JP2021109366A - Image processing device and image processing method - Google Patents

Abstract

To enable an image in which density unevenness in high gradation is reduced to be recorded by single-pass recording, even if variation in recording property is included in a plurality of recording elements that a recording head comprises.SOLUTION: An image processing device obtains a first recording property, as a recording property of a recording element unit and a second recording property, as a recording property of an own recording element and of a recording element near the own recording element, for each of recording elements arranged in a recording head. Further the image processing device generates a threshold matrix on the basis of the first recording property and the second recording property.SELECTED DRAWING: Figure 3

Description

The present invention relates to an image processing apparatus and an image processing method.

In a recording device that expresses gradation by using a pseudo gradation method, density unevenness that depends on variations in recording characteristics of recording elements arranged in a recording head may become a problem. In particular, when a full-line type recording device is used, or when single-pass recording is performed even if the serial type is used, an image on the recording medium is obtained by one relative scanning between the recording head and the recording medium. When completed, the uneven density becomes more noticeable.

Patent Document 1 discloses a method of generating a threshold mask (threshold matrix) used in a half toning process based on recording characteristics (concentration, misalignment) of each recording element. By using the threshold matrix generated by the method of Patent Document 1, it is possible to reduce the density unevenness depending on the variation in the recording characteristics of the recording element.

Japanese Unexamined Patent Publication No. 2001-113805

However, in Patent Document 1, the recording characteristics of each recording element are the recording characteristics peculiar to each recording element, and the influence of the recording characteristics of neighboring recording elements is not included. Therefore, even if appropriate correction can be performed in the low gradation region where the overlap between dots does not occur, the correction of the density unevenness may not be sufficient in the middle and high gradation region where the overlap between dots occurs.

The present invention has been made to solve the above problems. Therefore, the purpose is to record an image in which density unevenness in high gradation is reduced by single-pass recording even if a plurality of recording elements included in the recording head include variations in recording characteristics.

Therefore, the present invention is an image processing device that generates a threshold matrix used in halftone processing for recording an image on a recording medium by one relative scanning between the recording head and the recording medium, and the recording head. For each recording element arranged in, the first recording characteristic which is the recording characteristic of each recording element and the second recording characteristic which is the recording characteristic including the self-recording element and the recording element in the vicinity thereof are acquired. It is characterized by including an acquisition means and a generation means for generating the threshold matrix based on the first recording characteristic and the second recording characteristic.

According to the present invention, even if a plurality of recording elements included in a recording head include variations in recording characteristics, it is possible to record an image in which density unevenness in high gradation is reduced by single-pass recording.

It is a figure which shows the schematic structure of the image processing apparatus. It is a block diagram which shows the hardware structure of an image processing apparatus. It is a flowchart which shows the process of the calibration process and the image recording process. It is a figure which shows the test pattern for calibration. It is a figure for demonstrating the derivation method of the recording characteristic obtained from the 1st pattern. It is a figure which shows the density characteristic of a recording element, and a correction table. It is a figure which shows a part of the concentration fluctuation map schematically. It is a flowchart for demonstrating the process of generating a threshold matrix. It is a flowchart for demonstrating arrangement constraint processing. It is a flowchart for demonstrating the process of arrangement constraint processing. It is a figure which shows the functional structure of an image processing apparatus.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be noted that the following embodiments do not limit the present invention, and not all combinations of features described in the present embodiment are essential for the means for solving the present invention. The same configuration will be described with the same reference numerals.

<First Embodiment>
(Configuration of image processing device)
FIG. 1 shows a schematic configuration of an image processing apparatus 1 applicable to the present embodiment. In the present embodiment, the image processing device 1 is a full-line inkjet recording device. The recording medium P is transported in the X direction at a predetermined speed while being mounted on the transport belt 30. Four recording heads 10 corresponding to cyan (C), magenta (M), yellow (Y), and black (K) are arranged in the middle of the transport path, and ink is ejected according to the recorded data. In each of the recording heads 10, 256 recording elements for ejecting ink are arranged in the Y direction at a predetermined pitch. In the transport direction, an image sensor 20 (line sensor or area sensor) capable of reading an image of the transport recording medium P is arranged on the downstream side of the recording head 10. In the image sensor 20, a plurality of reading elements are arranged in the Y direction at a pitch shorter than that of the recording element of the recording head. Therefore, the image sensor 20 can read the image at a resolution higher than the recording resolution of the recording head 10.

FIG. 2 is a block diagram showing a hardware configuration of the image processing device 1. The image processing device 1 mainly includes a CPU 100, a RAM 101, a ROM 102, an operation unit 103, a display unit 104, an external storage device 105, an image recording unit 106, an image reading unit 107, an image processing unit 108, and an I / F (interface) unit. 109, including bus 110.

The CPU 100 controls the entire image processing device 1 while using the RAM 101 as a work area according to various parameters and programs stored in the ROM 102 and the external storage device 105. However, it is not necessary for the CPU 100 to perform such overall control independently, and it may be shared by a plurality of hardware.

The operation unit 103 is composed of a keyboard, a mouse, and the like, and receives instructions from the operator. The display unit 104 is composed of a CRT, a liquid crystal screen, or the like, and displays the result of processing by the CPU 100. The operation unit 103 and the display unit 104 may be integrated like a touch panel.

The external storage device 105 is a large-capacity information storage device typified by a hard disk drive. The external storage device 105 stores an OS (operating system), computer programs, data, and the like. In addition, the external storage device 105 can also hold temporary data (input / output image data, etc.) generated by the processing of each part. When performing a predetermined process on the computer programs and data stored in the external storage device 105, the CPU 100 reads these programs and data from the external storage device 105 into the RAM 101, and then performs the predetermined process.

The image recording unit 106 uses the recording head 10 described with reference to FIG. 1 to eject ink from the individual recording elements 11 according to the recorded data. Here, the recorded data indicates halftone image data after the image processing unit 108 has performed predetermined image processing on the image data input to the image processing device 1, and in the present embodiment, dots are used for each pixel. It is assumed that the record (1) or non-record (0) of is defined.

The image reading unit 107 uses the image sensor 20 described with reference to FIG. 1 to take an image of the original image, and stores the obtained image data in the RAM 101.

The image processing unit 108 is realized as a processor capable of executing a computer program or a dedicated image processing circuit, and performs various image processing on the image data input to the image processing device 1 and the image data acquired by the image reading unit 107. I do. For example, the image processing unit 108 performs predetermined processing on image data in which each color of R, G, and B input to the image processing device 1 has a pixel value of 8 bits (256 gradations), and C, M, Y, Image data in which each color of K has a pixel value of 8 bits (256 gradations) is generated. Further, the image processing unit 108 performs halftone processing to generate recorded data in which each of the C, M, Y, and K colors has a pixel value of 1 bit (binary value). The recording data in which each color of C, M, Y, and K is 1 bit is the data that defines the recording (1) or non-recording (0) of dots for each pixel area in the recording medium and each of C, M, Y, and K. Is.

The I / F unit 109 is an interface for connecting the image processing device 1 and an external device. The I / F unit 109 also functions as an interface for connecting to the Internet for exchanging data with a communication device using infrared communication, wireless LAN, or the like. Each of the above parts is connected to the bus 110, and data is exchanged via the bus 110.

FIG. 11 is a block diagram showing a functional configuration of the image processing device 1. The CPU 100 functions as the functional configuration shown in FIG. 11 by reading and executing a program stored in the ROM 102 or the external storage device 105 with the RAM 101 as a work area. It should be noted that it is not necessary that all of the processes shown below are executed by the CPU 100, and even if the image processing device 1 is configured so that a part or all of the processes are performed by one or a plurality of processing circuits other than the CPU 100. good.

The image processing device 1 includes a recording control unit 1101, a reading control unit 1102, a recording characteristic acquisition unit 1103, a threshold matrix generation unit 1104, an image data acquisition unit 1105, a color separation processing unit 1106, and a halftone processing unit. 1107 and. The recording control unit 1101 causes the image recording unit 106 to record an image. The reading control unit 1102 causes the image reading unit 107 to read the image. The recording characteristic acquisition unit 1103 acquires the recording characteristics of each of the recording elements 11 arranged in the recording head 10. The threshold matrix generation unit 1104 generates a threshold matrix for halftone processing. The image data acquisition unit 1105 acquires image data representing the image to be recorded. The color separation processing unit 1106 performs color separation processing on the acquired image data. The halftone processing unit 1107 performs halftone processing on the color-separated image data.

(Calibration process)
FIG. 3A is a flowchart for explaining the procedure of the calibration process in the present embodiment. This process is executed by the CPU 100 of the image processing device 1 while using the RAM 101 as a work area according to the program stored in the ROM 102. This process may be started at the time of shipment or arrival of the image processing device 1 or when the user gives an instruction from the operation unit 103, or may be automatically performed by the CPU 100 at a predetermined timing. In the following description, each step is indicated by "S" before the reference numeral.

When this process is started, first, in S201, the recording control unit 1101 reads out a predetermined test pattern stored in the external storage device 105 and causes the image recording unit 106 to record it. The test pattern includes a first pattern 301 and a second pattern 302 as shown in FIG.

In S202, the reading control unit 1102 causes the image reading unit 107 to read the test pattern recorded in S201, and stores the acquired image data in the RAM 101.

In S203, the recording characteristic acquisition unit 1103 performs a recording characteristic acquisition process on the image data stored in the RAM 101. By this recording characteristic acquisition process, the recording characteristics of each of the recording elements 11 arranged in the recording head 10 are derived. The contents of the recording characteristics will be described later.

In S204, the threshold matrix generation unit 1104 generates a threshold matrix based on the recording characteristics acquired in S203 and stores it in the ROM 102. This is the end of this process. The calibration process described above is similarly performed on the four rows of recording elements arranged in the recording head 10.

(Image recording processing)
FIG. 3B is a flowchart for explaining a process of normal image recording processing in the image processing apparatus 1. This process is executed by the CPU 100 of the image processing device 1 while using the RAM 101 as a work area according to the program stored in the ROM 102. This process is started by inputting a recording command from an externally connected host device or the like via the I / F unit 109.

When this process is started, the image data acquisition unit 1105 first expands the received image data into the RAM 101 in S205. This image data is image data in which each pixel has a pixel value of 8 bits (256 gradations) for each color of R, G, and B.

In S206, the color separation processing unit 1106 performs predetermined recording image processing (color separation processing) on the image data developed in S205, and each pixel is a pixel of 8 bits (256 gradations) of R, G, and B. The value is converted into a pixel value of 8 bits (256 gradations) of C, M, Y, and K.

In S207, the halftone processing unit 1107 performs halftone processing on the image data. The halftone processing is performed by the dither method, and the threshold matrix stored in the ROM 102 is used. By halftone processing, 8-bit (256 gradations) pixel values of C, M, Y, and K are converted into 1-bit (binary) pixel values indicating dot recording (1) or non-recording (0). ..

In S208, the recording control unit 1101 causes the image recording unit 106 to perform a recording operation according to the binary pixel value generated in S207. This is the end of this process.

In the present embodiment, the threshold matrix used in the halftone processing performed in S207 of FIG. 3B can be created in advance or updated as appropriate by the calibration processing of FIG. 3A. Then, in the calibration process, the threshold matrix is created in consideration of the density unevenness characteristic of each recording element. Therefore, in S208, a uniform image without density unevenness can be recorded.

(Test pattern)
FIG. 4 is a diagram showing a test pattern for calibration, which is recorded in S201 of FIG. 3A and read in S202. The test pattern includes a first pattern 301 and a second pattern 302. In both patterns, the Y direction corresponds to the arrangement direction of the recording elements, and the X direction corresponds to the transport direction of the recording medium.

The first pattern 301 is a pattern that does not include overlapping of dots recorded by different recording elements, and is a pattern for detecting the recording characteristics of a plurality of recording elements arranged in the recording head 10. The pattern is stepped so that the influences of recording elements adjacent to each other in the Y direction are not included in each other. By performing predetermined image processing on the image read by the image sensor 20 of the first pattern 301, the size error of dots formed on the recording medium by each recording element and the recording position error in the Y direction are acquired. Can be done. Hereinafter, among the plurality of recording elements arranged in the Y direction, the parameter indicating each recording element is set to “y”, the size error of the recording element y is p1 (y), and the recording position error of the recording element y is p2 (y). It is expressed as. Further, in the present specification, the size error p1 (y) and the recording position error p2 (y) are collectively referred to as the first recording characteristic of the recording element y. In this embodiment, y can take a value from 0 to 255.

The second pattern 302 is a pattern including the overlap of dots recorded by different recording elements, and the recording characteristics of each of the plurality of recording elements arranged in the recording head 10 including the influence of the self-recording element and the neighboring recording elements. It is a pattern for detecting. Since the degree of influence of neighboring recording elements changes depending on the gradation, four uniform gradation patterns G1 to G4 are recorded here. In addition, a G0 pattern in which dots are not recorded is also prepared as a white reference. The size of each pattern in the Y direction corresponds to the array width (256 pixels) of the recording elements in the recording head 10. The size in the X direction is not particularly limited, but is preferably a power of 256 or more. Hereinafter, each gradation pattern is indicated by G0 to G4, and the input gradation value for recording the gradation patterns G0 to G4 is indicated by g0 to g4. In the second pattern 302, the arrangement form of dots of each gradation pattern is not particularly limited. For example, a pattern having blue noise characteristics may be used, or an array such as a Bayer type may be adopted.

(Method of deriving recording characteristics)
5 (a) and 5 (b) are diagrams for explaining a method of deriving the first recording characteristic obtained from the first pattern 301. FIG. 5A is a partially enlarged view of the image obtained by reading the first pattern 301. A predetermined number of dots continuously recorded by one recording element are arranged in a row in the X direction. The recording characteristic acquisition unit 1103 cuts out a part of the image shown by the broken line in the figure for each recording element. Then, the difference between the average density value obtained by averaging the pixel values (density values) of the plurality of read pixels included in the cut-out area in the X direction and the pixel values (density values) of the pixels included in the blank area is obtained.

FIG. 5B is a concentration distribution showing the difference in association with the coordinates in the Y direction. The recording characteristic acquisition unit 1103 calculates the integrated value (integrated value) of such a concentration distribution for all the recording elements. Then, the average value of the integrated values of all the recording elements is obtained, and the difference between the average value and the integrated value of the recording element y is defined as the size error p1 (y) of the recording element y. Such a size error p1 (y) corresponds to the difference from the average of the recorded dot sizes. Further, the recording characteristic acquisition unit 1103 obtains the center of gravity of the concentration distribution for each recording element, and sets the difference between the Y coordinate of the recording element y and the Y coordinate of the center of gravity as the recording position error p2 (y) of the recording element y. do. Such a recording position error p2 (y) corresponds to the amount of deviation of the recorded dot from the ideal position in the Y direction.

FIG. 6A is a diagram showing a second recording characteristic of the recording element y obtained from the second pattern 302. The horizontal axis indicates the input gradation value. This input pixel value can be considered as the number of pixels in which the recording element y records dots among the 256 pixels arranged in the X direction, and is also referred to as the number of dots. In the figure, gradation values g0 to g4 for recording each of the gradation patterns G0 to G4 are plotted, and g0 indicates a gradation in which the number of dots is 0 and no dots are recorded on the recording medium. .. On the other hand, g4 has 256 dots and indicates a gradation for recording dots in all pixel regions on the recording medium.

The vertical axis shows the measured density in the region corresponding to the recording element y in the gradation patterns G0 to G4. For example, in the gradation g0 where the number of dots is 0, a density of 4000 on the paper surface is obtained as a measurement density. Further, in the gradation g4 in which the number of dots is 256, a density of 58,000 is obtained as a measurement density. As shown in FIG. 6A, the density characteristic in which each gradation g0 to g4 is associated with the measured density is acquired for all the recording elements. In the present specification, such a density characteristic is referred to as a second recording characteristic in the recording element y.

Since the second recording characteristic varies among the recording elements, density unevenness occurs on the recording medium. Therefore, in the present embodiment, the dot generation ratio p3 (g, y) for obtaining a standard density in all the recording elements is set for each gradation value g and for each recording element y.

FIG. 6B shows a dot number correction table obtained from the inverse function of the density characteristic of FIG. 6A. The horizontal axis shows the target density, and the vertical axis shows the number of dots for the recording element y to achieve the target density.

For example, when the input gradation value is 192, the recording element y records dots in 192 pixel regions out of 256 pixel regions arranged in the X direction. In this case, according to FIG. 6A, a concentration equivalent to 54,000 is expressed on the recording medium. When trying to achieve a target density of 44500 common to all recording elements, the recording element y may record 131 dots in the pixel region as shown in FIG. 6B. .. In this embodiment, the ratio 131/192 at this time is set to the dot generation ratio p3 (g3, y) of the recording element y at the gradation g = g3. That is, the dot number generation ratio p3 (g, y) of the recording element y is the dot required for the recording element y with respect to the standard dot number generation, which is required to achieve the target density in the gradation g. It means the ratio of the number of shots.

As described above, in the recording characteristic acquisition process of S203, the recording characteristic acquisition unit 1103 has the first pattern to the first recording characteristic, that is, the size error p1 (y) and the recording position error p2 (for each of the recording elements). y) is acquired. In addition, the second recording characteristic, that is, the density characteristic is acquired from the second pattern. Then, the dot number ratio p3 (g, y) is derived from the second recording characteristic.

(Threshold matrix generation process)
Next, the threshold matrix generation process performed by the threshold matrix generation unit 1104 in S204 of FIG. 3A will be described. The threshold matrix M of the present embodiment has a rectangular shape of Sx pixels in the X direction and Sy pixels in the Y direction. Sy is equivalent to the number of recording elements arranged in the Y direction in the recording head 10. Sx is arbitrary, but 256 pixels or more having a power of 2 length is preferable. For the sake of explanation here
Sx = Sy = 256
And.

In this embodiment, the conventionally known Void & Cruster method is adopted to generate the threshold matrix M. In the Void & Cruster method, a threshold matrix of the same size and a dot pattern area are prepared, dots are added or deleted one by one in the dot pattern area, and a threshold is set for the corresponding pixel of the threshold matrix according to the addition or deletion. It is a way to do it.

In this embodiment, the dot pattern region and the density variation map N (g) are used to generate the threshold matrix M. The dot pattern area is a binary map having a pixel area having the same size as the threshold matrix M. Dots are added to the pixel area included in the dot pattern area according to the gradation g, and in the dot pattern area, the pixel value of the pixel in which the dots are arranged is "1", and the pixel of the pixel in which the dots are not arranged is set to "1". The value is managed as "0".

The density variation map N (g) is a two-dimensional multi-valued map generated based on the dot pattern region, and is used as an evaluation standard for each pixel when dots are added to the dot pattern region. The content of the density variation map N (g) changes depending on the number of dots included in the dot pattern region, that is, the gradation value g. The density variation map N (g) is generated by adding the filter f (y) and the arrangement limit amount lm (g, y) to the dot pattern region.

The filter f (y) is a function indicating the regulatory force of the dot arrangement given to the peripheral pixels by the dots recorded by the recording element y, and can also be expressed as the filter f (y, s, t). Here, "s" and "t" indicate the X coordinate and the Y coordinate of the pixel of interest included in the filter. On the other hand, assuming that the distance between the dot recorded by the recording element y and the pixel of interest is r, the filter f (y, s, t) for the recording element y can be expressed by (Equation 1).

In (Equation 1), 1 is added to the denominator in order to avoid division by zero at the distance r = 0. In addition, r _{can be obtained by (Equation 2) in consideration of the coordinates (s 0} , t ₀ ) in which the recording element y recorded the dots and the recording position error p2 (y) of the recording element y.

The value obtained by such a filter f (y, s, t) is a regulation value indicating the degree to which one dot recorded by the recording element y regulates the arrangement of dots given to the pixel of the coordinate (s, t). Can be regarded as. Then, the regulation value of the pixel of interest (s, t) obtained by the filter f (y, s, t) becomes smaller as the distance from the dot recorded by the recording element y decreases, and the size error p1 (y) of the recording element y becomes smaller. The larger it is, the larger it becomes. The size of the filter f (y, s, t), that is, the range in which one dot exerts a regulatory force is arbitrary, but in the present embodiment, 256 pixels in the X direction and 256 pixels in the Y direction are matched to the threshold matrix M. And.

When generating the density variation map N (g), the filters f (y, s, t) are added for all the dots arranged in the dot pattern region. According to the generated density variation map N (g), the degree of density of dots in the pixel region can be grasped, the regulation value of the pixels included in the region where the dots are coarse is low, and the dots are dense. The regulation value of the pixels included in the area becomes high.

FIG. 7A is a diagram schematically showing a part of the density variation map N (g) in an arbitrary dot pattern. The limit values in which the dots recorded by the individual recording elements y affect the nearby pixel region are shown in shades of light. For dots recorded by the recording element y1 having a large size error p1 (y), the regulation value given to the nearby pixel region becomes large. Further, for the dots recorded by the recording element y2 having a large recording position error p2 (y), the regulation value given to the pixel region in the direction in which the landing position is deviated (+ Y direction in FIG. 7) becomes large.

FIG. 8 is a flowchart for explaining the process of generating the threshold matrix. This process corresponds to S204 of the flowchart described in FIG. 2A, and the CPU 100 of the image processing device 1 executes the process while using the RAM 101 as a work area according to the program stored in the ROM 102.

When this process is started, the threshold matrix generation unit 1104 first performs the filter generation process described above in S600. Specifically, the threshold matrix generation unit 1104 is based on the size error p1 (y) and the recording position error p2 (y) of the individual recording elements acquired in the density unevenness characteristic derivation process of S203, and the recording element y. A filter f (y, s, t) peculiar to each of the above is generated.

In S601, the threshold matrix generation unit 1104 prepares a threshold matrix M in which no threshold is set and a dot pattern region in which dots are not arranged.

In S602, the threshold matrix generation unit 1104 arranges one dot at an arbitrary position with respect to the dot pattern region. Further, the variable g indicating the gradation value is set to 1 (g = 1). In this flowchart, the variable g has a range of 0 to 256 × 256 = 65535.

In S603, the threshold matrix generation unit 1104 generates a density variation map N (g) based on the filter f (y, s, t) generated in S600 and the current dot pattern in the dot pattern region.

In S604, the threshold matrix generation unit 1104 selects the pixel having the lowest regulation value from the density variation map N (g) and determines it as the pixel in which the dots are arranged. If there are multiple pixels with the lowest regulation value, set them randomly. Here, it is assumed that the pixels at the coordinates (xd, yd) are determined as the pixels for arranging the dots.

In S605, the threshold matrix generation unit 1104 adds dots to the pixels in the dot pattern region corresponding to the pixels determined in S604, and updates the dot pattern.

In S606, the threshold matrix generation unit 1104 sets the threshold g in the pixels of the threshold matrix M corresponding to the pixels selected in S604. In this state, a threshold value of 1 to g is set in the threshold value matrix M.

In S607, the threshold matrix generation unit 1104 updates the concentration fluctuation map N (g). That is, the filter f (y, s, t) corresponding to the dots added in S605 is added to the current density variation map N (g).

In S608, the threshold matrix generation unit 1104 performs dot arrangement constraint processing.

FIG. 9 is a flowchart for explaining the arrangement constraint processing performed in S606. This process is executed by the CPU 100 of the image processing device 1 while using the RAM 101 as a work area according to the program stored in the ROM 102.

In S701, the threshold matrix generation unit 1104 has an arrangement limit amount lm (g, yd) based on the dot occurrence ratio p3 (g, yd) in the gradation g of the recording element yd corresponding to the dots added in S605. Is derived. In the present embodiment, the arrangement limit amount lm (g, yd) can be obtained by multiplying the reciprocal of the dot generation ratio p3 (g, yd) by a predetermined coefficient α. That is, the arrangement limit amount lm (g, yd) can be expressed by (Equation 3).

However, the dot number ratio p3 (g, y) obtained by actually measuring the second pattern is only for the discrete gradation values (g0, g1, g2, g3, g4). Therefore, the arrangement limit amount lm (g, gy) of the other gradation value g is calculated by performing an interpolation calculation using the arrangement limit amount lm (g, gy) corresponding to the two neighboring gradation values. ..

For example, when the gradation value g is g0 <g ≦ g1, the arrangement limit amount lm (g, yd) can be obtained by (Equation 4).

In S702, the threshold matrix generation unit 1104 adds the arrangement limit amount lm (g, yd) to all the pixels for which y = yd with respect to the density fluctuation map N (g) updated in S607. As a result, in the density variation map N (g), all the regulation values of the pixel to which the dot is added in S605 and the pixel having the same Y coordinate as the pixel are increased. This completes the placement constraint processing.

FIG. 7B is a diagram showing a state in which the arrangement limit amount lm (g, yd) is further added to the concentration fluctuation map N (g) shown in FIG. 7A. It can be seen that the arrangement limit amount lm (g, yd) is added to the pixel on which the dot is placed and all the pixels extending in the X direction including the pixel, and the limit value is increased.

Return to the flowchart of FIG. In S609, the threshold matrix generation unit 1104 determines whether or not the dots are arranged in all the pixels included in the dot pattern region. If there are still pixels in which dots are not arranged, the gradation value g is counted up in S610, the process returns to S604, and the process for the next gradation value is repeated. By repeating S604 to S610 until dots are arranged in all the pixels of the dot pattern region, a threshold matrix M is generated in which preferable dispersibility can be obtained in consideration of the recording characteristics and density characteristics of each recording element. be able to.

In S611, the threshold matrix generation unit 1104 performs gamma correction on all the thresholds arranged in the generated threshold matrix M. Gamma correction is a correction for adjusting the relationship between the input pixel value (gradation value) and the density expressed on the recording medium to an arbitrary relationship such as a linear relationship, and all threshold values are one-dimensional. It is done by converting.

In S612, the threshold matrix generation unit 1104 stores the threshold matrix M corrected in S611 in the ROM 102. This is the end of this process.

In the above processing, all the steps S605 to 607 can be performed based on the pixels determined in S604 and have no dependency on each other. Therefore, these processes may be performed in a different order or may be performed in parallel.

According to the present embodiment described above, each time a dot is added to the dot pattern region, the regulation value by the filter f (y, s, t) and the arrangement limit amount lm (g,) are added to the density variation map N (g). gy) is added, and the concentration fluctuation map N (g) is updated. Then, in S605, a new dot is added to the pixel having the lowest regulation value in the density fluctuation map N (g) at that time. At this time, the filter f (y, s, t) is set so that the pixel closer to the existing dot has a higher regulation value, which contributes to increasing the dispersity of the dots. On the other hand, the arrangement limit amount lm (g, yd) is set so as to obtain a regulation value according to the dot generation ratio of each recording element, and contributes to correcting the density unevenness between the recording elements. ..

In the present embodiment, the coefficient α of (Equation 3) is adjusted in advance so that the arrangement limit amount lm (g, yd) is prioritized over the regulation value added by the filter f (y, s, t). ing. Specifically, in the pixel region included in the density variation map N (g), the minimum value after adding the arrangement limit amount lm (g, yd) is the maximum value before adding the arrangement limit amount lm (g, yd). The coefficient α is set so that it becomes larger than the value.

By performing halftone processing using the threshold matrix M created by the method of the present embodiment as described above, it is possible to output an image having excellent dispersibility and suppressed density unevenness. Further, since it is not necessary to provide the correction process for suppressing the density unevenness as described in Patent Document 1 as one step of the image processing when recording the actual image, the processing load at the time of recording is conventionally increased. Can also be suppressed. Further, in the present embodiment, since the γ correction function is also included in the threshold matrix, the processing load when recording the actual image can be further reduced and the throughput can be improved.

<Second embodiment>
Also in this embodiment, the calibration processing described in FIGS. 3 to 8 is performed by using the image processing device 1 described in FIGS. 1, 2 and 11.

In the low gradation region where overlap between dots does not occur, by adding the arrangement limit amount lm (g, yd), the dispersibility of the dots may be impaired, and the graininess may be worsened. For example, when the size of the threshold matrix is small, or when the density characteristics vary widely among recording elements, such graininess is particularly noticeable. On the other hand, in the low gradation region where the dots do not overlap, the density unevenness itself due to the variation in the density characteristics between the recording elements tends to be inconspicuous.

In view of the above, in the present embodiment, when the gradation value g is in the gradation region of 0 to g0, the arrangement limit amount lm (g, yd) is not added to the density variation map N (g). do.

FIG. 10 is a flowchart for explaining a process of placement constraint processing executed by the threshold matrix generation unit 1104 of the present embodiment in S608 of FIG. This process is executed by the CPU 100 of the image processing device 1 while using the RAM 101 as a work area according to the program stored in the ROM 102.

In S801, the threshold matrix generation unit 1104 determines whether or not the current gradation value g satisfies g ≧ g1. When g ≧ g1 is not satisfied, that is, when the gradation value g is the gradation value g0 or less, the threshold matrix generation unit 1104 adds the arrangement limit amount lm (g, yd) to the density variation map N (g). This process ends without doing anything. That is, in the gradation region where g1 ≧ g ≧ 0, the density variation map N (g) is generated only by the filter f (y, s, t), and the dots are arranged at the position where the addition value of the filter is the lowest. .. In this case, the number of dots corresponding to each recording element is in an uncontrolled state. On the other hand, when g ≧ g1 is satisfied in S801, the threshold matrix generation unit 1104 proceeds to S802.

In S802, the threshold matrix generation unit 1104 determines whether or not the current gradation value g satisfies g> g1. When g ≧ g1 is satisfied, the process proceeds to S701, and the arrangement limit amount lm (g, yd) is added to the concentration fluctuation map N (g) by the same method as in the first embodiment. Since the contents of S701 and S702 are the same as those of the same step in FIG. 9, the description here is omitted. On the other hand, when g> g1 is satisfied in S802, that is, when g = g1, the threshold matrix generation unit 1104 proceeds to S803.

In S803, the threshold matrix generation unit 1104 counts the number of dots arranged in the dot pattern region at the present stage in association with each of the recording elements. Then, the value gc obtained for the recording element y is set as the target dot generation number gc in the current gradation value g1 of the recording element y, and the dot generation ratio p3 (g1, y) of the current gradation value g is updated. do. Then, this process is completed without adding the arrangement limit amount lm (g, yd) to the concentration fluctuation map N (g).

According to the present embodiment described above, the arrangement limit amount lm (g, yd) can be appropriately switched on and off with the gradation value g1 as a boundary. That is, in the medium density gradation in which the density unevenness is easily noticeable, the dots are arranged based on the density fluctuation map to which the arrangement limit amount lm (g, yd) is added, so that the image is output while suppressing the density unevenness. can do. On the other hand, in the low gradation region where graininess is more noticeable than density unevenness, the arrangement limit amount lm (g, yd) is not added, and the density fluctuation map generated only by the filter f (y, s, t) is displayed. Dots are arranged based on. Therefore, it is possible to output an image in which the graininess is suppressed and the dispersibility is excellent.

In the above, the configuration is such that the arrangement limit amount lm (g, yd) is switched on and off when the gradation value g = g1, but the gradation value for switching on and off is another gradation value. It doesn't matter. Further, the gradation region of g1 ≦ g ≦ g2 may be a transition region in which the weight of the arrangement limit amount lm (g, yd) is gradually increased.

Further, as already described, the balance between the regulation value to be added by the filter f (y, s, t) and the arrangement limit amount lm (g, yd) can be adjusted by using the coefficient α. That is, by changing the coefficient α according to the gradation value, not only the placement limit amount lm (g, yd) is turned on and off, but also the influence of the placement limit amount lm (g, yd) on the density variation map is affected. It may be adjusted in each gradation.

<Other Embodiments>
In the first and second embodiments, as described with reference to FIG. 8, the threshold matrix is generated in a state including the gamma correction process. However, the gamma correction process may be performed between S206 and S207 of the image recording process described with reference to FIG. 3 (b).

Further, when the density unevenness characteristic derived in S203 shows different characteristics for each recording medium, the image processing apparatus 1 may generate a threshold matrix according to the type of the recording medium.

The test patterns shown in FIGS. 4A and 4B are merely examples. If the pattern can derive the recording characteristics of dots recorded by a single recording element and the density characteristics of individual recording elements including the influence of neighboring recording elements, use a pattern of another shape. You may.

Further, in the above embodiment, the second test pattern is a five-step gradation pattern including a blank sheet, but the number of gradation steps may be further increased or decreased. Further, it is not necessary to fix the interval of gradation values to a constant value. For example, in the case of an inkjet recording device in which each recording element can record dots of a plurality of sizes, a pattern corresponding to a gradation value for switching the dot size may be recorded.

In the above embodiment, a function that uses the reciprocal of the distance between dots is used as the filtering process (see Equation 1), but other smoothing filters such as a Gaussian filter may be used. In any case, any filter that can control the frequency component perceived as graininess can be applied to the above embodiment.

Further, in the above-described embodiment, the full-line type recording head and the full-line type image sensor 20 are used as shown in FIG. 1, but the above-described embodiment is not limited to such a mode. .. The recording head 10 may be of a serial type as long as the single-pass recording is performed in which the image on the recording medium is completed by one relative scanning between the recording head and the recording medium. The image sensor 20 may also be a serial type that sequentially reads images while moving in the Y direction. Further, the recording head 10 and the image sensor 20 do not have to be arranged in the same transport path of the recording medium. Furthermore, the image processing device 1 does not have to be provided with the image sensor 20, and may be in a form in which an image read by an external reading device can be acquired.

Further, in the above, the inkjet recording device is used as the image recording device, but if the recording device uses a plurality of recording elements to express gradation by the pseudo gradation method, the dots are recorded by another method. Even so, the effects of the above-described embodiment can be fully exerted.

The present invention supplies a program that realizes one or more functions of the above-described embodiment to a system or device via a network or storage medium, and one or more processors in the computer of the system or device reads and executes the program. It can also be realized by processing. It can also be realized by a circuit (for example, ASIC) that realizes one or more functions.

1 Image processing device 1103 Recording characteristic acquisition unit 1104 Threshold matrix generation unit

Claims (14)

An image processing apparatus that generates a threshold matrix used in halftone processing for recording an image on a recording medium by one relative scanning between a recording head and a recording medium.
For each recording element arranged in the recording head, a first recording characteristic which is a recording characteristic for each recording element and a second recording characteristic which is a recording characteristic including a self-recording element and a recording element in the vicinity thereof. And the acquisition method to acquire
An image processing apparatus comprising: a generation means for generating the threshold matrix based on the first recording characteristic and the second recording characteristic. The acquisition means
Based on the image obtained by reading the first pattern that does not include the overlap of dots recorded by different recording elements, the first recording characteristic is acquired.
The second recording characteristic is acquired based on the image obtained by reading the second pattern including the overlap of dots recorded by different recording elements.
The image processing apparatus according to claim 1. The first recording characteristic is a characteristic relating to the size and recording position of dots recorded on the recording medium by each recording element.
The acquisition means acquires the characteristics related to the dot size from the average density value of the row of dots recorded continuously by each recording element recorded in the first pattern, and the position of the center of gravity of the row of dots. To obtain the characteristics related to the recording position from
The image processing apparatus according to claim 2. The second recording characteristic is a characteristic indicating the correspondence between the gradation value and the measured density in the image recorded by the self-recording element and the recording element in the vicinity thereof.
The acquisition means acquires the second recording characteristic from the measurement densities of a plurality of patterns having different gradation values recorded in the second pattern.
The image processing apparatus according to claim 2. The generation means adds dots to each pixel in the dot pattern region having the same size as the threshold matrix in association with the gradation value, and adds dots to the pixels of the threshold matrix corresponding to the pixels to which the dots are added. The image processing apparatus according to any one of claims 1 to 4, wherein the threshold matrix is generated by setting a threshold value corresponding to a gradation value. 5. The generation means is characterized in that dots are added in the dot pattern region based on the first recording characteristic so that the dispersibility of the dots arranged in the dot pattern region is high. The image processing apparatus according to. 5. The image processing apparatus according to. The generation means sets a regulation value indicating the degree of regulation of dot arrangement based on the dot arrangement in the dot pattern region, the first recording characteristic, and the second recording characteristic in the dot pattern region. The image processing apparatus according to any one of claims 5 to 7, wherein each pixel included in the image is derived and dots are added to the pixel having the lowest regulation value in the dot pattern region. The generation means generates a filter that regulates the arrangement of dots with respect to the pixels around the pixel in which the dots are arranged based on the first recording characteristic, and each recording is based on the second recording characteristic. Derivation of an arrangement limit amount that regulates the arrangement of dots for all pixels on which the element can record dots, and deriving the restriction value using the value obtained from the filter and the arrangement limit amount. The image processing apparatus according to claim 8. The generation means derives the regulation value using only the value obtained from the filter in the first gradation value, and the filter in the second gradation value higher than the first gradation value. The image processing apparatus according to claim 9, wherein the regulation value is derived by using the value obtained from the above and the arrangement limit amount. A recording control means for performing a halftone process using the threshold matrix generated by the generation means and causing the recording head to record an image according to the halftone image obtained by the halftone process is further provided. The image processing apparatus according to any one of claims 1 to 10. A program for causing a computer to function as each means of the image processing apparatus according to any one of claims 1 to 11. An image processing method that generates a threshold matrix used in halftone processing for recording an image on a recording medium by one relative scanning between a recording head and a recording medium.
For each recording element arranged in the recording head, a first recording characteristic which is a recording characteristic for each recording element and a second recording characteristic which is a recording characteristic including a self-recording element and a recording element in the vicinity thereof. And the acquisition process to acquire
An image processing method comprising a generation step of generating the threshold matrix based on the first recording characteristic and the second recording characteristic. A step of recording on a recording medium a first pattern that does not include the overlap of dots recorded by different recording elements and a second pattern that includes the overlap of dots recorded by different recording elements.
The step of reading the first pattern and the second pattern, and
With more
In the acquisition step, the first recording characteristic is acquired based on the image obtained by reading the first pattern, and the second recording is performed based on the image obtained by reading the second pattern. The image processing method according to claim 13, wherein the characteristics are acquired.

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