JP2021178503A - Image processing device - Google Patents

Abstract

To provide an image processing device capable of suppressing wind ripple unevenness for image data with low resolution without causing deterioration in granularity and a tone jump.SOLUTION: An image processing device includes an image data reception unit 11 for receiving image data and a half tone processing unit 13 for generating multi-valued data by subjecting the image data to half tone processing and converting the image data into at least 3 values or more. The half tone processing part 13 executes the half tone processing so that a zero value is included without fail except for a case in which all pixels constituting the image data are converted into a maximum value.SELECTED DRAWING: Figure 2

Description

The present invention relates to an image processing apparatus that performs halftone processing on image data.

Conventionally, an inkjet printing apparatus has been proposed in which ink is ejected from an inkjet head to perform a printing process on a printing medium conveyed on a conveying path.

In such an inkjet printing apparatus, an air flow is generated by transporting a printing medium directly under the inkjet head.

Further, when ink is continuously ejected from the nozzle of the inkjet head, the ink droplets are ejected with a self-air flow, and the self-air flow acts like a wall that blocks the air flow due to the transfer of the print medium described above. Then, the airflow generated by the transport of the print medium may collide with the wall of the self-airflow, and the airflow may be disturbed in a complicated manner. Due to this turbulence, the landing position of the ink ejected from the inkjet head may deviate from a desired position, which may cause density unevenness, so-called wind pattern unevenness.

As a method for correcting this density unevenness, in Patent Document 1, when the image data has a high resolution and the density is within a predetermined range, the resolution of the image data is converted to a low resolution according to the degree of occurrence of self-airflow. , A method to make the wind pattern unevenness inconspicuous has been proposed.

Japanese Unexamined Patent Publication No. 2016-013645

However, the method described in Patent Document 1 cannot be applied when the image data is originally of low resolution. Further, in the method described in Patent Document 1, the grain size is lowered because the ink droplet size becomes large in the region converted to low resolution, and the tone jump occurs in the boundary region where the resolution of the image data is switched to low resolution. There is a problem that it will occur. Tone jump is a phenomenon in which the gradation of an originally smooth gradation part changes suddenly and looks like a striped pattern.

In view of the above circumstances, it is an object of the present invention to provide an image processing apparatus capable of suppressing wind pattern unevenness even with low-resolution image data without causing deterioration of graininess or tone jump.

The image processing apparatus of the present invention includes an image data receiving unit that receives image data and a halftone processing unit that performs halftone processing on the image data and converts it into at least three values to generate multi-valued data. The halftone processing unit performs halftone processing so as to always include a zero value, except when all the pixels constituting the image data are converted to the maximum value.

According to the image processing apparatus of the present invention, when halftone processing is applied to image data to convert it into at least three values or more to generate multi-valued data, all the pixels constituting the image data have the maximum value. Except for the case of conversion, the halftone processing is performed so as to always include the zero value to suppress the wind pattern unevenness, so that the image data is low resolution without causing deterioration of graininess or tone jump. However, it is possible to suppress wind pattern unevenness.

A block diagram showing a configuration of an inkjet printing apparatus using the first and second embodiments of the image processing apparatus of the present invention. A block diagram showing a configuration of an image processing unit according to a first embodiment of the image processing apparatus of the present invention. Diagram to explain the concept of existing halftone processing The figure for demonstrating the concept of halftone processing in 1st Embodiment of the image processing apparatus of this invention. A flowchart for explaining an outline of arithmetic processing of halftone processing in the first embodiment of the image processing apparatus of the present invention. The figure for demonstrating the specific arithmetic processing of the halftone processing in 1st Embodiment of the image processing apparatus of this invention. A flowchart for explaining a specific arithmetic process of halftone processing in the first embodiment of the image processing apparatus of the present invention. A block diagram showing a configuration of an image processing unit according to a second embodiment of the image processing apparatus of the present invention. Figure for explaining binary error diffusion processing by Floyd-Steinberg method A diagram for explaining binary error diffusion processing equivalent to the Floyd-Steinberg method. The figure for demonstrating the multi-value error diffusion processing in the halftone processing part of 2nd Embodiment. A flowchart for explaining the flow of arithmetic processing of the halftone processing of the second embodiment. A block diagram showing a configuration of a modified example of the image processing unit of the second embodiment. The figure for demonstrating an example of the density conversion process for adjusting a white pixel density. The figure for demonstrating the method of adjusting the white pixel density in binary error diffusion processing. The figure which shows the result of applying the existing multi-value error diffusion processing to a monochrome gradation image. The figure which shows the result of applying the halftone processing of 2nd Embodiment to a monochrome gradation image.

Hereinafter, the inkjet printing apparatus 1 using the first embodiment of the image processing apparatus of the present invention will be described in detail with reference to the drawings. FIG. 1 is a schematic configuration diagram of the inkjet printing apparatus 1 of the present embodiment.

The inkjet printing device 1 performs printing processing by ejecting ink onto a sheet-shaped printing medium such as paper or film based on the image data output from the computer or the image data output from the document reading device. As shown in FIG. 1, the inkjet printing apparatus 1 includes an image processing unit 10, a head drive control unit 20, an inkjet head unit 30, a transport unit 40, and a control unit 50.

The image processing unit 10 receives the image data output from the computer or the document reading device, and performs various processing on the image data. In the present embodiment, the image processing unit 10 corresponds to one embodiment of the image processing apparatus of the present invention. The image processing unit 10 includes a CPU (Central Processing Unit), a semiconductor memory, and the like. The CPU and semiconductor memory of the image processing unit 10 may be shared with the control unit 50 described later, or may be provided separately.

The image processing unit 10 executes an image processing program stored in advance in a storage medium such as a semiconductor memory or a hard disk, and operates an electric circuit to process each unit described later.

As shown in FIG. 2, the image processing unit 10 includes an image data receiving unit 11, a color conversion unit 12, and a halftone processing unit 13.

The image data receiving unit 11 receives the RGB format image data output from the computer or the document reading device, and outputs the image data to the color conversion unit 12.

The color conversion unit 12 converts the RGB format image data into CMYK format image data and outputs the image data to the halftone processing unit 13.

The halftone processing unit 13 performs halftone processing on each of the C, M, Y, and K image data output from the color conversion unit 12 and converts them into at least three values to generate multi-valued data. do. The multi-valued data of the present embodiment is data that defines the number of ink drops ejected from one nozzle of the inkjet head in order to form one dot of the printed image, and is also referred to as ink drop data.

The halftone processing unit 13 of the first embodiment performs the halftone processing using the dither method, and performs the halftone processing for suppressing the wind pattern unevenness described above. The halftone processing unit 13 of the present embodiment performs halftone processing so as to always include a zero value, except when all the pixels constituting the image data are converted to the maximum value (maximum number of drops). However, the specific processing method will be described in detail later.

The image processing unit 10 is not limited to the above-mentioned processing, but also performs various known image processing such as gamma correction processing and edge enhancement processing.

The head drive control unit 20 drives the inkjet head unit 30 to eject ink from each nozzle of the inkjet head of each color based on the ink drop data of each color generated by the halftone processing unit 13.

The inkjet head unit 30 includes a plurality of inkjet heads that eject inks of each color of C, M, Y, and K. As described above, each inkjet head is controlled by the head drive control unit 20 based on the ink drop data of each color to eject ink to the print medium and form a print image on the print medium.

The transport unit 40 includes a transport mechanism that transports the print medium to the inkjet head unit 30.

The control unit 50 includes a CPU, a semiconductor memory, and the like, and controls the entire inkjet printing device 1. The control unit 50 controls the operation of each unit of the inkjet printing device 1 by executing a control program stored in advance in a storage medium such as a semiconductor memory or a hard disk and operating an electric circuit.

Next, before explaining the halftone processing of the inkjet printing apparatus 1 of the present embodiment, the existing halftone processing will be described with reference to the conceptual diagram of FIG. Here, a case where the maximum number of drops of ink ejected to one print dot is 3 drops will be described. Further, the existing halftone processing described here is also a halftone processing using a dither method, and is a halftone processing using a 4 × 4 dither matrix.

FIGS. 3 (1) to 3 (49) are diagrams showing the result of applying the existing halftone processing to a predetermined 4 × 4 pixel in the image data, and the print density is from the lowest density (zero). The halftone processing result when changing to the maximum density is shown. As the number in parentheses increases, the print density increases by one step. One square in each of FIGS. 3 (1) to 3 (49) indicates one pixel.

FIGS. 3 (1) to 3 (17) show the halftone processing results when the print density changes from zero to the 17th step. As shown in FIGS. 3 (1) to 3 (17), when the print density changes from zero to the 17th step, "1" indicating the number of ink drops "1" for each step of the print density increase. Data are added one by one according to the distribution of each dither threshold in the dither matrix. When the print density is 17 levels, all the pixels are "1" data.

Next, as shown in FIGS. 3 (18) to 3 (33), when the print density is from 18 steps to 33 steps, the ink is ink every time the print density is increased by one step from the data state where all the pixels are "1". The data of "2" indicating the number of drops "2" is added one by one according to the distribution of each dither threshold in the dither matrix. When the print density is 33 levels, all the pixels are "2" data.

Next, as shown in FIGS. 3 (34) to 3 (49), when the print density is from 34 steps to 49 steps, the ink is ink every time the print density is increased by one step from the data state of "2" for all pixels. The data of "3" indicating the number of drops "3" of is added one by one according to the distribution of each dither threshold in the dither matrix. When the print density is 49 steps, all the pixels are "3" data. That is, all pixels have the maximum value (maximum number of drops).

As described above, in the case of the existing halftone processing, all the pixels become non-zero data when the print density is 17 steps, and after the print density is 18 steps, the data of "2" or "3" is sequentially obtained. Will be added. That is, after the print density is 17 steps or later, the zero value is not included between the pixels, so that the print dot density is always high, and the self-air flow due to the ink ejection described above is likely to occur. Therefore, uneven wind pattern is likely to occur.

Next, the concept of halftone processing of the inkjet printing apparatus 1 of the present embodiment will be described with reference to FIG. Also here, the case where the maximum number of drops of ink ejected to one print dot is 3 drops will be described. Further, the halftone processing of the present embodiment described here is also a halftone processing using a 4 × 4 dither matrix.

4 (1) to 4 (37) are diagrams showing the result of performing the halftone processing of the present embodiment on a predetermined 4 × 4 pixel in the image data, and the print density is the lowest density (zero). ) To the maximum density, the halftone processing result is shown. As the number in parentheses increases, the print density increases by one step. Here, for the sake of clarity, it is assumed that all 4 × 4 pixels have the same density.

In the halftone processing of the present embodiment, first, the number of ink drops "1" is sequentially added according to the increase in the print density, but the addition of the data of "1" is stopped with the zero value remaining. That is, when the number of pixels having a zero value reaches a predetermined number of pixels, the addition of the data of "1" is stopped.

Next, the data of "2" is sequentially added according to the increase in the print density, and at this time, the data of "1" is arranged according to the same arrangement rule as when the data of "1" is arranged. Then, the addition of the data of "2" is stopped with the zero value remaining. Further, the data of "3" is sequentially added according to the increase in the print density, and at this time, the data of "2" is arranged according to the same arrangement rule as when the data of "2" is arranged. Then, the zero value remains until the print density reaches the maximum density, and all the pixels reach the maximum value (data of "3") at the time when the print density reaches the maximum density. Hereinafter, a more specific description will be given with reference to FIG.

FIGS. 4 (1) to 4 (9) show the halftone processing results when the print density changes from zero to the ninth step. As shown in FIGS. 4 (1) to 4 (9), when the print density changes from zero to the ninth step, each time the density increases by one step, the number of ink drops "1" is indicated by "1". Data are added one by one according to the distribution of each dither threshold in the dither matrix. Then, as described above, the addition of the data of "1" is stopped while the zero value is left, but here, the addition of the data of "1" is stopped when the print density is 9 steps. The print density at which the addition of the data of "1" is stopped is not limited to the nine stages, but is set to a stage where the wind pattern unevenness can be suppressed.

Next, as shown in FIGS. 4 (10) to 4 (21), the data of "1" or "0" is replaced with the data of "2" when the print density is from 10 to 21.

First, as shown in FIGS. 4 (10) to 4 (17), the print density from 10 steps to 17 steps is the same as the data arrangement rule of "0" when the print density changes from zero to 9 steps, for example. The placement rule is used to replace the data of "1" with the data of "2". As a result, the data of "1" can be replaced with the data of "2" while maintaining the number of zero values in nine stages.

Therefore, the effect of suppressing wind pattern unevenness can be maintained, and the print density gradation can be smoothed, so that tone jump can be suppressed.

Next, as shown in FIGS. 4 (18) to (21), when the print density is from 18 to 21 according to the distribution of each dither threshold in the dither matrix, the data of "0" is the data of "2". Is replaced by. Then, in the halftone processing of the present embodiment, the addition of the data of "2" is stopped with the zero value left as described above, but here, the data of "2" is stopped when the print density is 21 steps. The addition has stopped. The print density for stopping the addition of the data of "2" is not limited to the 21 steps, but is set to a step where the wind pattern unevenness can be suppressed.

The number of zero values at the time when the addition of the data of "2" is stopped can be smaller than the number of zero values at the time of stopping the addition of the data of "1" described above. This is because the size of the ink droplets increases as the number of ink drops increases, and the gaps between the ink dots on the printing surface are small or overlap, so even if the landing position shifts due to the influence of the air flow. This is because it is less likely to cause uneven wind pattern.

Then, by reducing the number of zero values at the time when the addition of the data of "2" is stopped to be smaller than the number of zero values at the time when the addition of the data of "1" is stopped, that is, the number of values is increased. By performing halftone processing so that the proportion of zero values contained in the entire multi-valued data decreases as the data becomes larger, the print density gradation can be increased and the image quality of the printed image can be improved. can.

Then, as shown in FIGS. 4 (22) to 4 (37), the data of "2" or "0" is replaced with the data of "3" when the print density is from 22 steps to 37 steps.

First, as shown in FIGS. 4 (22) to 4 (33), from the state where the data of "2" of 21 steps is maintained from the state where the print density is from 22 steps to 33 steps, for example, the print density is from 10 steps to 21 steps. The data of "2" is replaced with the data of "3" by using the same arrangement rule as the arrangement rule of the data of "2" in the case of changing up to. As a result, the data of "2" can be replaced with the data of "3" while maintaining the number of zero values in 21 steps.

Therefore, the effect of suppressing wind pattern unevenness can be maintained, and the print density gradation can be smoothed, so that tone jump can be suppressed.

Next, as shown in FIGS. 4 (34) to 4 (37), when the print density is from 34 to 37, the data of "0" is the data of "3" according to the distribution of each dither threshold in the dither matrix. Is replaced by. Then, the zero value remains until the print density reaches the maximum density, and all the pixels reach the maximum value (data of "3") at the time when the print density reaches the maximum density.

As shown in FIGS. 4 (1) to 4 (37), the halftone processing unit 13 of the present embodiment converts all the pixels constituting the image data to the maximum value (in the case of FIG. 4 (37)). Except for, halftone processing is always performed so that the zero value is included. As a result, the print dot density can be set to be lower than that of the existing halftone processing, so that it is possible to make it difficult for self-airflow due to the above-mentioned ink ejection to occur, and it is possible to suppress wind pattern unevenness. In addition, it is possible to suppress wind pattern unevenness even with low-resolution image data without causing deterioration of graininess or tone jump.

Further, as shown in FIGS. 4 (1) to 4 (9), when the data of "0" is converted into the data of "1", the pixel of the data of "0" is adjacent to the pixel of the data of "1". It is preferable that the pixels of the data of "1" are not continuous by two or more pixels in the vertical and horizontal directions. However, the arrangement of the data of "0" and the data of "1" depends on the density of each pixel of the image data. Therefore, for example, in halftone processing, after converting each pixel of the image data into data of "0" and "1" using a dither matrix, the data of "1" is continuous for two or more pixels in the vertical direction or the horizontal direction. By further performing the process of detecting the portion and converting the data of "1" of the detected portion into the data of "0", the pixels of the data of "1" are prevented from being continuous by two or more pixels in the vertical and horizontal directions. You may. As a result, it is possible to maintain a state in which the print dot density is low without depending on the image data.

Next, the outline of the arithmetic processing of the halftone processing of the present embodiment will be described with reference to the flowchart shown in FIG.

First, the halftone processing unit 13 sets the y-coordinate of the pixels constituting the image data to y = 0 (S10) and the x-coordinate to x = 0 (S12). The initial values of the x-coordinate and y-coordinate of the pixels constituting the image data are zero.

Then, the density data data [x] [y] of the pixels at the positions of the x-coordinate and the y-coordinate set in S10 and S12 and the dither threshold dth of the dither matrix Dth corresponding to the positions of the x-coordinate and the y-coordinate are acquired. (S14). The position of the dither threshold dth in the dither matrix Dth is, for example, the remainder obtained by dividing the x-coordinate of data [x] [y] by the size of the dither matrix Dth in the x-direction and the y-coordinate divided by the size of the dither matrix in the y-direction. It is obtained by calculating the remainder. The dither matrix Dth and the dither threshold dth will be described in detail later.

Then, the halftone processing unit 13 executes arithmetic processing using the density data data [x] [y] obtained in S14 and the dither threshold value dth, thereby corresponding to the density data data [x] [y]. The quantification data (ink drop data) is calculated (S16). The specific arithmetic processing here will be described in detail later.

Next, the halftone processing unit 13 increments the x coordinate by 1 (S18), and when the value of x is smaller than the size (x_size) in the x direction of the image data (S20, YES), S14 to S18. Repeat the process of.

Then, in S20, when x ≧ x_size (S20, NO), the halftone processing unit 13 increments the y coordinate by 1 (S22), and the value of y is the size of the image data in the y direction (S20, NO). If it is smaller than y_size) (S24, YES), the processes of S12 to S22 are repeated.

Then, the halftone processing unit 13 ends the processing when y ≧ y_size (S24, NO) in S24. As a result, multi-valued data (ink drop data) can be obtained for all the pixels constituting the image data.

Next, the arithmetic processing of S16 in FIG. 5 in the halftone processing of the present embodiment will be specifically described. Here, the density data of each pixel of the image data is set to 0 to 255, and as shown in FIG. 4, it is converted into multi-valued data of 0 to 3 by performing halftone processing.

First, the density threshold value Th and the dither matrix Dth used in the halftone processing of the present embodiment will be described. In the present embodiment, as shown in FIG. 6, the concentration range of 0 to 255 is divided into three ranges. The horizontal axis of FIG. 6 is density data, and the vertical axis is print density. Then, the value of the boundary of the division is set to the concentration threshold value Th [0], Th [1], Th [2], Th [3]. Th [0] = 0 and Th [3] = 255. Th [1] is a value for determining the print density range to which the data of "1" is added by the halftone process, and is a value for determining the print density range from the 0th step to the 9th step shown in FIG. That is, it is a print density that stops the addition of the data of "1". For example, Th [1] = 30 is set. When Th [1] is increased, the density of the data of "1" becomes high, that is, the print dot density becomes high and wind pattern unevenness occurs, and when Th [1] is small, wind pattern unevenness does not occur. However, since the number of small dots is reduced and the graininess is increased, Th [1] is set to a value in which the wind pattern unevenness and the graininess are well-balanced by an experiment or the like.

Th [2] is a value for determining the print density range to which the data of "2" is added by the halftone process, and is a value for determining the print density range from 10 steps to 21 steps shown in FIG. That is, it is a print density that stops the addition of the data of "2". For example, Th [2] = 110 is set. Similar to Th [1], Th [2] is also set to a value in which wind pattern unevenness and graininess are well-balanced by an experiment or the like.

Then, in this embodiment, Th [0] to Th [1] are set to the concentration range index m = 0, Th [1] to Th [2] are set to the concentration range index m = 1, and Th [2] to Th [ 3] is set as the concentration range index m = 2. The concentration range index m = 0 to 2 will be used later in the description of specific arithmetic processing.

Next, in the present embodiment, halftone processing is performed using the three dither matrices Dth [1], Dth [2], and Dth [3] according to the three density ranges of the image data.
The dither matrix Dth [1] is a dither matrix that converts the image data in the first density range 0 to 105 into data of "0" or "1" by halftone processing. The dither matrix Dth [1] is obtained by normalizing the dither matrix composed of the blue noise mask with the density values in the first density range 0 to 105. For example, when one threshold value of the dither matrix composed of a blue noise mask is dth and the corresponding threshold value of the dither matrix Dth [1] is dth [1], it is calculated by the following equation. In this embodiment, a dither matrix composed of a blue noise mask is used, but a halftone dot type dither matrix may be used.
dth [1] = (first normalized value x dth) / 256

Further, the first normalized value in the above equation is a value that controls the speed at which the dots become dense. For example, if the first normalization value is 256, when dth is 10, 100, dth [1] is 10, 100, but if the first normalization is 128, dth [1] is 5, 50. The threshold value becomes smaller and printing becomes easier. That is, this means that the smaller the first normalized value, the faster the density. In this embodiment, 105 is set as the first normalized value.

The dither matrix Dth [2] is a dither matrix that converts the image data in the second density range 30 to 135 into the data of “2” by halftone processing. The dither matrix Dth [2] is obtained by normalizing the dither matrix consisting of the blue noise mask with a concentration value in the second concentration range of 30 to 135. For example, when one threshold value of the dither matrix composed of a blue noise mask is dth and the corresponding threshold value of the dither matrix Dth [2] is dth [2], it is calculated by the following equation. The meaning of the second normalized value is the same as that of the first normalized value, and in the present embodiment, 105 is set as the second normalized value.
dth [2] = (second normalized value x dth) / 256

The dither matrix Dth [3] is a dither matrix that converts the image data in the third density range 105 to 255 into the data of "3" by halftone processing. The dither matrix Dth [3] is obtained by normalizing the dither matrix consisting of the blue noise mask with a concentration value in the second concentration range 105 to 255. For example, when one threshold value of the dither matrix composed of a blue noise mask is dth and the corresponding threshold value of the dither matrix Dth [3] is dth [3], it is calculated by the following equation. The meaning of the third normalized value is the same as that of the first normalized value, and in the present embodiment, the third normalized value is 255-Th [2]. By setting such a value, when the density data is 255, the solid data of the ink drop of "3" can be obtained.
dth [3] = (third normalized value x dth) / 256

Further, in FIG. 6, the area converted into the ink drop data of “0” and “1” (0,1 drop area) and the ink drop data of “0”, “1”, and “2” are converted. Areas (0,1,2 drop areas), areas converted to "0" and "2" ink drop data (0,2 drop areas), and "0", "2", and "3" inks. An area converted into drop data (0,2,3 drop area) and an area converted into ink drop data of "0" and "3" (0,3 drop area) are shown.

Next, the halftone processing using the above-mentioned density threshold values Th [0] to Th [3] and the dither matrix Dth [1] to [3] will be described with reference to the flowchart shown in FIG. 7.

First, the halftone processing unit 13 acquires the density data of a predetermined pixel constituting the image data, and determines which of the above-mentioned density range index m = 0 to 2 the density data data belongs to. (S30). Specifically, m that satisfies Th [m] ≦ data <Th [m + 1] is determined.

Next, the halftone processing unit 13 calculates the above-mentioned dth [1] to dth [3] (S32).

When the value of m determined in S13 is zero (S34, YES), the density data data of the pixel and the dither threshold dth [1] of the dither matrix Dth [1] at the position corresponding to the pixel. When data> dth [1] (S36, YES), the multi-valued data (ink drop data) of the pixel is set to “1” (S38).

On the other hand, when data ≦ dth [1] (S36, NO), the multi-valued data (ink drop data) of the pixel is set to “0” (S40).

Further, when the value of m determined in S30 is not zero (S34, NO), the halftone processing unit 13 subtracts Th [m] from the density data data of the pixel (data-Th [m]. ) And the dither threshold dth [m + 1] of the dither matrix Dth [m + 1] at the position corresponding to the pixel (S42). Note that data-Th [m] is an operation because the pixel density data is input data based on Th [m].

Then, when the input data is larger than dth [m + 1] (S42, YES), the halftone processing unit 13 sets the multi-valued data (ink drop data) of the pixel to m + 1 (S44).

Specifically, the halftone processing unit 13 compares data-Th [1] and dth [2], for example, when m is 1. When data-Th [1] is larger than dth [2], the multi-valued data (ink drop data) of the pixel is set to 2. As a result, the data of "2" shown in FIGS. 4 (10) to (21) is arranged.

On the other hand, in S42, when data-Th [m] ≤ dth [m + 1] (S42, NO), the dither threshold dth [m] of the dither matrix Dth [m] at the position corresponding to the pixel and Th. Compare with [m] -Th [m-1] (S46).

Here, Th [m] -Th [m-1] becomes Th [1] -Th [0] when, for example, m = 1, and as shown in FIGS. 4 (1) to 4 (9), "1" The concentration interval from the start of adding data to the stop is shown. Then, as shown in FIGS. 4 (10) to 4 (17), the data of "2" needs to be arranged at the same place as the position of the data of "1", which is based on the condition of S42. It is realized by arranging the data of "2".

However, when the condition of S42 is not satisfied, it is necessary to maintain the concentration at the time of Th [1]. Therefore, when the data of "2" is not arranged in S42, it is necessary to arrange the data of "1" in the place where the data of "1" is arranged at the time of Th [1].

Therefore, when the data of "2" is not arranged in S42, the dither threshold dth [1] for the data of "1" is smaller than the concentration at which the addition of the data of "1" is stopped in the comparison formula of S46. In this case, the data of "1" is arranged (S48). This is because when the dither threshold dth [1] is smaller than Th [1] −Th “0”, it indicates that the data of “1” is already arranged at that position.

On the other hand, in the comparative formula of S46, when dth [m] ≧ Th [m] −Th [m-1], the multi-valued data (ink drop data) of the pixels is set to 0 (S50).

As a result, when the density data of the pixels of the image data is the density interval of m = 1, it can be converted into the data of "0", "1" or "2". That is, it is possible to smooth the change in print density while mixing the data of "0".

In the above description, the case of m = 1 has been described, but even in the case of m = 2, the concentration data in the concentration section of m = 2 is set to “0” by performing the processing based on the comparative formula of S42 and S46. It can be converted into "2" or "3" data. That is, it is possible to smooth the change in print density while mixing the data of "0".

Next, the inkjet printing apparatus 2 using the second embodiment of the image processing apparatus of the present invention will be described in detail. The schematic configuration of the inkjet printing apparatus 2 of the second embodiment is the same as that of the inkjet printing apparatus 1 of the first embodiment shown in FIG. 1, but the configuration of the image processing unit 10 is different from that of the first embodiment. ..

The halftone processing unit 13 of the first embodiment performs halftone processing using the dither method as described above, whereas the image processing unit 10 of the second embodiment uses the multi-value error diffusion method. The halftone processing used is performed. In the case of halftone processing using the dither method as in the first embodiment, a memory capacity for storing the dither matrix is required. For example, when using a 256 × 256 dither matrix, a memory capacity of 64 kByte is required. On the other hand, the multi-value error diffusion process does not need to store the dither matrix, so that the memory capacity can be reduced, and the arithmetic process can be realized by simple hardware. It is possible to reduce the entire hardware. The memory capacity required for the multi-value error diffusion process will be described in detail later.

FIG. 8 is a block diagram showing the configuration of the image processing unit 10 of the second embodiment. Similarly to the first embodiment, the halftone processing unit 13 of the second embodiment always sets a zero value except when all the pixels constituting the image data are converted to the maximum value (maximum number of drops). Although halftone processing is performed so as to include the image processing unit 10, the image processing unit 10 of the second embodiment includes a binary error diffusion processing unit 14 in order to perform such halftone processing. Then, the halftone processing unit 13 of the second embodiment performs the multi-value error diffusion processing based on the processing result of the binary error diffusion processing unit 14, so that the halftone including the zero value is surely included as described above. Perform processing.

The binary error diffusion processing unit 14 performs binary error diffusion processing on each image data of C, M, Y, and K before the halftone processing by the halftone processing unit 13. As a binary error diffusion process, for example, a binary error diffusion process by the Floyd-Steinberg method using a diffusion coefficient as shown in FIG. 9 is known, but in the present embodiment, an equivalent method is used. Perform binary error diffusion processing. As shown in FIG. 9, the Floyd-Steinberg method is a method of distributing an error generated in a pixel of interest by multiplying a peripheral pixel by a diffusion coefficient. In the present embodiment, as shown in FIG. 10, the peripheral pixel A method is used in which the error is multiplied by the diffusion coefficient and distributed to the pixels of interest. In this method, the error err_bin distributed to the pixels of interest is expressed by the following equation. In the following equation, err_mem0 [] is a memory that stores the error one line before the line of the pixel of interest, err_pre is the error one pixel before the pixel of interest, and err_mem1 [] is the pixel of interest. A memory that stores the error used in the next line of the line.
err_bin = err_mem0 [x-1] * 1/16 + err_mem0 [x] * 3/16 + err_mem0 [x + 1] * 5/16 + err_pre * 7/16

Then, assuming that the density data of the pixel of interest is D, the pixel data Derr after the error is distributed is expressed by the following equation.
Derr = D + err_bin

Then, when Derr> 127, the black determination is made and the quantized value is 255. On the other hand, when Derr ≦ 127, white determination is made and the quantized value is set to 0.

Then, err = Derr-quantization value is calculated, err_mem1 [x] = err, and err_pre = err.

By performing the binary error diffusion processing by the arithmetic processing as described above, the hardware may be a total of two lines of memory, err_mem0 [] and err_mem1 []. Further, if the error storage timing is shifted, the error of the pixel of interest can be written back to the used area of err_mem0 [] after the error is read, so that a memory of one line is substantially required. The error distributed to the pixels of the first line (y = 0) may be set in advance.

Then, the binary error diffusion processing unit 14 performs binary error diffusion processing on the image data of C, M, Y, and K, respectively, and as a result, the white-determined pixel, that is, the quantization value becomes 0. A white pixel flag is added to the pixel that has become.

Then, when the halftone processing unit 13 of the second embodiment performs the halftone processing by the multi-value error diffusion processing, the pixel determined to be white by the binary error diffusion processing unit 14 is always set to a zero value. Hereinafter, the multi-value error diffusion processing in the halftone processing unit 13 of the present embodiment will be described.

Similar to the binary error diffusion processing, the halftone processing unit 13 quantizes the density data of each pixel using the quantization threshold value, and calculates the error from the quantization value and the density data.

Specifically, assuming that the quantization value is q [i], the quantization threshold is q_th [i], and the density data of each pixel is D, when the maximum number of drops is maxdrop = 3, for example, as shown in FIG. Each value can be set.

Then, as in the binary error diffusion process, assuming that the error distributed from the peripheral pixels to the pixel of interest is err_mlt, which of the quantization thresholds q_th [1] to q_th [3] shown in FIG. 11 is used? The value of i that determines is obtained by the following equation. Note that INT () is a function that rounds down to the nearest whole number and returns the maximum integer that does not exceed the original number.
i = INT ((D + err_mlt) * maxdrop / 255)

For example, as shown in FIG. 11, when D + err_mlt = 150, i is calculated by the following equation and becomes 1.
i = INT (150 * 3/255) = INT (1.76) = 1

At this time, q_th [1] = 127 is used as the quantization threshold value, and D + err_mlt = 150 is quantized to q [1] = 85 or q [2] = 170, but D + err_mlt = 150 is q_th [ Since it is larger than 1] = 127, the quantized value is q [2] = 170. Then, the multi-valued data (ink drop data) becomes "2" corresponding to q [2] = 170.

More specifically, first, the above-mentioned Derr is calculated, and then the value of i is calculated. Then, in the case of i> maxdrop, i = maxdrop is set. Then, in the case of i = maxdrop, the quantized value becomes q [maxdrop], and the multivalued data becomes maxdrop.

If i = maxdrop, it is confirmed whether or not the white pixel flag is added to the pixel, and if the white pixel flag is added, zero is calculated as the quantization value of the pixel. , Multi-valued data also becomes zero. As described above, for the pixel to which the white pixel flag is added, the quantization value becomes zero, but since the error between the input density and the quantization value zero is compensated by the peripheral pixels, due to the characteristics of error diffusion, The concentration does not decrease.

On the other hand, when the white pixel flag is not added and Der> q_th [i], q [i + 1] is calculated as the quantized value, and the multivalued data becomes i + 1. When Derr ≤ q_th [i], q [i] is calculated as the quantized value, and the multivalued data becomes i.

Next, the flow of the arithmetic processing of the halftone processing of the second embodiment described above will be described with reference to the flowchart shown in FIG.

First, the halftone processing unit 13 sets the y-coordinate of the pixels constituting the image data to y = 0 (S90) and the x-coordinate to x = 0 (S92). The initial values of the x-coordinate and y-coordinate of the pixels constituting the image data are zero.

Then, binary error diffusion processing is performed on the density data of the pixels at the positions of the x-coordinate and the y-coordinate set in S90 and S92 (S94). Then, when the white determination is made, the white pixel flag is added to the pixel (S96).

Next, multi-value error diffusion processing is performed on the density data of the pixels at the x-coordinate and y-coordinate positions set in S90 and S92, and the multi-valued data of the pixels is calculated (S98). At the time of the diffusion processing, the white pixel flag added in S96 is referred to as described above.

Next, the halftone processing unit 13 increments the x coordinate by 1 (S100), and when the value of x is smaller than the size (x_size) in the x direction of the image data (S102, YES), S94 to S100. Repeat the process of.

Then, in S102, when x ≧ x_size (S102, NO), the halftone processing unit 13 increments the y coordinate by 1 (S104), and the value of y is the size of the image data in the y direction (S102, NO). If it is smaller than y_size) (S106, YES), the processes of S92 to S104 are repeated.

Then, the halftone processing unit 13 ends the processing when y ≧ y_size in S106 (S106, NO). As a result, multi-valued data (ink drop data) can be obtained for all the pixels constituting the image data.

Next, a modified example of the second embodiment described above will be described. In the second embodiment, a white pixel flag is added to a pixel that is determined to be white by performing binary error diffusion processing, and the multi-valued data is forcibly set to zero for that pixel. For example, in a portion where the density is bright, the density of white pixels is originally high, so when the above-mentioned processing is performed, the quantization value of the multi-valued error diffusion processing of most of the pixels becomes zero. In such a state, in the process of multi-valued error diffusion processing, the error of the pixel whose quantized value becomes zero accumulates, and the quantified value suddenly becomes large in the printable area. For example, in a portion where the density is bright, it is desired to mix 0 drop and 1 drop, but 0 drop and 3 drop are mixed, and the graininess of the printed image deteriorates.

Therefore, in the modified example of the second embodiment, the density of the white pixels is prevented from becoming too high after the binary error diffusion processing. FIG. 13 is a diagram showing a configuration of a modified example of the image processing unit 10 of the second embodiment. As shown in FIG. 13, in the modified example of the image processing unit 10 of the second embodiment, the white pixel density adjusting unit 15 is further provided.

The white pixel density adjusting unit 15 performs density conversion processing as white pixel density adjusting processing on the input C, M, Y, and K image data. Specifically, as shown in FIG. 14, the white pixel density adjusting unit 15 makes the density of pixels to be determined as white sparse as the input density of the image data is brighter or darker, and is determined as white at an intermediate density. Each image data is subjected to a density conversion process that maximizes the pixel density.

In the graph shown in FIG. 14, at the intermediate density, the output density is controlled so that the white pixel density is sufficient to reduce the wind pattern unevenness, and at the portion brighter than the intermediate density, the brighter the output density with respect to the input density. It becomes darker (white pixel density is sparse), and in a portion darker than the intermediate density, the darker the color, the darker the output density with respect to the input density (white pixel density is sparse). The method of realizing the density conversion process may be a look-up table or a function such as a predetermined linear expression.

Then, the binary error diffusion processing unit 14 applies the binary error diffusion processing unit 14 to each image data that has been subjected to the density conversion processing by the white pixel density adjusting unit 15. The modified example of the second embodiment is the same as that of the second embodiment in other configurations.

According to the modification of the second embodiment, the density of the pixels to be determined to be white is made sparser in the portion where the input density of the image data is brighter, so that the deterioration of the graininess can be prevented.

Further, the method of adjusting the density of white pixels after the binary error diffusion processing is not limited to the above method, and the binary error diffusion processing unit 14 may adjust the density of the pixels to be determined to be white. good.

Specifically, the quantization value of the pixel determined to be white is set to a negative value, and the quantization threshold is set based on the negative value and the quantization value of the pixel determined to be black to perform binary error diffusion processing. conduct. Specifically, as shown in FIG. 15, the quantization value of the pixel determined to be white is set to a negative value white_dens (for example, -20), and the negative value white_dens and the quantization value of the pixel determined to be black are black_dens (255). Based on the above, the quantization threshold (137) is calculated, and the binary error diffusion process is performed. As described above, when the quantization value is a negative value (-20), for example, even if the input density is 0, the error is the input density (0) -the quantization value (-20) = 20, so that the periphery Distribute the positive error to the pixels. That is, it works to increase the density of peripheral pixels, which makes the density of white pixels sparse.

By applying such a binary error diffusion process to a portion brighter than the intermediate density of the image data, the density of the white pixels after the binary error diffusion process can be made sparse. As a result, it is possible to prevent deterioration of graininess even in a portion where the density is bright, as in the modified example of the second embodiment.

16A to 16D are diagrams showing the results of applying an existing multi-value error diffusion process to a monochrome gradation image. 16A to 16D are diagrams in which a part of the gradation image subjected to the multi-value error diffusion processing is extracted, and the density becomes thinner toward A to D. FIG. 16A includes a portion converted to the maximum concentration. Wind pattern unevenness is likely to occur in the concentration range R only by applying the existing multi-value error diffusion treatment.

17A to 17D are diagrams showing the results of applying the halftone processing of the second embodiment to monochrome gradation images similar to those of FIGS. 16A to 16D. In FIGS. 17A to 17D, all white pixels (zero values) are included except for the portion converted to the maximum density. In particular, it can be seen that white pixels are included in the solid portions of FIGS. 17B and 17C. As a result, the influence of wind pattern unevenness can be suppressed in the concentration range R.

Further, the following additional notes are disclosed with respect to the image processing apparatus of the present invention.
(Additional note)

In the image processing apparatus of the present invention, the halftone processing unit is in the process of converting image data into multi-valued data including n values (n is an integer of 0 or more) and n + 1 values according to the density of the image data. After stopping the increase of n + 1 value pixels when the number of zero value pixels reaches a predetermined number in the multivalued data, the n + 2 value is placed at the same position as the n + 1 value according to the increase in the density of the image data. can do.

Further, in the image processing apparatus of the present invention, the halftone processing unit can perform halftone processing so that zero-value pixels are adjacent to one-value pixels and two or more single-value pixels are not continuous.

Further, in the image processing apparatus of the present invention, the halftone processing unit performs halftone processing so that the proportion of zero values included in the entire multivalued data decreases as the multivalued data corresponding to each pixel becomes large. be able to.

Further, in the image processing apparatus of the present invention, a binary error diffusion processing unit that performs binary error diffusion processing on image data can be provided before the halftone processing by the halftone processing unit, and the halftone processing can be performed. When performing the halftone processing, the unit can set the quantization value and the multi-valued data of the pixel determined to be white in the binary error diffusion processing unit to zero values.

Further, in the image processing apparatus of the present invention, a white pixel density adjustment process for adjusting the density of pixels determined to be white by the binary error diffusion process is performed before the binary error diffusion process by the binary error diffusion processing unit. A white pixel density adjusting unit to be applied to the data can be provided, and the binary error diffusion processing unit can perform binary error diffusion processing on the image data to which the white pixel density adjusting processing has been performed.

Further, in the image processing apparatus of the present invention, the binar error diffusion processing unit sets the quantization value of the pixel determined to be white as a negative value, and is 2 based on the negative value and the quantization value of the pixel determined to be black. A binar error diffusion process can be performed by setting a quantization threshold.

Further, in the image processing apparatus of the present invention, the brighter the density of the image data, the less the density of the pixels determined to be white.

1 Inkjet printing device 10 Image processing unit 11 Image data reception unit 12 Color conversion unit 13 Halftone processing unit 14 Two-value error diffusion processing unit 15 White pixel density adjustment unit 20 Head drive control unit 30 Inkjet head unit 40 Transport unit 50 Control unit

Claims (8)

The image data reception unit that accepts image data and the image data reception unit
It is provided with a halftone processing unit that performs halftone processing on the image data and converts it into at least three values or more to generate multi-valued data.
An image processing apparatus in which the halftone processing unit performs the halftone processing so as to always include a zero value, except when all the pixels constituting the image data are converted to the maximum value. In the process of the halftone processing unit converting the image data into multi-valued data including n-value (n is an integer of 0 or more) and n + 1 value according to the density of the image data, the multi-valued data. After stopping the increase of the n + 1 value pixels when the number of zero value pixels reaches a predetermined number, the n + 2 values are arranged at the same positions as the n + 1 values according to the increase in the density of the image data. The image processing apparatus according to claim 1. The image processing apparatus according to claim 2, wherein the halftone processing unit performs the halftone processing so that a zero-valued pixel is adjacent to a one-valued pixel and two or more single-valued pixels are not continuous. From claim 1, the halftone processing unit performs the halftone processing so that the proportion of the zero value included in the entire multivalued data decreases as the multivalued data corresponding to each pixel becomes larger. 3. The image processing apparatus according to any one of the following items. A binary error diffusion processing unit that performs binary error diffusion processing on the image data is provided before the halftone processing by the halftone processing unit.
The image processing according to claim 1, wherein when the halftone processing unit performs the halftone processing, the quantization value of the pixel determined to be white in the binary error diffusion processing unit and the multi-valued data are set to zero values. Device. Before the binary error diffusion processing by the binary error diffusion processing unit, the white pixel density adjusting unit that adjusts the density of the pixels determined to be white by the binary error diffusion processing is applied to the image data. Equipped with
The image processing apparatus according to claim 5, wherein the binary error diffusion processing unit performs binary error diffusion processing on the image data to which the white pixel density adjustment processing has been performed. The binary error diffusion processing unit sets the quantization value of the pixel determined to be white as a negative value, sets the quantization threshold based on the negative value and the quantization value of the pixel determined to be black, and makes a binary error. The image processing apparatus according to claim 5, which performs diffusion processing. The image processing apparatus according to claim 6 or 7, wherein the brighter the density of the image data, the sparser the density of the pixels determined to be white.

Images