JP6064523B2 - Gradation processing method, image forming apparatus, and program - Google Patents

Description

  The present invention relates to a gradation processing method, an image forming apparatus, and a program.

  As an image processing apparatus for processing image data, there are a personal computer and a workstation. Image data composed of various objects (for example, characters, fills, lines, or photographs) is formed by application software that operates in such an image processing apparatus.

As an image forming apparatus that forms and outputs the image data as an image, there are a printer, a facsimile, a copying apparatus, and a multi-function machine that combines these. Examples of the image forming method include an ink jet recording method and an electrophotographic method, and an image is formed using an image forming material such as a recording liquid (for example, ink) or toner.
Among such image forming apparatuses, apparatuses that perform digital image recording by an ink jet method have been rapidly developed and spread.

  In general, an ink jet recording apparatus includes a carriage on which recording means (for example, a print head) is mounted, a transport means for transporting recording paper, and a control means for controlling these.

  At present, there are so-called serial head method and line head method as ink jet recording methods.

  In the serial head method, a print head that discharges ink droplets from a plurality of ejection openings is serially scanned in the recording paper transport direction (also referred to as sub-scanning direction) and in the direction orthogonal to the transport direction (also referred to as main scanning direction). On the other hand, intermittent conveyance is performed at a predetermined amount during non-recording.

  In the line head system, a print head or a plurality of print heads corresponding to the print width are arranged, and a recording sheet is conveyed in one direction to form an image.

  Furthermore, in the case of a color-compatible inkjet recording apparatus, a color image is formed by superimposing ink droplets ejected from a plurality of color print heads.

  The line head method is a method in which a plurality of heads are arranged in the print width direction to widen the print width. Further, even in the serial head method, in order to increase the printing speed, there is a case where the printing width of one scan is widened by arranging a plurality of heads.

  In such a recording method, it is necessary to reduce the gradation value when converting the input gradation data into the output data. This is because dots are used to form an image, and the number of dots that can be expressed is limited.

In such a case, halftone processing is performed to simulate the input gradation. However, the pattern that can be expressed in the input image may be lost in the output image.
In order to compensate for such problems, various techniques have been proposed (see, for example, Patent Documents 1 and 2).

  The invention described in Patent Document 1 relates to an “image processing apparatus and program”, and specifically, “for forming an image of the input image data indicated by the first color system with a printer engine” In the image processing apparatus for converting to data, a first feature amount calculating means for calculating a first feature amount indicating a feature of a target pixel of image data indicated by the first color system, and a first color system Color conversion means for converting the indicated image data into image data indicated by the second color system, and a target pixel of the image data indicated by the second color system converted by the color conversion means Attention from the second feature quantity calculation means for calculating the second feature quantity indicating the feature, the first feature quantity calculated by the first feature quantity calculation means, and the second feature quantity calculated by the second feature quantity calculation means Third feature value for calculating a third feature value indicating the feature of the pixel Based on the third feature value calculated by the output means and the third feature value calculation means, it is determined whether the pixel of interest attaches importance to resolution or graininess, and the attention corresponding to the determination And halftone processing means for performing pixel quantization ”. In the invention described in Patent Document 1, the dither parameter is changed according to the input pattern.

  The invention described in Patent Document 2 relates to “an image processing apparatus, an image forming apparatus, a recording medium”, and specifically, “used to reproduce the color of a line segment constituting an input image. A maximum color specifying means for specifying the color of the color material having the maximum value as a maximum color among a plurality of color material colors, and a screen according to the drawing direction of the maximum color and the line segment specified by the maximum color specifying means Structure determining means for controlling parameters, and screen processing means for performing screen processing in accordance with the screen parameters controlled by the structure determining means. The structure determining means is a maximum at a screen angle different from the line drawing direction in the screen processing means. Control screen parameters so that color screen processing takes place ". In the invention described in Patent Document 2, when the input pattern is a line, the screen angle is changed according to the angle of the line.

The methods listed above can increase the probability for faithfully reproducing the input gradation data.
However, it cannot be said with certainty how much reproduction is possible with this method, and whether reproduction is possible with the maximum use of the gradation processing capability.
Further, when the output gradation is less than the input gradation, a process for reducing the gradation value is necessary.
When such halftone processing is performed, a pattern that can be expressed in the input image may be lost in the output image.

  SUMMARY OF THE INVENTION An object of the present invention is to provide a gradation processing method, an image forming apparatus, and a program that can reproduce an input image pattern to the maximum with an output image.

To solve the above problems, the invention according to claim 1 of the present application is a gradation processing method for performing gradation processing images data, said a first gradation processing before the first image data first By comparing with the second image data after the gradation processing, the loss degree of the information amount is calculated, and the second gradation process different from the first gradation process is performed according to the defect degree. The deficiency is reduced.

  According to the present invention, the input image pattern can be reproduced to the maximum with the output image.

It is a schematic block diagram of the whole mechanism part of an inkjet recording device. It is principal part plane explanatory drawing of an inkjet recording device. It is a perspective explanatory view explaining the head composition of an ink jet recording device. FIG. 2 is a schematic cross-sectional explanatory diagram of a conveyance belt of the ink jet recording apparatus illustrated in FIG. 1. (A) is a figure which shows a mode that a droplet is ejected to a paper from a recording head, (b) is what expanded the dot Di formation part of (a). 2 is an overall block diagram of a control unit of the image forming apparatus. FIG. It is a block diagram which shows an example of an image processing apparatus. It is an example of the flowchart for demonstrating the process of the halftone in one Embodiment. It is another example of the flowchart for demonstrating the process of the halftone in one Embodiment. It is explanatory drawing about normal gradation processing. It is explanatory drawing of calculation of the correction | amendment pixel value in an error diffusion process. It is explanatory drawing of the gradation process which concerns on one Embodiment. It is explanatory drawing of an example of the gradation process by a threshold value mask. It is explanatory drawing about an example of the gradation process [rotation process] by error diffusion. It is explanatory drawing about the example of calculation of the defect degree for knowing how faithfully the image is reproduced. It is explanatory drawing which shows an example of the gradation process by a threshold value mask. It is explanatory drawing which shows an example of the gradation process [rotation process] by a threshold value mask. It is explanatory drawing which shows an example of the gradation process by error diffusion. It is explanatory drawing which shows an example of the gradation process [rotation process] by error diffusion. It is explanatory drawing which shows an example of the gradation process 2 by a threshold value mask. It is explanatory drawing which shows an example of the gradation process 2 [placement change] by a threshold mask. It is explanatory drawing which shows an example of the gradation process 2 by error diffusion. It is explanatory drawing which shows an example of the gradation process 2 [placement change] by error diffusion. It is explanatory drawing which shows an example of the gradation process 3 [threshold mask change] by a threshold mask. It is explanatory drawing which shows an example of the gradation process 3 by error diffusion. It is explanatory drawing which shows an example of the gradation process 3 [threshold mask change] by error diffusion.

The present embodiment is applied to a process of reducing the gradation value when the output gradation is less than the input gradation. This includes preventing the pattern that has been expressed in the input image from being lost in the output image by calculating the degree of reproduction and performing gradation processing switching that maximizes the degree of reproduction.
The following embodiment is a so-called dither mask method, but any method can be applied as long as it is a process for reducing the gradation value when the output gradation is smaller than the input gradation.

<Embodiment 1>
The first embodiment will be described.
[Constitution]
First, an example of an ink jet recording apparatus as an image forming apparatus to which the present invention is applied will be described with reference to FIGS. Details of the present invention are described after this description.
FIG. 1 is a schematic configuration diagram of the entire mechanism unit of the ink jet recording apparatus, and FIG. 2 is a plan view of a main part of the ink jet recording apparatus. FIG. 3 is a perspective explanatory view for explaining a head configuration of the ink jet recording apparatus, and FIG. 4 is a schematic cross-sectional explanatory view of a conveyance belt of the ink jet recording apparatus shown in FIG.

  This ink jet recording apparatus has an image forming unit 2 inside the apparatus main body 1, and a paper feed tray 4 on which a large number of recording media (hereinafter referred to as “paper”) 3 can be stacked below the apparatus main body 1. I have. The ink jet recording apparatus takes in the paper 3 fed from the paper feed tray 4, records a required image by the image forming unit 2 while transporting the paper 3 by the transport mechanism 5, and then moves to the side of the apparatus main body 1. The sheet 3 is discharged to the mounted discharge tray 6.

  In addition, the ink jet recording apparatus includes a duplex unit 7 that can be attached to and detached from the apparatus main body 1. When performing duplex printing, the sheet 3 is transported in the reverse direction by the transport mechanism 5 after completion of one-surface (front surface) printing. The sheet is taken into the duplex unit 7, reversed, and sent to the transport mechanism 5 again as the other side (back side) as a printable side. After the other side (back side) printing is completed, the sheet 3 is discharged to the discharge tray 6.

  Here, the image forming unit 2 slidably holds the carriage 13 on the guide shafts 11 and 12, and moves the carriage 13 in a direction orthogonal to the conveyance direction of the paper 3 (main scanning) by a main scanning motor (not shown). . The carriage 13 is equipped with a recording head 14 composed of a droplet discharge head in which nozzle holes 14n (see FIG. 3) as a plurality of discharge ports for discharging droplets are arranged. The ink cartridge 15 for supplying the ink is detachably mounted. Note that a sub tank may be mounted in place of the ink cartridge 15 so that ink is replenished and supplied from the main tank to the sub tank.

  Here, as the recording head 14, for example, as shown in FIGS. 2 and 3, droplets that eject ink droplets of each color of yellow (Y), magenta (M), cyan (C), and black (Bk). Four independent inkjet heads 14y, 14m, 14c, and 14k, which are ejection heads, are provided. The recording head 14 may be configured to use one or a plurality of heads having a plurality of nozzle rows that eject ink droplets of each color. The number of colors and the order of arrangement are not limited to this.

  Examples of the inkjet head constituting the recording head 14 include a thermal actuator that uses a phase change due to film boiling of a liquid using a piezoelectric actuator such as a piezoelectric element or an electrothermal conversion element such as a heating resistor. In addition, a shape memory alloy actuator using a metal phase change due to a temperature change, an electrostatic actuator using an electrostatic force, and the like can be used as energy generating means for discharging ink.

  As the electrothermal conversion element, it is possible to use an electrothermal conversion element having a non-linear characteristic in which the resistance value hardly changes even when a low voltage is applied and the resistance value greatly changes when a voltage of a certain level or more is applied.

  In an electrothermal conversion element having a linear characteristic, when a plurality of heat generating means are selectively driven, noise voltage is applied to the non-selected heat generating means, energy is wasted, and the drive voltage is affected to affect the ink. There is a possibility that the discharge amount may change and affect the recorded image.

  In particular, in an inkjet recording head that applies voltages to a plurality of vertical wirings and a plurality of horizontal wirings and selectively drives heating means arranged in a matrix at intersections of the vertical wirings and the horizontal wirings, the driving process In some cases, a voltage lower than the drive voltage is applied to the non-selected heat generating means. When this drive voltage is in the forward direction, unnecessary heat generation occurs in the non-selected heat generating means. If unnecessary heat is generated and heat is accumulated, if it is heated when it is ejected, it will generate more heat than specified, and as a result, an excessive amount of ink will be ejected. As a result, the ink discharge amount varies from nozzle to nozzle.

  However, if an electrothermal conversion element having non-linear characteristics is used, even if a voltage lower than the driving voltage such as noise is applied to the heating means, unnecessary heat generation does not occur. Graininess and gradation are improved. Moreover, since unnecessary heat generation can be prevented, waste of energy can be prevented.

  Further, the resistance value of each electrothermal conversion element of the recording head can be measured, and the drive voltage applied to each electrothermal conversion element can be adjusted based on the resistance value. In particular, when the recording head is lengthened, the resistance value of the electrothermal conversion element for each nozzle tends to vary, and as a result, the amount of ejected ink varies. However, by adjusting the applied voltage by feeding back the resistance value of each electrothermal resistance element, it is possible to eject ink droplets of a target size.

  Furthermore, when a thermal recording head is used, a protective layer may be provided on the electrothermal conversion element (discharge energy generator). By providing the protective layer, erosion by ink, kogation (burning of ink components) and cavitation (destruction due to impact when bubbles shrink) do not directly act on the electrothermal conversion element. Since the electrothermal conversion element is not damaged, the life of the electrothermal conversion element can be extended.

  The sheets 3 in the sheet feeding tray 4 are separated one by one by a sheet feeding roller (also referred to as half-moon roller) 21 and a separation pad (not shown), fed into the apparatus main body 1, and sent to the transport mechanism 5.

  The transport mechanism 5 includes a transport guide portion 23, a transport roller 24, a pressure roller 25, guide members 26 and 27, and a pressing roller 28.

  The transport mechanism 5 guides the fed paper 3 upward along the guide surface 23a. The conveyance guide unit 23 guides the sheet 3 fed from the duplex unit 7 along the guide surface 23b. The transport roller 24 transports the paper 3. The pressure roller 25 presses the paper 3 against the transport roller 24. The guide member 26 guides the sheet 3 to the conveyance roller 24 side. The guide member 27 guides the sheet 3 returned at the time of duplex printing to the duplex unit 7. The pressing roller 28 presses the paper 3 fed from the transport roller 24.

  Further, the transport mechanism 5 includes a transport belt 33 stretched between the driving roller 31 and the driven roller 32, a charging roller 34, a guide roller 35 facing the charging roller 34, and a guide member (plastic template) (not shown). And a cleaning roller.

  The transport belt 33 is a belt for transporting the recording head 14 while maintaining the flatness of the paper 3. The charging roller 34 is a roller for charging the transport belt 33. The guide member (plastic template) guides the conveyance belt 33 at a portion facing the image forming unit 2. The cleaning roller is made of a porous material or the like that is a cleaning unit for removing the recording liquid (ink) attached to the conveyance belt 33.

  Here, the conveyance belt 33 is an endless belt, and is stretched between the driving roller 31 and the driven roller (tension roller) 32 so as to circulate in the direction indicated by the arrow in FIG. 1 (paper conveyance direction). It is composed.

  The conveyor belt 33 can be configured as a single layer, or as shown in FIG. 4, a two-layer configuration of a first layer (outermost layer) 33a and a second layer (back layer) 33b, or a configuration of three or more layers. . For example, the transport belt 33 is a surface layer that is a sheet adsorbing surface formed of a pure resin material having a thickness of about 40 μm that is not subjected to resistance control, for example, ETFE pure material, and resistance control by carbon using the same material as the surface layer. It consists of the back layer (medium resistance layer, earth layer) performed.

  The charging roller 34 is disposed so as to come into contact with the surface layer of the transport belt 33 and to rotate following the rotation of the transport belt 33. A voltage is applied to the charging roller 34 in a predetermined pattern from a high voltage circuit (high voltage power source) (not shown).

  Further, on the downstream side from the transport mechanism 5, a paper discharge roller 38 for sending the paper 3 on which an image is recorded to the paper discharge tray 6 is provided.

  In the image forming apparatus configured as described above, the conveyance belt 33 is circulated in the direction of the arrow, and is positively charged by coming into contact with the charging roller 34 to which a high potential application voltage is applied. In this case, the charging roller 34 is charged at a predetermined charging pitch by switching the polarity at predetermined time intervals.

  Here, when the paper 3 is fed onto the conveying belt 33 charged at this high potential, the inside of the paper 3 is in a polarized state, and the electric charge having the opposite polarity to the electric charge on the conveying belt 33 is connected to the belt 33 of the paper 3. Dielectrically in contact with the surface. The charges on the belt 33 and the charges charged on the conveyed paper 3 are electrostatically attracted to each other, and the paper 3 is electrostatically attracted to the conveying belt 33. In this way, the sheet 3 strongly adsorbed to the transport belt 33 is calibrated for warpage and unevenness, and a highly flat surface is formed.

Therefore, the recording belt 14 is moved around the conveyor belt 33 and the recording head 14 is driven according to the image signal while moving and scanning the carriage 13 in one direction or in both directions, as shown in FIGS. As shown, droplets 14 i are ejected (jetted) from the recording head 14. In this way, ink droplets that are droplets are landed on the stopped paper 3 to form dots Di, so that one line is recorded, and after the paper 3 is conveyed by a predetermined amount, the next line is recorded. Do. When the recording end signal or the signal that the rear end of the paper 3 reaches the recording area is received, the recording operation is ended.
FIG. 5A is a diagram illustrating a state in which droplets are ejected from a recording head onto a sheet, and FIG. 5B is an enlarged view of a dot Di formation portion in FIG. .
In this way, the sheet 3 on which the image is recorded is discharged to the discharge tray 6 by the discharge roller 38.

Next, an outline of the control unit of the image forming apparatus will be described with reference to FIG. FIG. 6 is an explanatory block diagram of the entire control unit of the image forming apparatus.
The control unit 100 includes a CPU (Central Processing Unit) 101, a ROM (Read-Only Memory) 102, a RAM (Random-Access Memory) 103, a nonvolatile memory 104, and an ASIC (Application Specific Integrated Circuit) 105. Examples of the nonvolatile memory 104 include NVRAM (Non-Volatile RAM).

The CPU 101 is a device that controls the entire apparatus, such as a microprocessor. The CPU 10 includes calculation means and gradation means that are configured by software. The calculation means has a function of comparing the input gradation data and the output gradation data to calculate the degree of information loss. The gradation means has a function of reducing the defect level by performing a gradation process different from the prescribed gradation process according to the defect level.
The ROM 102 is a device that stores a program executed by the CPU 101 and other fixed data, and includes, for example, a mask ROM. The RAM 103 is a device that temporarily stores image data and the like, and examples thereof include a DRAM (Dynamic RAM) or an SRAM (Static RAM). The non-volatile memory (NVRAM) 104 is a device for holding data even when the power of the apparatus is shut off, and includes, for example, a flash memory. The ASIC 105 is a device that processes input / output signals for controlling various types of signal processing, rearrangement, and other image processing and other devices.

  The control unit 100 includes an I / F (Inter Face) 106, a head drive control unit 107, a head driver 108, a main scanning motor driving unit 111, a sub scanning motor driving unit 123, a subsystem driving unit (not shown), an environmental sensor 118, and An I / O (Input / Output) 116 is provided.

  The I / F 106 is a device for transmitting and receiving data and signals to and from the host 90 which is an image processing apparatus such as a personal computer, and includes, for example, a SCSI (Small Computer System Interface). The head drive control unit 107 and the head driver 108 are devices for driving and controlling the recording head 14. The main scanning motor driving unit 111 is a device for driving the main scanning motor 110. The sub scanning motor driving unit 123 is a device for driving the sub scanning motor 112. The subsystem drive unit is a device for driving a motor of a subsystem not shown in the drawing. The environmental sensor 118 detects environmental temperature and / or environmental humidity. The I / O 116 is a device for inputting detection signals from the environment sensor 118 and various sensors (not shown).

  The control unit 100 is connected to an operation panel 117 for inputting and displaying information necessary for the apparatus. Further, the control unit 100 performs on / off switching and output polarity switching control of a high-voltage circuit (also referred to as a high-voltage power supply) 114 that applies a voltage to the charging roller 34.

  Here, the control unit 100 receives print data including image data from the host 90 side such as a data processing device such as a personal computer, an image reading device such as an image scanner, and an imaging device such as a digital camera via a cable or a network. Received by the I / F 106. It should be noted that the print data generation output for the control unit 100 is performed by the printer driver 91 according to the present invention on the host 90 side.

  The CPU 101 reads and analyzes the print data in the reception buffer included in the I / F 106, performs data rearrangement processing by the ASIC 105, and transfers the image data to the head drive control unit 107. For conversion of print data for image output into bitmap data, the printer driver 91 on the host 90 side develops the image data into bitmap data and transfers it to this apparatus. This may be performed by storing font data in the ROM 102, for example.

  When the head drive control unit 107 receives image data (also referred to as dot pattern data) corresponding to one row of the recording head 14, the head driver 108 synchronizes the dot pattern data for one row in synchronization with the clock signal. Serial data is sent to the head driver 108 at a predetermined timing.

  The head drive control unit 107 includes a ROM (which can also be constituted by the ROM 102) storing drive waveform pattern data, also called drive signals, and D / A (Digital to Digital) drive waveform data read from the ROM. Analog) includes a waveform generation circuit including a D / A converter for conversion and a drive waveform generation circuit including an amplifier and the like.

  The head driver 108 includes a shift register, a latch circuit, a level conversion circuit, and an analog switch array, and drives the head by selectively applying a drive waveform to the actuator means of the recording head 14 by on / off control of the analog switch array. .

  The shift register is a device that inputs a clock signal from the head drive control unit 107 and serial data that is image data. The latch circuit is a circuit that latches the registration value of the shift register with a latch signal from the head drive control unit 107. The level conversion circuit is also called a level shifter and is a circuit that changes the output value of the latch circuit. The analog switch array is also referred to as switch means, and is turned on / off by a level shifter.

The image forming apparatus can also perform printing without providing a margin for at least a part of the edge of the recording medium. In printing, in order to print the edge portion, an ordinary image forming apparatus discharges ink to the outside of the recording medium. The ink is ejected in such a way that even if the ink is ejected so as to be printed up to the surface position of the edge of the recording medium, the ideal landing position is actually caused by the feeding error of the transport system of the recording medium or the driving error of the carriage. In many cases, the ink cannot be landed on the screen, which creates a margin. For this reason, printing is performed wider than ideal considering the error of the printing position, and as a result, ink is ejected to the outside of the recording medium.
At this time, the ink that protrudes from the recording medium does not contribute to the recording, and is a wasteful consumption of ink. Therefore, there is a demand for reducing the protruding ink as much as possible.

  Therefore, as a method for reducing the protruding ink, for example, there is a method for increasing the conveyance accuracy of the recording medium. This method is to reduce useless protruding ink by increasing the conveyance accuracy and reducing the estimated protruding area. Specifically, when printing the edge of the recording medium, it is possible to increase the conveyance accuracy by making the feeding of the recording medium minute.

Next, an example of an image processing apparatus including a printer driver on the host side that transfers image data to form an image by the image forming apparatus will be described with reference to FIG.
FIG. 7 is a block diagram illustrating an example of an image processing apparatus.
The printer driver 91 of the data processing apparatus includes a CMM (Color Management Module) processing unit 131, a BG / UCR (Black Generation / Under Color Removal) processing unit 132, a γ correction unit 133, a zooming unit 134, and halftone processing. Part 135 is included.

  The CMM processing unit 131 is a circuit that converts the image data 130 supplied from application software or the like from a monitor display color space to a recording device color space (RGB color system → CMY color system). The BG / UCR processing unit 132 is a circuit that performs black generation / undercolor removal from CMY values. The γ correction unit 133 is a circuit that performs input / output correction that reflects the characteristics of the recording apparatus and user preferences. The zooming unit 134 is a circuit that performs enlargement processing in accordance with the resolution of the recording apparatus. It includes a multi-value / low-value matrix that replaces the image data with a pattern arrangement of dots ejected from the printing apparatus.

[Operation]
FIG. 8 is an example of a flowchart for explaining halftone processing according to an embodiment.
The subject of operation is the CPU 101.
When halftone processing is started, the processing range is determined. The vertical and horizontal sizes are M × N pixels (step S1).
Normal gradation processing described later is executed (step S2).
The degree of deficiency is calculated (step S3).
It is determined whether the defect level is equal to or less than a threshold value or 0 (step S4). If the defect level is equal to or less than the threshold value or 0 (step S4 / Yes), it is determined whether gradation processing for all pixels of the input image is completed. (Step S5). If the missing degree is equal to or less than the threshold value or not 0 (step S4 / No), the missing degree minimizing process is performed (step S6), and the process proceeds to step S5.
When the gradation processing for all the pixels of the input image has not been completed (step S5 / No), the process returns to step S1, and when the gradation processing has been completed (step S5 / Yes), the halftone processing is terminated.
In FIG. 8, when filtering processing using a threshold mask is performed, the processing content is preferably a size equivalent to the mask size. When performing other processing, the processing range may be determined according to the processing speed and processing capacity.

FIG. 9 is another example of a flowchart for explaining halftone processing in an embodiment.
The subject of operation is the CPU 101.
When halftone processing is started, normal gradation processing is executed (step S11).
Determine the processing range. The vertical and horizontal sizes are M × N pixels (step S12).
The deficiency is calculated (step S13).
It is determined whether the defect level is equal to or less than a threshold value or 0 (step S14). If the defect level is equal to or less than the threshold value or 0 (step S14 / Yes), it is determined whether gradation processing for all pixels of the input image is completed. (Step S15). If the missing degree is equal to or less than the threshold value or not 0 (No in step S14), the missing degree minimizing process is performed (step S16), and the process proceeds to step S5.
When the gradation processing for all the pixels of the input image has not been completed (step S15 / No), the process returns to step S1, and when the gradation processing has been completed (step S15 / Yes), the halftone processing is terminated.
In FIG. 9, the processing content may be determined according to the processing speed and processing content.

  FIG. 10 is an explanatory diagram of normal gradation processing.

Here, normal gradation processing will be described. As shown in FIG. 10, in the normal gradation processing, the input image and the threshold mask are compared, and two gradations are obtained to obtain a temporary output image.
As described above, the gradation process is a process of converting an input gradation to an output gradation, and usually the number of input gradations> the number of output gradations. Two typical gradation processes are shown below. That is, gradation processing using a threshold mask and gradation processing using error diffusion. Applying the following processing to the entire input image is normal gradation processing.

FIG. 11 is an explanatory diagram for calculating a correction pixel value in the error diffusion processing.
In the upper part of FIG. 11, black circles indicate pixels that are turned on by error diffusion processing, white circles indicate pixels that are turned off by error diffusion processing, and numbers indicate unprocessed pixels.

In the next stage of FIG. 11, e _xy indicates an error generated in the n-value conversion process, * indicates a pixel of interest, and a number indicates an unprocessed pixel.

  In the next stage of FIG. 11, the corrected pixel value is calculated by multiplying the error value of the processed peripheral pixel by the following weight and adding it to the value of the next pixel to be processed.

When the error weight matrix shown in the lower part of FIG. 11 is multiplied by 1/16, a correction value D _xy represented by Expression (1) is obtained.
Here, the threshold value and the correction data are compared, and the error value (e ₃₂ ) of dot ON / OFF and the position of the target pixel is calculated.
When threshold value = 128 and correction value D _xy = 160, D _xy is equal to or greater than the threshold value. Therefore, when the output value at dot ON is 255, e ₃₂ is −95.

<Embodiment 2>
Embodiment 2 will be described.
This embodiment is applied to a process of reducing the gradation value when the output gradation is less than the input gradation. In the present embodiment, by calculating the reproduction degree and switching the gradation processing that maximizes the reproduction degree, the pattern that can be expressed in the input image is prevented from being lost in the output image.

The example shown below is a so-called dither mask method, but any method can be applied as long as the gradation value is reduced when the output gradation is smaller than the input gradation.
FIG. 12 is an explanatory diagram of gradation processing according to an embodiment.
This embodiment is an example of gradation processing using a threshold mask. Hereinafter, the case where the number of input gradations is 10 and the number of output gradations is 2 will be described.
For example, in the case where the process is changed, the input image shown in the upper part of FIG. Since this temporary output image has 3 input data dots and 1 output data dots, the missing degree is 1.
When the input image at the upper left in FIG. 12 is rotated at 90 ° as the rotation angle that minimizes the degree of deficiency, the input image shown at the lower left in FIG. 12 is obtained. An output image as shown in the lower right of 12 is obtained. Since this output image has 3 input data dots and 3 output data dots, the missing degree is 0. When this output image is rotated by −90 °, an output image having no missing data as shown in the upper right of FIG. 12 is obtained.

  Here, details of the rotation processing will be described. For example, as shown in FIG. 13, the input image is rotated in increments of 45 °, gradation processing is performed, the missing degree is calculated, and the rotation with the smallest missing degree is found. Next, data obtained by reversely rotating the data output by the processing is output (see FIG. 12).

<Embodiment 3>
A third embodiment will be described.
FIG. 13 is an explanatory diagram of an example of gradation processing using a threshold mask.
It is explanatory drawing about an example of the gradation process [rotation process] by.
As an example of the rotation process, the input image shown in the upper left of FIG. 13 is subjected to a rotation process, compared with a threshold mask, converted into two gradations, and the missing degree is calculated. When the input image is rotated by 45 ° and 90 ° and gradation processing is performed, the degree of deficiency is minimized. When the input image is rotated by 45 ° or 90 °, data loss is minimized.
Examples of the rotation angle include, but are not limited to, 45 °, 90 °, and 135 °. When the rotation processing angle is 45 ° or 90 °, the defect degree is 0, and when the rotation processing angle is 135 °, the defect degree is 1.

<Embodiment 4>
A fourth embodiment will be described.
Next, an example in which error diffusion processing is applied to the present technology will be shown.
In the case of error diffusion, the concept is the same as that of the mask processing described above except that the gradation processing is error diffusion.
FIG. 14 is an explanatory diagram of an example of gradation processing [rotation processing] by error diffusion.
As an example of the rotation process, when the input image shown in the upper left of FIG. 14 is subjected to the rotation process and the loss degree of the temporary output image obtained by directly converting the gradation into two gradations is calculated, The degree becomes 0, and the defect degree becomes 1 at the time of 135 ° rotation processing.

<Embodiment 5>
Embodiment 5 will be described.
FIG. 15 is an explanatory diagram of an example of calculating the degree of loss to know how faithfully an image can be reproduced.
The degree of deficiency is calculated as follows.
When the input gradation data of the input image shown in FIG. 15 is P _in and the output gradation data of the temporary output image is P ′ _out , a predetermined range of K × (P _in −M × P ′ _out ). The sum is calculated (M, K: coefficients), and the deficiency is 2.

<Embodiment 6>
Embodiment 6 will be described.
When the degree of deficiency is large, it is determined that information deficiency has occurred, and the process proceeds to processing for compensating for information deficiency.
If the threshold value of the defect level, which is a condition for shifting to compensation processing, is reduced, more accurate reproduction is possible, but the processing time increases. The threshold value may be determined depending on which of processing time and faithful reproduction is important.

<Embodiment 7>
Embodiment 7 will be described.
The process for compensating for the information loss is a process with the smallest loss level. This processing enables faithful reproduction of input gradation data.

<Embodiment 8>
Embodiment 8 will be described.
There are the following methods as processing for compensating for information loss.
The input gradation data within a predetermined range is rotated, prescribed gradation processing is performed, the angle with the least information loss is R ° (R: 0 to 360 °), and the gradation processing data at that time is −R °. The rotated data is used as output gradation data. The example shown in FIG. 16 is a so-called dither mask method, but any method can be applied as long as the gradation value is reduced when the output gradation is smaller than the input gradation.
FIG. 16 is an explanatory diagram illustrating an example of gradation processing using a threshold mask.
In the case of changing the processing, the input image shown in the upper left of FIG. 16 is compared with the threshold mask, and when the gradation is changed to two gradations, a temporary output image is obtained. In this case, since the number of input data dots is 3 and the number of output data dots is 1, the degree of deficiency is 2.
When the input image shown at the upper left in FIG. 16 is rotated by 90 ° as the rotation angle at which the deficiency is minimized, the image shown at the lower left of FIG. 16 is obtained.
When the input image shown in the lower left of FIG. 16 is compared with the threshold mask to make two gradations, the output image shown in the lower right of FIG. 16 is obtained. In this output image, since the number of input data dots is 3 and the number of output data is 3, the missing degree is 0. When this output image is rotated by −90 °, an output image having no missing data as shown in the upper right of FIG. 16 is obtained.

Here, details of the rotation processing will be described.
For example, as shown in FIG. 17, the input image is rotated in increments of 45 °, gradation processing is performed, the missing degree is calculated, and the rotation with the smallest missing degree is found.
Next, data obtained by reversely rotating the data output in the processing is output (see FIG. 16).

<Ninth Embodiment>
Embodiment 9 will be described.
FIG. 17 is an explanatory diagram showing an example of gradation processing [rotation processing] using a threshold mask.
The input image shown in the upper left of FIG. 17 is rotated at a predetermined rotation angle, compared with a threshold mask, and converted into two gradations, a temporary output image group as shown in the middle to lower parts of FIG. 17 is obtained. When the input image is rotated by 45 ° and 90 ° and gradation processing is performed, the missing degree is minimized. Further, when the input image is rotated by 45 ° or 90 °, data loss is minimized.
That is, when the input image shown in the upper left of FIG. 17 is rotated by 45 °, compared with the threshold mask, and the loss degree of the temporary output image obtained by two gradations is calculated, the number of input data dots is 3, and the output data The number of dots is 3, and the deficiency is 0.
The input image shown in the upper left of FIG. 17 is rotated by 90 °, compared with the threshold mask, and the missing degree of the temporary output image obtained by two gradations is calculated to be 0.
The input image shown in the upper left of FIG. 17 is rotated by 135 °, compared with the threshold mask, and when the missing degree of the temporary output image obtained by two gradations is calculated, the number of input data dots is 3, and the number of output data dots Is 2, and the deficiency is 1.

Next, an example in which error diffusion processing is applied will be shown.
<Embodiment 10>
Embodiment 10 will be described.
FIG. 18 is an explanatory diagram showing an example of gradation processing by error diffusion.
When the input image shown in the upper left of FIG. 18 is subjected to two gradations by error diffusion, a temporary output image is obtained. Since this temporary output image has 3 input data dots and 1 output data dots, the missing degree is 2.
When the input image is rotated at 90 ° as the rotation angle at which the degree of deficiency is minimum, the image shown in the lower left of FIG. 18 is obtained when the deficiency is minimum, and as shown in the lower right of FIG. An output image can be obtained. Since this output image has 3 input data dots and 3 output data dots, the missing degree is 0. When this output image is rotated by −90 °, an output image with no missing data is obtained as shown in the upper right of FIG.

  Even when error diffusion is performed on the input image, the concept is the same as that of the mask processing described above except that gradation processing is error diffusion.

<Embodiment 11>
Embodiment 11 will be described.
FIG. 19 is an explanatory diagram showing an example of gradation processing [rotation processing] by error diffusion.
When the input image shown in the upper left of FIG. 19 is subjected to a rotation process at a predetermined rotation angle and subjected to two gradations by error diffusion, a temporary output image shown in the middle to the lower of FIG. 19 is obtained. When the input image is rotated by 45 ° and 90 ° and gradation processing is performed, the missing degree is minimized, and when the input image is rotated by 45 ° and 90 °, data loss is minimized.
There are the following methods as processing for compensating for information loss.
There is a method in which the arrangement of input gradation data within a predetermined range is changed, prescribed gradation processing is performed, and the arrangement of gradation processing data at that time is further changed.
The following example is a so-called dither mask method, but any method can be applied as long as the gradation value is reduced when the output gradation is smaller than the input gradation.

<Twelfth embodiment>
Embodiment 12 will be described.
FIG. 20 is an explanatory diagram showing an example of gradation processing 2 using a threshold mask.
In the case of changing the process, when the input image shown in the upper left of FIG. 20 is compared with the threshold mask and two gradations are applied, a temporary output image is obtained. Since this temporary output image has 3 input data dots and 0 output data dots, the missing degree is 3.
When the arrangement of the input gradation data is changed so that the degree of deficiency is minimized in the input image shown in the upper left of FIG. 20, an input image as shown in the lower left of FIG. 20 is obtained. When this input image is compared with a threshold mask and two gradations are applied, a temporary output image as shown in the lower right of FIG. 20 is obtained. Since this temporary output image has 3 input data dots and 2 output data dots, the missing degree is 1. When the arrangement of the temporary output image is returned to the original position, an output image with no missing data as shown in the upper right of FIG. 20 is obtained.

Here, the details of the arrangement change will be described.
For example, as shown in FIG. 21, the data position of the input image is sequentially changed, gradation processing is performed, the missing degree is calculated, and the case where the missing degree is the smallest is found.
Next, data obtained by returning the data output in the process to the original position is output (see FIG. 20).

<Embodiment 13>
Embodiment 13 will be described.
FIG. 21 is an explanatory diagram showing an example of gradation processing 2 [change arrangement] using a threshold mask.
When the input image shown in the upper left of FIG. 21 is subjected to a predetermined arrangement change, compared with the threshold mask, and subjected to two gradations, a temporary output image as shown from the middle to the lower of FIG. 21 is obtained. The calculation result of the loss degree of each temporary output image is shown on the right side of FIG. The deficiency of replacement 1 is minimized. As a judgment example, it can be seen that it is possible to reproduce a maximum of 2 dots by trying all replacement combinations or by comparing the number of input gradations with a threshold value.

An example of error diffusion is shown below.
<Embodiment 14>
Embodiment 14 will be described.
FIG. 22 is an explanatory diagram showing an example of gradation processing 2 by error diffusion.
When the input image shown in the upper left of FIG. 22 is subjected to two gradations by error diffusion, a temporary output image shown in the upper part of FIG. 22 is obtained. Since this temporary output image has 3 input data dots and 0 output data dots, the missing degree is 3.
By changing the arrangement of the input gradation data so that the missing degree is minimized in the input image shown in the upper left of FIG. 22, an input image having the smallest missing degree is obtained. The provisional output image shown in the lower right of FIG. 22 is obtained by applying two gradations by error diffusion to the input image. By returning the arrangement of the temporary output image to the original, an output image with no data missing as shown in the upper right of FIG. 22 is obtained.

  In the case of error diffusion, the concept is the same as that of the mask processing described above except that the gradation processing is error diffusion.

<Embodiment 15>
Embodiment 15 will be described.
FIG. 23 is an explanatory view showing an example of gradation processing 2 [placement change] by error diffusion.
A temporary output image group is obtained by changing the arrangement of the input image shown in the upper left of FIG. The calculation result of the degree of loss of each temporary output image is shown on the right side of FIG. The degree of deficiency of replacement 1 is the smallest, and a method for finding this condition is to try all replacement combinations.

The following methods can be cited as processing for compensating for information loss.
In this method, the gradation processing within a predetermined range is changed so as to minimize the deficiency, and the prescribed gradation processing is performed.
The following example is a so-called dither mask method, but any method can be applied as long as the gradation value is reduced when the output gradation is smaller than the input gradation.

  Here, details of the threshold mask change will be described. For example, as shown in FIG. 24, the data position of the threshold mask is sequentially changed, gradation processing is performed, the missing degree is calculated, and the case where the missing degree is the smallest is found. The processed data is output (see FIG. 23).

<Embodiment 16>
Embodiment 16 will be described.
FIG. 24 is an explanatory diagram showing an example of gradation processing 3 [threshold mask change] using a threshold mask.
The arrangement of the threshold masks shown in the upper left of FIG. 24 is changed, the threshold masks 1 to N are compared with the input image, and each of the two gradations is used to obtain a temporary output image group. The calculation result of the loss degree of each temporary output image is shown on the right side of FIG.
It can be seen that the missing degree of the threshold mask 1 is the smallest. As an example of determination, try a full replacement combination, or the number of dots in the input image is 3, and the number of gradations is 2, 2, 2. It can be seen that a maximum of 2 dots can be reproduced by comparing the input gradation numbers 2, 2, and 2 with the threshold values 1, 2, and 3.
An example of error diffusion is shown below.

<Embodiment 17>
Embodiment 17 will be described.
FIG. 25 is an explanatory diagram showing an example of gradation processing 3 by error diffusion.
The provisional output image as shown in the upper part of FIG. 25 is obtained by converting the input image shown in the upper left part of FIG. 25 into two gradations by error diffusion. Since this temporary output image has 3 input data dots and 0 output data dots, the missing degree is 3.
The input image shown in the upper left of FIG. 25 is divided into two gradations, and the error diffusion processing parameters are changed so that the deficiency is minimized. When the degree of deficiency of the input image shown in the lower left of FIG. 25 is the minimum, a provisional output image as shown in the lower right of FIG. 25 is obtained by applying two gradations to the input image by error diffusion. Since this temporary output image has 3 input data dots and 2 output data dots, the missing degree is 1. By returning the error diffusion processing parameters of the temporary output image, an output image having no missing data as shown in the upper right of FIG. 25 can be obtained.

Here, details of the parameter change will be described.
For example, as shown in FIG. 26, the parameter set is sequentially changed, gradation processing is performed, the missing degree is calculated, and the case where the missing degree is the smallest is found. The processed data is output (see FIG. 25).
The parameter set in this example is obtained by sequentially changing the arrangement of the error weight matrix values.

<Embodiment 18>
Embodiment 18 will be described.
FIG. 26 is an explanatory diagram showing an example of gradation processing 3 [threshold mask change] by error diffusion.
A temporary output image group is obtained by changing the parameter set 0 to be the parameter set 1 to the parameter set N and performing two gradations by error diffusion. The calculation result of the degree of defect of each temporary output image is shown on the right side in FIG.
The loss degree of parameter set 1 is the smallest. One way to find this condition is to try all the replacement combinations.

<Others>
The present invention can be applied to various forms.
For example, it can be stored in a recording device and connected to the recording device when necessary. Alternatively, it can be realized as a recording system including a recording apparatus. Further, it can be realized as a program, executed by a personal computer or the like, and transmitted to the recording device. Alternatively, the above-described program can be recorded on a recording medium.

<Program>
The image processing apparatus according to the present invention described above is realized by a program that causes a computer to execute processing. Examples of the computer include general-purpose computers such as personal computers and workstations, but the present invention is not limited to this. Therefore, as an example, a case where the present invention is realized by a program will be described below.

For example,
A program for controlling an image forming apparatus that performs gradation processing for converting the number of input gradations of input image data into output gradations,
In the substantial computer of the image forming apparatus,
A procedure in which the calculation means compares the input gradation data and the output gradation data to calculate the degree of information loss;
The gradation means reduces the deficiency by performing gradation processing different from the specified gradation processing according to the deficiency,
A program that executes

Thus, the image processing apparatus according to the present invention can be realized anywhere as long as there is a computer environment capable of executing the program.
Such a program may be stored in a computer-readable storage medium.

<Storage medium>
Examples of the storage medium include storage media such as CD-ROM (Compact Disc ROM), flexible disk (FD), CD-R (CD Recordable), semiconductor memory such as flash memory, RAM, ROM, ferroelectric memory, and HDD ( Hard Disc Drive).

  The above-described embodiment shows an example of a preferred embodiment of the present invention, and the present invention is not limited thereto, and various modifications can be made without departing from the scope of the invention. is there.

DESCRIPTION OF SYMBOLS 1 Apparatus main body 2 Image formation part 3 Recording medium (it is also called paper)
DESCRIPTION OF SYMBOLS 4 Paper feed tray 5 Carriage mechanism 6 Paper discharge tray 7 Duplex unit 11, 12 Guide shaft 13 Carriage 14 Recording head 14y, 14m, 14c, 14k Inkjet head 15 Ink cartridge 21 Paper feed roller 23 Transport guide part 24 Transport roller 25 Pressure Roller 26, 27 Guide member 28 Press roller 31 Drive roller 32 Driven roller 33 Conveyor belt 33a First layer 33b Second layer 34 Charging roller 35 Guide roller 90 Host 91 Printer driver 100 Control unit 101 CPU
102 ROM
103 RAM
104 Nonvolatile memory 105 ASIC
106 I / F
107 Head Drive Control Unit 108 Head Driver 110 Main Scan Motor 111 Main Scan Motor Drive Unit 112 Sub Scan Motor 116 I / O
117 Operation Panel 118 Environmental Sensor 130 Image Data 131 CMM Processing Unit 132 BG / UCR Processing Unit 133 γ Correction Unit 134 Zooming Unit 135 Halftone Processing Unit

Japanese Patent No. 4426486 Japanese Patent No. 3912480

Claims (8)

A gradation processing method for performing gradation processing on image data,
By comparing the first gradation processing before the first image data and second image data after the first gradation processing to calculate the amount of information of the defect degree,
A gradation processing method, wherein the defect degree is reduced by performing a second gradation process different from the first gradation process according to the defect degree. The deficiency is
When the first image data is P _in and the second image data is P _out , it is calculated as a total value of K × (P _in −M × P _out ) (M, K: coefficient). The gradation processing method according to claim 1, wherein: The deficiency is
3. The gradation processing method according to claim 1, wherein second gradation processing different from the first gradation processing is performed when the threshold value is larger than a predetermined threshold value. 4. 4. The gradation processing method according to claim 3, wherein the second gradation processing different from the first gradation processing is processing that minimizes the degree of deficiency. If the different second tone processing said first gradation processing to rotate the first image data before said first gradation processing, and the second gradation processing, the most amount of information 5. The gradation processing method according to claim 1, wherein the second image data is obtained by rotating an angle with a small defect degree by R ° (R: 0 to 360 °). 6. If the second gradation processing different from the first gradation processing to change the arrangement of the first image data before said first gradation processing, and the second gradation processing, floor The gradation processing method according to claim 1, further comprising changing the arrangement of the tone processing data. An image forming apparatus that performs gradation processing on image data,
A calculation means for calculating the amount of information of the missing degree by comparing the first gradation processing before the first image data and second image data after the first gradation processing,
Gradation means for reducing the defect level by performing a second gradation process different from the first gradation process according to the defect level;
An image forming apparatus comprising: A program for controlling an image forming apparatus that performs gradation processing on image data,
In the computer of the image forming apparatus,
Calculation means, steps of calculating the amount of information missing degree by comparing the first gradation processing before the first image data and the first of the gradation processed second image data,
A procedure for reducing the deficiency by performing a second gradation process different from the first gradation process according to the deficiency, according to the gradation means;
A program characterized by having executed.

Images