to 0, respectively. In the following description, a nozzle that outputs an ink dot that forms its own pixel is referred to as a “self nozzle”, and a nozzle that outputs an ink dot that forms a reference pixel is referred to as an “adjacent nozzle”.

Subsequently, the CPU 110 calculates a required output luminance (step S303). The required output luminance is like a target value of output luminance. In the present embodiment, the input image is expressed with a luminance of 256 gradations (0 to 255). However, as described above, the luminance that can be output by the image forming apparatus 200 is limited to the range of MinMax to MaxMin (23 to 241 in the present embodiment). Therefore, it is necessary to convert the luminance of the input image to the required output luminance so that the luminance of the input image falls within the output luminance range. The CPU 110 converts the luminance I of the input image into the required output luminance Creq according to the following equation (2).
C _req = (MaxMin−MinMax) / C _max × I + MinMax (2)
Here, C _max indicates the maximum luminance (C _max = 255 in the present embodiment).

Assuming that a solid image having a luminance of 128 is input as an input image, C _req = 132 is obtained by substituting MaxMin = 241, MinMax = 23, C _max = 255, and I = 128 into the equation (2) (decimal point). Rounded down below). Since the input image is a solid image, the required output luminance is 132 for all pixels.

  FIG. 17 is a diagram for visually explaining the output luminance range and the required output luminance. A broken line in FIG. 17 is a straight line representing the expression (2).

  A description will be given with reference to FIG. 16 again. Subsequently, the CPU 110 acquires a density correction table for the own nozzle, that is, the nozzle #y (step S304). This process is performed as follows, for example. The CPU 110 transmits a table transmission request for requesting transmission of the density correction table to the image forming apparatus 200. When receiving the table transmission request, the CPU 210 of the image forming apparatus 200 reads the density correction table TB1 from the RAM 230. The CPU 210 transmits a table transmission response including the read density correction table TB1 to the PC 100 that is the transmission source of the table transmission request. When receiving the table transmission response, the CPU 110 of the PC 100 extracts the density correction table TB1 from the received table transmission response. The CPU 110 stores the extracted density correction table TB1 in the HDD 150. The CPU 110 extracts the density correction table for the nozzle #y from the density correction table TB1 stored in the HDD 150. The CPU 110 stores the extracted density correction table in the RAM 130.

  Note that reading of the density correction table TB1 from the image forming apparatus 200 to the PC 100 may be performed prior to the flow illustrated in FIG. 16, for example, when a printer driver is installed in the PC 100. Further, the image forming apparatus 200 may read all of the density correction table TB1, or may read only a part if necessary.

  Subsequently, the CPU 110 determines whether or not the own nozzle is a nozzle located at the end, that is, y = 0 (step S305). When y = 0 (step S305: YES), the CPU 110 sets the brightness (pixel value) of the adjacent nozzle to a predetermined value (128 in this embodiment) (step S307). This is because the adjacent nozzle does not exist when the own nozzle is located at the end, and therefore the initial value of the luminance of the adjacent nozzle is virtually given. The CPU 110 calculates a correction value from the density correction table using the luminance of the adjacent nozzle and the required output luminance (step S308). A method for calculating the correction value will be described later. CPU 110 stores the calculated correction value in RAM 130.

  On the other hand, when y ≧ 1 (step S305: NO), the CPU 110 reads the correction value M [x, y−1] from the RAM 130 as the luminance of the reference pixel (step S306). The CPU 110 calculates the correction value of the own pixel from the density correction table using the luminance of the reference pixel and the required output luminance (step S308). A method for calculating the correction value will be described later. CPU 110 stores the calculated correction value in RAM 130.

Calculation of the correction value in step S308 is performed as follows.
FIG. 18 is a graph of the density correction table for nozzle # 00 shown in FIG. As shown in FIG. 18, the density correction table is considered to indicate “own nozzle input / output characteristics” for each luminance of adjacent nozzles. As described above, when the self nozzle is nozzle # 00, a predetermined value (128 in this embodiment) is used as the luminance of the adjacent nozzle.

In this embodiment, the density correction table records the output brightness (density data of the actually formed image) when the brightness of the reference pixel is 0, 51, 102, 153, 204, 255. Therefore, when the brightness of the adjacent nozzle is a value other than these values, it is necessary to calculate the value by interpolation. Now, since the input luminance of the adjacent nozzle is 128, linear interpolation is performed using data when the luminance is 102 and 153. Specifically, it is as follows.
In the present embodiment, the density correction table records the output luminance when the luminance of the reference pixel is 0, 51, 102, 153, 204, 255. Therefore, when the luminance of the reference pixel is a value other than these values, it is necessary to calculate a correction value by interpolation. Now, since the input luminance of the reference pixel is 128, linear interpolation is performed using data when the luminance is 102 and 153. Specifically, it is as follows.

  FIG. 19 is a diagram illustrating an interpolation method using an approximate straight line. First, the CPU 110 specifies four points of data used for interpolation from the density correction table. Since the luminance of the reference pixel is 128, data in which the luminance of the reference pixel (adjacent nozzle) is 102 and 153 before and after that is used. The CPU 110 identifies four points surrounding a point where the luminance is 128 out of the straight line with the luminance of the adjacent nozzle 102 and the straight line with 153. In the present embodiment, four points of data surrounded by a thick line in the density correction table for nozzle # 00 shown in FIG. 15 are used. These four data correspond to D (m, n), D (m + 1, n), D (m, n + 1), and D (m + 1, n + 1) in FIG. In this case, D (m, n) = 98, D (m + 1, n) = 133, D (m, n + 1) = 124, and D (m + 1, n + 1) = 161. Here, the symbol D (m, n) means density data (output luminance) when the gradation number of the own pixel (own nozzle) is m and the gradation number of the reference pixel (reference nozzle) is n. . For example, when the density correction table as shown in FIG. 15 is used, the gradation numbers are assigned m = 1, 2,..., 6 in order with respect to the luminance of 0, 51, 102, 153, 204, 255. Means a number.

  Subsequently, the CPU 110 calculates interpolation values D1 and D2 by linear interpolation from the luminance FN of the reference pixel (FIG. 19B). In this case, FN = 128, D1 = 111, D2 = 147. Subsequently, the CPU 110 obtains an equation of a straight line connecting the interpolation values D1 and D2. The CPU 110 substitutes the required brightness DO into this straight line equation to calculate the correction value FO (FIG. 19C). In this case, since DO = 132, FO = 233 is calculated. In FIG. 18, the dotted line indicates the approximate input / output characteristic in which the luminance of the reference pixel obtained by interpolation is 128.

In place of the interpolation method using the approximate line, interpolation using the approximate plane may be employed.
FIG. 20 is a diagram for explaining an interpolation method using an approximate plane. The CPU 110 calculates a plane expression including three points D (m, n), D (m + 1, n), and D (m, n + 1), and D (m + 1, n), D (m, n + 1), and D (m + 1). , N + 1) is obtained as a plane equation including three points. Next, the CPU 110 calculates a correction value from the already determined luminance of the reference pixel and the required output luminance from the respective plane equations. Subsequently, the CPU 110 determines which plane is correct from the brightness of the reference pixel and the range of the correction value. The CPU 110 adopts the correction value calculated using the plane formula determined to be correct as the correction value FO.

  As described above, by using the value (128) predetermined as the luminance of the reference pixel for the pixel [x, 0] and the approximate input / output characteristic where the luminance of the reference pixel obtained by interpolation is 128. The required input brightness, that is, the correction value can be obtained for the required output brightness 132.

  A description will be given with reference to FIG. 16 again. After calculating the correction value of the own nozzle, the CPU 110 updates the nozzle number y (step S309). Specifically, the nozzle number y is updated with y = y + 1. The CPU 110 determines whether the processing has been completed for all nozzles (step S310). When the processing has not been completed for all the nozzles (step S310: NO), the CPU 110 repeatedly executes the processing of steps S304 to S309 described above. In the present embodiment, when the process of steps S304 to S309 is completed for nozzle # 00 (pixel [x, 0]), the process of steps S304 to S309 is subsequently performed for nozzle # 01 (pixel [x, 1]). .

  The processes in steps S304 to S309 for the pixel [x, 1] are basically performed in the same manner as the processes in steps S304 to S309 for the pixel [x, 0]. Differences from the processing for the pixel [x, 0] are as follows. Since the current nozzle is nozzle # 01 (y = 1), the determination result in step S305 is NO. In this case, the process proceeds to step S306. In step S306, the CPU 110 reads the correction value of the reference pixel [x, y−1], that is, the pixel [x, 0], from the RAM 130 as the luminance of the reference pixel. The processing in steps S308 to S312 is the same as that for the pixel [x, 0]. Similar processing is performed for pixels after pixel [x, 2] (nozzles after nozzle # 02).

  On the other hand, when the processing is completed for all the nozzles for one line (step S310: YES), the CPU 110 updates the value of x as x = x + 1 and returns the nozzle number to 0 (step S311). The CPU 110 determines whether the processing has been completed for all pixels (step S312). When the processing has not been completed for all the pixels (step S312: NO), the CPU 110 repeatedly executes the processing of steps S304 to S311. When the processing has been completed for all pixels (step S312: YES), the CPU 110 completes the density correction processing.

  As described above, according to the present embodiment, it is possible to generate a correction table in consideration of the influence of adjacent nozzles. Further, according to the image forming system according to the present embodiment, it is possible to compensate for variations in physical characteristics of nozzles by using a correction table that takes into account the influence of adjacent nozzles (reference pixels). Thereby, a higher quality image can be obtained.

  The correction table (FIG. 15) used in the description of the present embodiment is merely an example, and the content of the correction table is not limited to this. In the example shown in FIG. 15, the density correction table TB1 includes data of six luminances (gradation values) for its own nozzle and adjacent nozzles, but the number of luminances is not limited to six. . In order to improve the accuracy of interpolation, it is desirable to use data with a large number of gradation values, and in order to save memory capacity, it is desirable to use data with a small number of gradation values.

  In this embodiment, the image forming apparatus 200 is a line head type printer. However, the image forming apparatus 200 may be a printer other than the line head type, such as a so-called two-pass printer. In the present embodiment, the image forming apparatus 200 is a printer that forms an image using four colors of ink. However, the number of inks used by the image forming apparatus 200 is not limited to four colors. The image forming apparatus 200 may perform image formation using six colors, seven colors, or more inks.

  In the present exemplary embodiment, the aspect in which the PC 100 performs the image processing illustrated in FIG. 4 has been described. However, the image forming apparatus 200 may perform part or all of the processing in steps S100 to S150 in FIG. . When the image forming apparatus 200 performs all of the processes in steps S100 to S150 in FIG. 4, the image forming apparatus 200 preferably has a memory card interface for reading data from the memory card. In this case, the user inserts a memory card on which an image is recorded by an imaging device such as a digital camera into the memory card interface of the image forming apparatus 200. The image forming apparatus 200 reads the image from the inserted memory card and performs the process of FIG.

<2. Second Embodiment>
Subsequently, a second embodiment of the present invention will be described. The configurations of the image forming system and the density correction table generating system in the present embodiment are the same as those of the image forming system 1 and the density correction table generating system 2 according to the first embodiment, and thus common reference numerals are used for common portions. The explanation is omitted. Only differences from the first embodiment will be described below.

  In the first embodiment described above, an aspect has been described in which the reference pixel is a pixel formed by a nozzle adjacent to the nozzle that forms the pixel itself. In the present embodiment, a description will be given of an aspect in which the reference pixel is a pixel formed by the same nozzle as the nozzle that forms the pixel, and in particular, the reference pixel is a pixel adjacent to the pixel. That is, in the present embodiment, the image forming system 1 performs density correction using the density correction table TB2 that considers the influence of adjacent lines, not adjacent nozzles. Specifically, the density correction table generation system 2 generates the density correction table TB2 using the test pattern 311 instead of the test pattern 301 described in the first embodiment.

  FIGS. 21A to 21F are views showing a part of the test pattern 311 according to the present embodiment. The test pattern 311 has a structure obtained by rotating the test pattern shown in FIG. 9 by 90 °. Also in FIG. 21, the nozzles are arranged in the vertical direction in the figure as in FIG. 9, and the horizontal direction in the figure is the paper feed direction. In the test pattern 311, the size of the unit pattern is the number of dots corresponding to the total number of nozzles. The test pattern 311 is a continuous striped pattern for the number of printable lines. The test pattern in FIG. 21 has a total of l lines, and line numbers are given in order from the left, such as lines # 00, # 01, # 02,.

In the basic pattern shown in FIG. 21A, the odd lines have a luminance of 0 and the even lines have a luminance of 255. As shown in FIG. 21, in order to acquire data of 6 gradations for each of odd lines and even lines, 6 × 6 = 36 basic patterns are necessary as a combination of both (FIG. 21 shows that even lines are Only six basic patterns with luminance 255 are shown). That is, in order to acquire data of c gradations for each of odd lines and even lines, c × c = c ² basic patterns are required as a combination of both.

  FIG. 22 is a diagram illustrating a method for generating the density correction table TB2 in the present embodiment. First, a case where an even line (for example, line # 02) is a correction target line (hereinafter referred to as “own line”) will be described. In the test patterns shown in FIGS. 21A to 21F, the luminance of the own line is fixed at 255, and the luminance of the line adjacent to the own line (hereinafter referred to as “adjacent line”) is 0 for each basic pattern. , 51, 102, 153, 204, 255. The CPU 310 of the PC 300 calculates the average luminance of each unit area and stores it in the RAM 330 as in the first embodiment.

  Next, a case where the odd line (for example, line # 05) is the own line will be described. In the test patterns shown in FIGS. 21A to 21F, the luminance of the own line changes to 0, 51, 102, 153, 204, and 255 for each basic pattern, and the luminance of the adjacent line is fixed to 255. Yes. The CPU 310 of the PC 300 calculates the average luminance of each unit area and stores it in the RAM 330 as in the first embodiment.

  As in the first embodiment, the CPU 310 combines the average luminances stored in the RAM 330 to generate the density correction table TB2. The image forming system 1 performs density correction processing using the density correction table generated in this way. The details of the density correction processing are basically the same as those in the first embodiment except that the “nozzle number” in the first embodiment is replaced with “line number”, and thus the description thereof is omitted.

  According to the present embodiment, it is possible to generate a correction table in consideration of the influence of adjacent lines. The influence of the adjacent line means the influence of the own nozzle in the paper feed direction. This includes variations in the physical characteristics of the nozzles themselves and the effects of the paper feed mechanism. In addition, according to the image forming system according to the present embodiment, it is possible to compensate for line-by-line variations by using a correction table that takes into account the influence of adjacent lines. Thereby, a higher quality image can be obtained.

<3. Third Embodiment>
Subsequently, a third embodiment of the present invention will be described. The configurations of the image forming system and the density correction table generating system in the present embodiment are the same as those of the image forming system 1 and the density correction table generating system 2 according to the first embodiment, and thus common reference numerals are used for common portions. The explanation is omitted. Only differences from the first embodiment will be described below.

  In the first embodiment described above, an aspect has been described in which the reference pixel is a pixel formed by a nozzle adjacent to the nozzle that forms the pixel itself. In this embodiment, in addition to the first reference pixel formed by the nozzle adjacent to the nozzle forming the self pixel described in the first embodiment, in particular, the first reference is present. An aspect in which density correction is performed using a density correction table that also considers the influence of the second reference pixel adjacent to the pixel will be described. Specifically, the density correction table generation system 2 generates a density correction table using a test pattern 321 instead of the test pattern 301 described in the first embodiment.

  FIGS. 23A to 23F are views showing a part of the test pattern 321 according to this embodiment. FIGS. 23A to 23F show basic patterns in which the brightness of the own nozzle is fixed to 255, respectively. In each of FIGS. 23A to 23F, the middle line (k-th line in FIG. 23) indicates the pattern of the own nozzle. The luminance of the nozzle pattern adjacent to the own nozzle (k−1 and k + 1th lines in FIG. 23) is 255, 204, 153, 102, 51 in order in the patterns of FIGS. , 0. The brightness of the pattern of the nozzle next to its own nozzle (k-2th and k + 2th lines in FIG. 23) changes to 0, 51, 102, 153, 204, 255 in each basic pattern.

6 × 6 × 5 = 180 basic patterns are necessary to acquire data of 6 gradations for each of the own nozzle, the adjacent nozzle, and the adjacent nozzle. This is due to the following reason. Since the brightness of the own nozzle is fixed in the basic patterns (six patterns) shown in FIG. 23, six more basic pattern groups shown in FIG. 23 are required to change the brightness of the nozzles in six ways. is there. In addition, since each basic pattern shown in FIG. 23 can acquire data only for the kth nozzle as its own nozzle, in order to acquire data for all five nozzles forming the basic pattern, It is necessary to form a 5 times pattern. That is, in order to acquire c gradation data for each of the own nozzle, the adjacent nozzle, and the adjacent nozzle, c × c × 5 = 5c ^two basic patterns are required.

  FIG. 24 is a diagram showing (a part of) the test pattern 321. In the basic pattern group in FIG. 23, the brightness of the own nozzle is fixed, but in FIG. 24, the brightness of the own nozzle is changed to 6 gradations. Actually, it is necessary to prepare five basic pattern groups shown in FIG.

  FIG. 25 is a diagram illustrating the configuration of the density correction table TB3 according to the present embodiment. As shown in FIG. 25, the density correction table TB3 has a three-dimensional structure in which the density correction table TB1 described in the first embodiment is overlapped by the luminance of the adjacent nozzle. For example, in order to obtain the data of the shaded area in FIG. 25, the brightness of the adjacent nozzle is 255 and the brightness of the adjacent nozzle is 0, 51, 102 in the basic pattern group where the brightness of the own nozzle is 204. , 153, 204, and 255, the average luminance may be calculated for the unit patterns that change.

  The density correction method using the density correction table TB3 is basically the same as that described in the first embodiment. First, when the CPU 110 of the PC 100 performs the correction process for the nozzle # 00, the initial value of the luminance of the adjacent nozzle and the initial value of the luminance of the adjacent nozzle are set to predetermined values (for example, both 128). give. The CPU 110 uses this initial value and the density correction table TB3 to calculate a correction value by the same method as described in the first embodiment. Next, when correction processing is performed for nozzle # 01, CPU 110 uses a predetermined value (for example, 128) as an initial value of the luminance of the adjacent nozzle. Further, the CPU 110 uses the correction value of the nozzle # 00 as the luminance of the adjacent nozzle. The CPU 110 uses these values and the density correction table TB3 to calculate a correction value by the same method as described in the first embodiment. Next, when performing correction processing for nozzle # 01, CPU 110 uses the correction value of nozzle # 00 as the luminance of the adjacent nozzle and the correction value of nozzle # 01 as the luminance of the adjacent nozzle. The CPU 110 uses these values and the density correction table TB3 to calculate a correction value by the same method as described in the first embodiment. The CPU 110 calculates a correction value for each nozzle in the same manner.

  As described above, according to the present embodiment, it is possible to generate a density correction table in consideration of the influence of the adjacent nozzle in addition to the adjacent nozzle. In addition, according to the image forming system according to the present embodiment, it is possible to compensate for variations in physical characteristics of nozzles by using a correction table that takes into account the influence of adjacent nozzles and adjacent adjacent nozzles. Thereby, a higher quality image can be obtained.

  In this embodiment, the test pattern 321 shown in FIG. 23 is used in order to create a density correction table in consideration of the influence of the adjacent nozzle and the adjacent nozzle, but as described in the second embodiment. Further, it may be configured to compensate for variations in the line direction.

  In the present embodiment, the density correction table in consideration of the influence of the adjacent nozzle (first reference pixel) and the adjacent nozzle (second reference pixel) is described. The positional relationship between the nozzles taking into account the influence on the nozzles and the own nozzles is not limited to that described in the present embodiment. In short, any nozzle that corrects using the brightness of one or a plurality of reference nozzles (nozzles other than the own nozzle) whose positional relationship with the own nozzle satisfies a predetermined condition among the plurality of nozzles. Often, “predetermined conditions” are optional design items. The same applies to the first and second embodiments.

<4. Fourth Embodiment>
Subsequently, a fourth embodiment of the present invention will be described. The configurations of the image forming system and the density correction table generating system in the present embodiment are the same as those of the image forming system 1 and the density correction table generating system 2 according to the first embodiment, and thus common reference numerals are used for common portions. The explanation is omitted. Only differences from the first embodiment will be described below.

  In the first embodiment described above, an aspect has been described in which the reference pixel is a pixel formed by a nozzle adjacent to the nozzle that forms the pixel itself. Further, in the above-described second embodiment, the aspect in which the reference pixel is a pixel formed by the same nozzle as the nozzle that forms the own pixel has been described. In the present embodiment, an aspect that considers two reference pixels, in particular, the first reference pixel described in the first embodiment (a pixel formed by a nozzle adjacent to the nozzle that forms the pixel itself), and a second A mode in which two reference pixels of the second reference pixel described in the embodiment (a pixel formed by the same nozzle as the nozzle forming the own pixel and adjacent to the own pixel) is considered will be described. In the present embodiment, the first reference pixel and the second reference pixel are located in different directions on the basis of the own pixel. In particular, a straight line connecting the first reference pixel and the own pixel is orthogonal to a straight line connecting the second reference pixel and the own pixel.

  Specifically, in the present embodiment, the image forming system 1 determines the density correction table TB1 in consideration of the influence of the adjacent nozzle described in the first embodiment and the influence of the adjacent line described in the second embodiment. Density correction processing is performed using two density correction tables, the density correction table TB2 considered. Therefore, in the present embodiment, the density correction table generation system 2 generates two density correction tables, the density correction table TB1 and the density correction table TB2. Since each density correction table generation method is as described in the first and second embodiments, the description thereof is omitted here.

  The density correction processing in the present embodiment is generally performed as follows. In the present embodiment, there are two density correction tables for one pixel. First, the CPU 110 of the PC 100 calculates two correction values (referred to as “temporary correction values”) using these two density correction tables. Next, the CPU 110 calculates the average of the two calculated temporary correction values, and stores it in the RAM 130 as the correction value of the pixel to be processed.

  Specifically, the density correction process is performed as follows, for example. When the pixels of the nozzle # 00 and the line # 00 are to be corrected, the CPU 110 of the PC 100 first sets the initial value of the luminance of the adjacent nozzle as a predetermined value (for example, 128) and the density correction table TB1. Is used to calculate the temporary correction value 1. The temporary correction value 1 is a correction value considering the influence of adjacent nozzles. The CPU 110 stores the temporary correction value 1 in the RAM 130. Further, the CPU 110 calculates the temporary correction value 2 by using the initial value of the luminance of the adjacent line as a predetermined value (for example, 128) and using the initial value and the density correction table TB2. The temporary correction value 2 is a correction value that takes into account the influence of adjacent lines. The CPU 110 stores the temporary correction value 2 in the RAM 130. Next, the CPU 110 calculates the average of the temporary correction value 1 and the temporary correction value 2, and stores the calculated average in the RAM 130 as the correction value of the correction target pixel.

  Similarly, when the pixels of nozzle #k and line #l are to be corrected, the CPU 110 first uses the correction values of the pixels of nozzle # (k−1) and line #l and the density correction table TB1. A temporary correction value 1 is calculated. The CPU 110 stores the temporary correction value 1 in the RAM 130. Further, the CPU 110 calculates the temporary correction value 2 using the correction values of the pixels of the nozzle #k and the line # (l−1) and the density correction table TB2. The CPU 110 stores the temporary correction value 2 in the RAM 130. Next, the CPU 110 calculates the average of the temporary correction value 1 and the temporary correction value 2, and stores the calculated average in the RAM 130 as the correction value of the correction target pixel.

  As described above, according to the present embodiment, it is possible to compensate for variations in physical characteristics of nozzles by using a correction table that takes into account the influence of adjacent nozzles and adjacent lines. Thereby, a higher quality image can be obtained.

  Note that, instead of one or both of the density correction table TB1 and the density correction table TB2, a density correction table TB3 that considers an adjacent nozzle (or an adjacent line) as described in the third embodiment is used. Also good.

<5. Other embodiments>
In the first to fourth embodiments described above, examples in which the present invention is applied to an image forming apparatus such as a line head printer have been described. The application target of the present invention is not limited to this, and the present invention can also be applied to a dot display device such as a liquid crystal display or a plasma display. That is, the test pattern described in the above embodiment is displayed on the dot display device, and the luminance at each dot is measured. A density correction table corresponding to the density correction table TB1 is obtained from the measured luminance. This density correction table is unique to each dot display device. The dot display device stores a density correction table unique to itself.

  When performing display, the dot display device according to the present embodiment performs density correction processing using a density correction table stored in advance. The method for generating the density correction table and the correction method using the density correction table are basically the same as those described in the first to fourth embodiments.

1 is a diagram illustrating a functional configuration of an image forming system 1 according to a first embodiment. 2 is a block diagram illustrating a hardware configuration of an image forming apparatus 200. FIG. 2 is a block diagram illustrating a hardware configuration of a PC 100. FIG. 3 is a flowchart showing the operation of the image forming system 1. 2 is a block diagram showing a functional configuration of a density correction table generation system 2. FIG. It is a figure which shows the hardware constitutions of PC300. It is a flowchart which shows the outline | summary of a density | concentration correction table production | generation process. It is a figure which illustrates test pattern 301 (part). It is a figure which illustrates test pattern 301 (part). It is a figure explaining the gradation expression in a unit pattern. It is a figure explaining the definition of the density data between nozzles. It is a figure which illustrates a unit field. It is a figure explaining the production | generation method of the density correction table of nozzle # 01. It is a figure explaining the production | generation method of the density correction table of nozzle # 02. It is a figure which illustrates density correction table TB1. It is a flowchart which shows the detail of a density correction process. It is a figure which illustrates an output luminance range and a required output luminance visually. FIG. 6 is a graph showing a density correction table for nozzle # 00. It is a figure which shows the interpolation method using an approximate line. It is a figure explaining the interpolation method using an approximate plane. It is a figure which shows the test pattern 311 which concerns on 2nd Embodiment. It is a figure explaining the production | generation method of the density | concentration correction table which concerns on the same embodiment. It is a figure which shows the test pattern 321 (part) of the embodiment. It is a figure which shows the test pattern 321 (part) of the embodiment. It is a figure explaining the structure of density correction table TB3 which concerns on 3rd Embodiment. It is a figure explaining the influence of the adjacent nozzle at the time of correction table preparation.

Explanation of symbols

TB1 ... density correction table, TB2 ... density correction table, TB3 ... density correction table, 1 ... image forming system, 2 ... density correction table generation system, 100 ... PC, 101 ... resolution converter, 102 ... color space converter, 103 ... Density correction unit 104 ... Quantization unit 105 ... Rasterization unit 108 ... Application 109 ... Device driver 110 ... CPU 120 ... ROM 130 ... RAM 140 ... I / F 150 ... HDD 160 ... Keyboard , 170 ... Display, 190 ... Bus, 200 ... Image forming apparatus, 210 ... CPU, 220 ... ROM, 230 ... RAM, 240 ... I / F, 250 ... Image forming section, 251 ... Line head, 252 ... Ink tank, 253 ... head drive circuit, 254 ... control unit, 255 ... motor, 256 ... motor drive Path, 257 ... page buffer, 290 ... bus, 300 ... PC, 301 ... test pattern, 302 ... density correction table generation unit, 303 ... density measurement unit, 304 ... scanned image, 310 ... CPU, 311 ... test pattern, 321 ... Test pattern, 330 ... RAM, 340 ... I / F, 350 ... HDD, 390 ... bus, 400 ... scanner, 2401 ... dot, 2402 ... dot, 2403 ... nozzle, 2404 ... nozzle

Claims (7)

For each of the plurality of pixel output means for performing image formation according to the pixel value, the input pixel value of the own pixel to be corrected among the plurality of pixels constituting the input image data including the input pixel value for each pixel, and the own pixel A table storage unit that stores a density correction table in which an input pixel value of a reference pixel adjacent to the pixel and an output pixel value of the own pixel are associated;
Among the density correction tables stored in the table storage means, the maximum value of the input pixel value of the own pixel and the reference stored in one density correction table corresponding to the pixel output means forming the own pixel Among the output pixel values of the own pixel corresponding to the maximum value of the input pixel value of the pixel, the maximum / minimum value having the smallest pixel value, the minimum value of the input pixel value of the own pixel, and the minimum of the reference pixel The output pixel value of the own pixel corresponding to the value is calculated as a minimum maximum value having the maximum pixel value, and the pixel value of the own pixel falls within the range from the minimum maximum value to the maximum minimum value. Required output pixel value calculating means for calculating the converted value as the required output pixel value of the own pixel;
When the input pixel value of the reference pixel is given to the input image data using the density correction table, the requested output pixel value of the own pixel and the output pixel value of the own pixel are equal to each other. Image correction means for performing correction processing for determining a correction value of the own pixel;
The image data including the correction value determined by the image correcting unit, and a data output means for outputting to an image forming means having a plurality of pixel output means,
The density correction table is created using the density in the intermediate area between the own pixel and the reference pixel, measured from the result of outputting a predetermined test pattern to the own pixel and the reference pixel. An image processing apparatus characterized by the above. The image processing apparatus according to claim 1, wherein the plurality of pixel output units include a plurality of nozzles that eject ink. The image processing apparatus according to claim 1, wherein the plurality of pixel output units include a display device that displays visible light. The table storage means stores a first density correction table and a second density correction table for each of the plurality of pixel output means ,
The reference pixel in the first density correction table is a pixel formed by a pixel output unit adjacent to a pixel output unit that forms the self pixel,
2. The reference pixel in the second density correction table is a pixel that is formed by a pixel output unit that is the same as a pixel output unit that forms the self pixel, and is adjacent to the self pixel. Image processing apparatus. For each of the plurality of pixel output means for performing image formation according to the pixel value, the input pixel value of the own pixel to be corrected among the plurality of pixels constituting the input image data including the input pixel value for each pixel, and the own pixel A reading step of reading out the density correction table from a table storage unit storing a density correction table in which an input pixel value of an adjacent reference pixel and an output pixel value of the own pixel are associated;
Among the density correction tables, the maximum value of the input pixel value of the own pixel and the maximum value of the input pixel value of the reference pixel, which are stored in one density correction table corresponding to the pixel output unit that forms the self pixel. Among the output pixel values of the own pixel corresponding to the value, a maximum / minimum value having the smallest pixel value, the minimum value of the input pixel value of the own pixel, and the minimum value of the reference pixel Among the output pixel values, the minimum maximum value that is the largest pixel value is calculated, and a value obtained by converting the pixel value of the own pixel so as to be within the range of the maximum minimum value from the minimum maximum value , A required output pixel value calculating step of calculating as a required output pixel value of the own pixel;
A correction process is performed on the input image data by using the density correction table to determine the correction value of the own pixel so that the required output pixel value of the own pixel is equal to the output pixel value of the own pixel. An image correction step;
The image data including the correction value determined in the image correction step, and a data output step of outputting to an image forming means having a plurality of pixel output means,
The density correction table is created using the density in the intermediate area between the own pixel and the reference pixel, measured from the result of outputting a predetermined test pattern to the own pixel and the reference pixel. An image processing method characterized by the above. Computer equipment,
For each of the plurality of pixel output means for performing image formation according to the pixel value, the input pixel value of the own pixel to be corrected among the plurality of pixels constituting the input image data including the input pixel value for each pixel, and the own pixel A reading step of reading out the density correction table from a table storage unit storing a density correction table in which an input pixel value of an adjacent reference pixel and an output pixel value of the own pixel are associated;
Among the density correction tables, the maximum value of the input pixel value of the own pixel and the maximum value of the input pixel value of the reference pixel, which are stored in one density correction table corresponding to the pixel output unit that forms the self pixel. Among the output pixel values of the own pixel corresponding to the value, a maximum / minimum value having the smallest pixel value, the minimum value of the input pixel value of the own pixel, and the minimum value of the reference pixel Among the output pixel values, the minimum maximum value that is the largest pixel value is calculated, and a value obtained by converting the pixel value of the own pixel so as to be within the range of the maximum minimum value from the minimum maximum value , A required output pixel value calculating step of calculating as a required output pixel value of the own pixel;
A correction process is performed on the input image data by using the density correction table to determine the correction value of the own pixel so that the required output pixel value of the own pixel is equal to the output pixel value of the own pixel. An image correction step;
The image data including the correction value determined in the image correction step, and a data output step of outputting to an image forming means having a plurality of pixel output means,
The density correction table is created using the density in the intermediate area between the own pixel and the reference pixel, measured from the result of outputting a predetermined test pattern to the own pixel and the reference pixel. A program for causing an image processing method to be executed. Computer equipment,
For each of the plurality of pixel output means for performing image formation according to the pixel value, the input pixel value of the own pixel to be corrected among the plurality of pixels constituting the input image data including the input pixel value for each pixel, and the own pixel A reading step of reading out the density correction table from a table storage unit storing a density correction table in which an input pixel value of an adjacent reference pixel and an output pixel value of the own pixel are associated;
Among the density correction tables, the maximum value of the input pixel value of the own pixel and the maximum value of the input pixel value of the reference pixel, which are stored in one density correction table corresponding to the pixel output unit that forms the self pixel. Among the output pixel values of the own pixel corresponding to the value, a maximum / minimum value having the smallest pixel value, the minimum value of the input pixel value of the own pixel, and the minimum value of the reference pixel Among the output pixel values, the minimum maximum value that is the largest pixel value is calculated, and a value obtained by converting the pixel value of the own pixel so as to be within the range of the maximum minimum value from the minimum maximum value , A required output pixel value calculating step of calculating as a required output pixel value of the own pixel;
A correction process is performed on the input image data by using the density correction table to determine the correction value of the own pixel so that the required output pixel value of the own pixel is equal to the output pixel value of the own pixel. An image correction step;
The image data including the correction value determined in the image correction step, and a data output step of outputting to an image forming means having a plurality of pixel output means,
The density correction table is created using the density in the intermediate area between the own pixel and the reference pixel, measured from the result of outputting a predetermined test pattern to the own pixel and the reference pixel. A storage medium storing a program for executing an image processing method.

Images