JPH07182504A - Method and device for processing image - Google Patents

Abstract

PURPOSE:To provide the method for processing image so as to preserve a color tone, concentration and fine lines or the like by defining a pattern, which is used for performing magnification or resolution conversion, as a pattern made into a pseudo random number. CONSTITUTION:A control code or image data are transmitted from a host computer 1 to a reception buffer 3 of a printer 2, next, the control code is analyzed by a command analyzing/image extending part 4, and the image data are worked/extended and outputted to a print buffer 5. At a magnification processing part 6, the image data of the print buffer 5 and the pattern data made into the pseudo random number in a DRAM 8 are ANDed and outputted to a recording head 9. The pattern made into the pseudo random number is previously stored in a ROM 7 and DMA-transferred to the DRAM 8.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and apparatus, for example, an image processing method and apparatus for performing scaling of image data and resolution conversion.

[0002]

2. Description of the Related Art Conventionally, in a digital image processing system, an image having a dot pattern is recorded on a recording medium.

Further, conventional image processing apparatuses such as printers, copying machines, and facsimiles record an image consisting of a dot pattern as an output image on a recording material such as paper or a plastic thin plate based on the input image information. Was.

The image processing apparatus has an ink jet type, a wire dot type, a thermal type,
It can be divided into a laser beam type and the like. Among them, the ink jet type (ink jet printer) records an image by ejecting ink (recording liquid) droplets from an ejection port of a recording head and attaching the droplets to a recording material.

In recent years, the spread of image processing apparatuses has been remarkable,
Along with this, needs for the image processing apparatus such as high-speed recording, high resolution, high image quality, and low noise are increasing. Further, with the expansion of inkjet technology, colorization has been rapidly promoted.

Further, as the functions of the image processing apparatus have become more sophisticated, not only the scaling processing for enlarging and reducing the image but also the resolution conversion have made remarkable progress.

[0007]

However, the above-mentioned conventional example has the following drawbacks.

As the image processing apparatus becomes more sophisticated, that is, as the processing becomes more sophisticated, a complicated algorithm must be used, and the processing speed is greatly reduced. Conversely, if you limit the performance of image processing to emphasize processing speed,
For example, fine lines in the image may be missing during the scaling process due to synchronization with the mask pattern, or the tint may change due to changes in the color reproduction pattern due to scaling, which often causes problems in terms of image quality. It was

In the case of resolution conversion or the like, a more serious problem may occur. For example, if regular thinning out such as one dot for several dots is performed, not only the change in the overall tint but also a texture having a different tint may occur.

A general-purpose solution to these problems has not been obtained so far. Therefore, the user himself has to adjust various processing parameters according to the image to be processed, which is very inconvenient. Further, since the image adjustment is performed by the user, the adjustment result largely depends on the individual ability of the user, and thus requires skill.

The present invention has been made to solve the above-mentioned problems, and in order to solve the above-mentioned problems, an image in which the tint and gradation of the original image are preserved without performing complicated processing. An object is to provide an image processing method and apparatus capable of processing.

Another object of the present invention is to convert image data by using a mask pattern of pseudo-random numbers at the time of scaling and resolution conversion so that the density of each color is preserved and the image data is converted. It is an object of the present invention to provide an image processing method and device capable of performing image processing while preserving the tint and gradation.

Still another object of the present invention is to process fine lines and contour portions and other area portions separately so that the thin lines and contour portions are completely preserved and the area portions are density preserved. To provide an image processing method and apparatus capable of performing good image processing at high speed in all of fine line storability, gradation, and tint by using an optimal reduction method with emphasis on each property. To aim.

Further, another object of the present invention is to provide an image processing method and a reduction processing which can preserve the gradation even in the image recording method by the density gradation method using multi-dots or dark and light inks. The purpose is to provide a device.

Still another object of the present invention is to provide an image processing method and apparatus which does not require the user to adjust the image and does not require the skill of the user.

[0016]

In order to achieve the above-mentioned object, the present invention comprises the following constitutions.

That is, input means for inputting image data,
Holding means for holding a mask pattern generated by determining a predetermined number of masking out of a predetermined pixel block according to a pseudo-random number, and image data input by the input means are held by the holding means. It has a conversion means for performing masking using a mask pattern and an output means for outputting the image data masked by the conversion means.

For example, the holding means holds the mask pattern in advance.

Further, it is characterized by further comprising a pseudo random number generating means for generating a pseudo random number and a mask pattern generating means for generating the mask pattern by the pseudo random number generated by the pseudo random number generating means.

For example, the mask pattern is changed according to a conversion rate in the conversion means.

For example, in the converting means, when the image data is represented by a plurality of colors, masking is performed for each color component, and at that time, the mask pattern for at least one color component is for the other color components. It is characterized in that it is different from the mask pattern.

For example, in the conversion means, when the image data is expressed by a gray scale method, masking is performed for each gray scale, and at this time, the mask pattern for at least one gray scale is used for other gray scales. It is different from the mask pattern.

Also, input means for inputting image data,
A thin line extracting means for extracting thin lines / contour lines from the image data, an area extracting means for extracting a portion having an area from the image data, and a thinning / contouring line thinning conversion for the thin lines / contour lines extracted by the thin line extracting means. Converting means, holding means for holding a mask pattern generated by determining a predetermined number of predetermined pixel blocks to be masked according to a pseudo-random number, and the holding area for the area portion extracted by the area extracting means. Second conversion means for performing masking using the mask pattern held by the means;
Outputting the image data combined by the combining unit, which combines the image data converted by the first converting unit with the image data masked by the second converting unit And an output unit that operates.

Also, input means for inputting image data,
Holding means for holding the pattern generated by the pseudo-random number, selecting means for selecting a pixel from the image data input by the input means according to the pattern held by the holding means, and pixel selected by the selecting means It has a conversion means for adding a pixel by referring to the neighboring pixels of, and an output means for outputting the image data added with the pixel by the conversion means.

For example, the conversion means adds a pixel by taking a logical sum of the pixel selected by the selection means and the pixel adjacent thereto.

Further, input means for inputting image data,
First conversion means for converting the number of pixels of the image data in a predetermined direction, second conversion means for converting the number of pixels of the image data in a direction perpendicular to the predetermined direction, and the first conversion means. And output means for outputting the image data converted by the second converting means, and holding means for holding the pattern generated by the pseudo-random number. The first converting means and the second converting means are provided. At least one of them determines a pixel to be converted according to the pattern held in the holding means.

For example, the output means is an ink jet printer for ejecting ink for recording.

For example, the output means is an ink jet printer provided with a recording head for ejecting ink by utilizing heat energy, and is provided with a heat energy converter for generating heat energy given to the ink. Is characterized by.

[0029]

With the above arrangement, image data can be converted by using a mask pattern of pseudo-random numbers at the time of scaling and resolution conversion.

Further, the fine line or contour portion and the other area portion can be processed separately.

Further, also in the image recording method by the density gradation method using multi-dots, dark and light ink, etc., the image data can be converted by using the mask pattern by the pseudo random numbers.

Further, there is a peculiar effect that the user does not need to adjust the image.

[0033]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment according to the present invention will be described in detail below with reference to the drawings.

[0034]

[First Embodiment] FIGS. 2 and 3 show examples of enlargement and reduction of an original image in the present embodiment for characters and thin lines, respectively. In this way, it is of course ideal to perform scaling so that the original image does not collapse or disappear during expansion and reduction.

When performing the reduction processing, it is possible to employ a simple method such as thinning out pixels of the original image at regular intervals, but when the reduction ratio becomes large, the thin line in the reduced image becomes thin. The number of parts increases, and vertical lines and horizontal lines often disappear at last.

An example in which vertical lines and horizontal lines disappear is shown in FIG.
This will be described below with reference to FIGS.

Consider, for example, the case where the reduction processing is performed on the binary image shown in FIG. It should be noted that in FIGS. 4 to 6, each square represents one pixel, and the square marked with a circle indicates that the pixel is black and the other pixels are white. Hereinafter, the black pixels are referred to as “effective pixels”.

When the image of FIG. 4 is reduced by thinning out with the regular mask pattern shown by the diagonal lines of FIG.
The part synchronized with the mask pattern disappears. As a result, the reduced output image becomes as shown in FIG.
That is, the original image of FIG. 4 is lost. Furthermore,
Depending on the original image or mask pattern, the worst case in which all effective pixels disappear may be considered.

Generally, in the processing of an image having a regular pattern such as a halftone pattern or a dither pattern, in order to prevent the disappearance of effective pixels by the above method, OR processing is performed on neighboring image data. Therefore, the device is devised to prevent the loss of effective pixels at the time of reduction.

However, if such a process is repeated, the data processing time may increase progressively, and the mask size and the like may change depending on the scaling factor. Can be very problematic.

In the present embodiment, in order to solve the above-mentioned problems, a mask pattern at the time of scaling, especially at the time of reduction, is created by using a pseudo random number.

Further, in general, when a reduction process is performed on a halftone image, the density of the original image often changes greatly. However, according to the present embodiment, the reduction processing can be performed without degrading the halftone gradation of the original image. Therefore, this embodiment is particularly effective for gray scale and full color images.

The reduction processing in this embodiment will be described below with reference to FIG.

FIG. 1 is a block diagram showing the schematic arrangement of a printer capable of executing the reduction processing of this embodiment. In FIG. 1, 1 is a host computer and 2 is a printer. The printer 2 includes a reception buffer 3, a command analysis / image development unit 4, an image buffer 5, a scaling processing unit 6, and a ROM.
7, DRAM 8, print buffer 9, recording head 10
Etc., which are controlled by the CPU 12. The RAM 11 is used as a work area for the CPU 12.

As will be described later in detail, the ROM 7 stores mask patterns used in the reduction processing of this embodiment.

First, the control code and the image data are transmitted from the host computer 1 to the printer 2 through the interface. In the printer 2, the host computer 1
The control code and the image data are received by the reception buffer 3, and then the command analysis / image expansion unit 4 analyzes the control code. Then, based on the analysis result, the image data is processed so that it can be printed by the recording head 10.
It is developed and output to the image buffer 5.

When the scaling processing or the like is not performed, the image data accumulated in the image buffer 5 as described above is passed through the scaling processing section 6 and the print buffer 9 and printed as it is from the recording head 10. . On the other hand, when performing the scaling process or the like, the scaling process unit 6 executes the required scaling process, stores it in the print buffer 9, and then prints from the recording head 10. The scaling process in the scaling unit 6 will be described below.

The scaling unit 6 is composed of a gate array, performs an AND process on the image data transferred from the image buffer 5 and the mask pattern data sent from the DRAM 8, and outputs it to the print buffer 9.

The mask pattern data of the DRAM 8 is stored in the ROM 7 in advance, and is sent to the DRAM 8 by direct memory access transfer (DMA transfer). The mask pattern data stored in the ROM 7 is created using pseudo random numbers as described later.

In the scaling processing unit 6, the image data is output to the print buffer 9 by directly resetting the address of the image data in the image buffer 5 or directly in accordance with the state of the mask pattern data from the DRAM 8. This can be realized by adjusting the transfer timing from the buffer 5 to the recording head 10. As described above, it is possible to avoid the disappearance of thin lines in the image data.

Although the above description has been made for the processing suitable for a monochrome image, when processing a color image, for example, Y (yellow), M (magenta), C (cyan), K (black) are previously stored in the ROM 7. ), Etc., it is sufficient to store a mask pattern with a matrix of a size of 8 × 8 or 16 × 16.

In the scaling processing or resolution conversion processing in color image recording, there can be considered a method of applying the same mask pattern for each color information of Y, M, C and K and a method of applying different mask patterns. In either case, in principle, it is achieved by masking the original image data with a mask pattern in which the number of thinned dots is the same in the raster direction and the column direction according to the ratio of scaling and resolution conversion. It

However, in any case, the mask is masked with a regular mask pattern, so that a portion that is in synchronism with the regularity of the color reproduction dither pattern or the like is always generated.
There may be a problem that the tint locally changes greatly in the processed image. 50% in extreme cases
In some cases, the print density of 100% would result in a print density of 100%.

An example in which the distortion of the print density as described above occurs will be described below with reference to FIG.

FIG. 7 shows 8 × which expresses a halftone of green color by using yellow with a density of 25% and cyan with a density of 25%.
8 simply shows the image data of No. 8.

In FIG. 7, yellow and cyan are arranged in a regular pattern in the raster and column directions at intervals of one dot. Consider a case where such image data is subjected to reduction processing of ½ in each of the raster and column directions to reduce the area to ¼.

In FIG. 7, it is assumed that the dot array of the image data is thinned by applying a mask with a regular grid-shaped mask pattern shown by the slanting lines on the lower left as shown in FIG. Then, the dots that overlap the portion shown by the diagonally downward-sloping portion in FIG. 8 are thinned out.

FIG. 9 shows an example in which the dots remaining after thinning by the mask pattern of FIG. 8 are allocated to the corresponding portions of the reduced screen and rearranged.

The remaining dots shown in FIG. 9 are all yellow because the mask pattern shown in FIG. 8 is 100% synchronized with the cyan portion and the blank portion of the image data shown in FIG. It has become a dot. Therefore, the reduced image in FIG. 9 is an image with 100% density of yellow, which is completely different from the original image of green color.

Further, in FIG. 8, when the dot position of the thinning mask is reduced with the dot position shifted in the 1-dot raster and column directions, an image having 100% cyan density is obtained.

Not only in the extreme cases described above,
It is possible for the tint of the image after thinning to change significantly due to the synchronization of the mask pattern and the original image data.

As described above, in order to prevent the tint change due to the synchronization of the image data and the mask pattern in the reduction processing, the mask pattern created by using the pseudo random numbers is used in this embodiment.

The reduction processing in this embodiment is to obtain a reduced image by performing AND processing between the mask pattern created by the pseudo random number and the image data at the thinning rate according to the reduction rate.

In the present embodiment, random numbers are used when creating masks used for scaling and resolution conversion, but of course there is no problem if perfect random numbers can be used in principle. In this embodiment, pseudo random numbers are used in order to use the function and the like.

Basically, as the mask pattern used in this embodiment, a mask pattern having the same number of dots for thinning in the raster direction and the column direction is used.

Therefore, in the present embodiment, the original image data and the mask pattern are not synchronized with each other, and even if the tint is microscopically changed in the reduced image, the density of each color is macroscopically maintained. The rate is saved, including the blank rate,
It is possible to prevent a large change in color.

An example of the reduction processing in this embodiment will be described with reference to FIGS. 10 and 7.

FIG. 10 shows an example of a mask pattern used in this embodiment. Contrary to FIG. 8, the diagonal lines in the lower left of the figure designate the positions where dots are stored.

The mask pattern in this embodiment is 2 ×
It is created by randomly selecting only one dot from a block of two dots by a pseudo random number.

The blocks of 8 × 8 dots shown in FIG. 10 are numbered A to H for each dot in the column direction and 1 to 8 for each dot in the raster direction. Then, the dot adjacent to each other in the column direction or the raster direction (m · n)
Further, the dot position indicated by the column direction 1 and the raster direction r is indicated by (l, r). Then, in FIG.
Select the position of (A, 1) in the block of 2 × 2 dots of (A / B) × (1.2), and then select (C / D) on the right side
It is possible to select a dot position to be randomly extracted with a pseudo-random number at a rate of 1 dot per 4 dots, such as selecting a position of (C, 2) in a block of × (1.2). I understand. Then, by repeating this random selection / extraction, the mask pattern shown in FIG. 10 is completed.

Although the mask pattern shown in FIG. 10 has been described as 8 × 8 dots, it is actually allowed depending on the processing speed of hardware and software, for example, one screen, one page, one scanning width. Created in a relatively large range. For example, when the printer 2 in this embodiment is a serial printer, it is practically sufficient that the raster direction has a printable nozzle width of the recording head 10 and the column direction has a size of several hundreds of columns.

The mask pattern shown in FIG. 10 explained above is applied to the original image data of FIG. 7, the extracted dots or blanks are packed in the reduced range and rearranged, and the drawing result is shown in FIG.

The number of dots of each color in the reduced image of FIG. 11 is 4 dots of yellow, 4 dots of cyan, and 8 dots of blank, and the composition ratio thereof is 4: 4: 8, that is, 1: 1: 2. Has become. Since the same ratio in the original image data of FIG. 7 is 16:16:32, the ratio is also 1: 1: 2. Therefore, in the reduction example shown in FIG. 11, the original image data shown in FIG. It can be seen that the composition ratios of yellow, cyan, and blank are the same, and the tint and the density are 100% preserved.

In the above description, the case where the composition ratio of each color is completely the same is shown, but in reality, the composition ratio of each color is not the same as the original image data in all reduction ranges. Absent. Depending on the mask pattern, the tint and the density may be microscopically different. However, since the mask pattern is set using pseudo random numbers, the tint and the density are macroscopically preserved.

Further, since the extreme tuning does not occur in a wide area, the preservation of the tint and the density is very good.

The reduction processing in this embodiment described above is shown in the flowchart of FIG. First, step S
At 101, image data to be processed is input from the host computer 1 to the reception buffer 3. Then, the command analysis / image expansion unit 4 expands it into a predetermined format and stores it in the image buffer 5 (FIG. 7). next,
In step S102, the mask pattern (FIG. 10) stored in ROM 7 is transferred to DRAM 8.
Then, in step S103, masking is performed in the scaling unit 6, and in step S104, the extracted dots are rearranged and output to the print buffer 9.
(FIG. 11). The image data in the print buffer 9 is output to the recording head 10 in step S105.

In the present embodiment, the example in which the mask pattern is stored in the ROM 7 in advance has been described, but the present embodiment is not limited to this example, and the configuration shown in FIG. It is also possible to take.

In FIG. 19, the same components as those in FIG. 1 described above are designated by the same reference numerals and the description thereof will be omitted. In FIG. 19, 13 is a pseudo random number generator, and 14 is a mask pattern generator. When the reduction process is started, the pseudo random number generation unit 13 generates a pseudo random number at a predetermined timing. Then, the mask pattern generation unit 14 uses the pseudo random number generated by the pseudo random number unit 13 to generate a mask pattern based on the designated reduction rate, and transfers the mask pattern to the DRAM 8. Then, after that, masking is performed in the same manner as the example described above.

By generating a mask pattern in the apparatus as shown in FIG. 19, it is not necessary to hold various mask patterns in the ROM 7 shown in FIG.

The reduction processing in the configuration shown in FIG. 19 of this embodiment is shown in the flowchart of FIG. In FIG. 21, first, in step S201, image data is expanded in the image buffer 5. Then, in step S202, it is determined whether or not the masking process is completed for all the image data, and if not completed, the process proceeds to step S203. In step S203, the pseudo random number generator 13 generates a pseudo random number, and in step S204, the mask pattern generator 14 uses the pseudo random number to generate a mask pattern of a predetermined size. Then, in step S205, the mask pattern generated in step S204 is transferred to the DRAM 8 and masking is performed in the scaling processing unit 6 in step S206. Then, the process returns to step S202, and the above process is repeated until the masking of all the image data stored in the image buffer 5 is completed.

If it is determined in step S202 that masking is completed, the process proceeds to step S207, the extracted dots are rearranged, and the dots are output to the print buffer 9. Then, the image data stored in the print buffer 9 in step S208 is output to the recording head 10.

As described above, according to the present embodiment, since the original image data is thinned out by the mask pattern created by using the pseudo-random number for the color image and the reduction processing is performed, the density of each color is saved. It is possible to perform image processing that preserves the tint and gradation of the original image data.

[0083]

[Second Embodiment] In the second embodiment, a method will be described in which, in addition to the image processing method described in the first embodiment, the storability of thin lines is also taken into consideration.

Below, the original image is rasterized by 1 in the raster direction and 1 in the column direction.
A method of creating a mask pattern for reducing the size to / 2 and a thinning algorithm will be described.

In the second embodiment, the recording resolution, which is the minimum unit used for printing, is 1 dot, which is the same as the resolution of the mask pattern to which the pseudo random number is applied. Therefore, when the grayscale image data or the like created based on the resolution of the recording head 10 of the printer 2 is masked by the mask pattern, it is synchronized with the periodicity of the pseudo random number somewhere in the image. There is a risk that

Then, as a result, dots may be missing continuously, or dots may not be removed conversely, resulting in a problem that thin lines in the image become dotted lines, zigzags, or disappear. . In the case of full-color images, the mask pattern for color reproduction is more affected, so the above problems are often less noticeable, but in the case of printing business graphics or text, the above problems are serious. Therefore, the storability of fine lines and contours and their accuracy are important points in image quality. FIG. 17
FIG. 8 shows the device configuration of the printer in the second embodiment. In FIG. 17, the same components as those in FIG. 1 of the first embodiment described above are designated by the same reference numerals and the description thereof will be omitted. In FIG. 17, 21 is an area extraction unit that extracts an area portion from image data, 22 is a thin line / contour extraction unit that extracts thin lines and contours from image data, and 23 and 24 are scaling processing units a, b, 25,
26 is a memory a, b, and 27 is a coupling unit.

The reduction processing of the second embodiment having the above-mentioned device configuration will be described in detail below with reference to FIGS. 12 and 13.

FIG. 12A shows the original image data, and consider the case where the original image data is reduced to 1/2 in the raster and column directions.

In order to make it easy to understand the reduction relationship on the drawing, the original image data shown in FIG.
The same diagram as shown in (A) of FIG. First, Fig. 1
The original image data shown in (A) of 2 is stored in the image buffer 5. Then, in the fine line / contour extraction unit 22, the fine line and the contour portion are extracted from the image data as shown in FIG.
As shown in (B) of FIG. 13 in the scaling processing unit b24, and the stored data is stored in the memory b26. deep. Here, if the original image data is only a thin line or a contour line, there is no area portion, so that the image quality can be sufficiently maintained by thinning with a mask pattern such as a houndstooth check pattern.

Next, from the original image data shown in FIG. 12A, the area extraction unit 21 extracts the area portion other than the thin line and the contour portion as shown in FIG. 12C. And
In the scaling unit a23, the mask pattern of pseudo random numbers is used to reduce the size to ½ as shown in FIG. 13C by the method described in the first embodiment, and the memory a2
Save to 5. It should be noted that the area extraction unit 21 does not extract the area part, and includes the thin line part and the contour shown in FIG. 12B, that is, the original image data shown in FIG. You may reduce by the process part a23.

Subsequently, in the combining unit 27, the memory b2
ORing the reduced image of the thin lines and contours shown in FIG. 13 stored in FIG. 6 with the reduced image of the thin lines and contours shown in FIG. 13C stored in the memory a25. Thus, as shown in (D) of FIG.
2 reduced images are generated.

The reduction processing in the second embodiment described above is shown in the flowchart of FIG. First, step S3
In 01, the image data is expanded in the image buffer 5 ((a) of FIG. 12). Then, the process proceeds to step S302, and the thin line / contour extracting unit 22 extracts the thin line and the contour ((b) of FIG. 12). And step S303
Then, the scaling processing unit b24 performs masking with the mask pattern from the DRAM 8 and stores the masked image data in the memory b26 in step S304 (FIG. 13).
(B)).

Next, in step S305, the area portion is extracted from the image data of the image buffer 5 ((d) of FIG. 12). Then, in step S306, the scaling unit a23 performs masking with the mask pattern from the DRAM 8, and in step S307, the masked image data is stored in the memory a25 ((c) of FIG. 13).

Then, the process proceeds to step S308, and the combining unit 2
In FIG. 7, the contents stored in the memory a25 and the memory b26 are OR-processed to be combined and stored in the print buffer 9 ((d) of FIG. 13), and step S309
Is output to the recording head 10.

As described above, according to the second embodiment,
By using thin lines and contours separately from other area parts, the optimal reduction method should be used, emphasizing perfect preservation for thin lines and contours and density preservation for area. As a result, it is possible to obtain a reduced image in which grayscale is preserved in grayscale, and color images are preserved in tint and tone, and fine line preservation, tone, and tint are all well preserved. Is possible.

Further, in the second embodiment, only the thin line and the contour portion are processed first simply and at high speed, and the portion having the area is processed by the dedicated processing system, and finally the OR processing is performed. It is not necessary to select the processing while always determining whether the image data is a thin line, a contour, or other. Therefore,
It is possible to perform processing at a higher speed than processing the thin line or contour portion and the area portion at the same time.

As the method of extracting the thin line or the contour and the method of extracting the area portion described above, known methods using software or hardware can be used.

[0098]

[Third Embodiment] The second embodiment described above is a method in which the preservability of the thin line portion is added to the first embodiment. However, the present invention is not limited to the above example, and can be applied not only to the area gradation method but also to an image recording method of a density gradation method using multi-dots or dark and light ink. The tint and gradation preservation in the third embodiment of the present invention using such a method will be described below.

Since the device configuration of the third embodiment is the same as that of FIG. 1 shown in the first embodiment, the description thereof will be omitted.

In the first and second embodiments described above,
Since the image recording method is the area gradation method, when reducing the original image data, a mask with a pseudo-random number according to the reduction ratio is used so that the ratio of dots in the unit area is almost the same in the reduced image. By using the pattern for reduction, it was possible to preserve the gradation of the original image data.

However, in the density gradation type image recording method, for example, the density is determined by the combination of the dark ink and the light ink. Therefore, in order to realize the reduction processing that maintains the gradation of the original image data, the dark ink and the light ink are simply used as a mask pattern by one pseudo-random number as in the first and second embodiments. In addition to the first method of thinning out at the same time, a second method considering further gradation and storage stability of color can be considered.

Regarding the first method, since the area gradation is basically used together even in the density gradation method using the dark and light ink, if the number of dots is simply thinned out by the mask pattern. However, there is a possibility that the gradation may be slightly broken.

On the other hand, in the second method, when the mask pattern corresponding to the reduction ratio is created by using the pseudo random number, different mask patterns are created for the dark ink and the light ink, and the reduction process is executed for each. The gradation property can be preserved by performing the OR processing at the end.

In the case where the mask patterns are processed separately as described above, for example, the reduction ratio is large, and therefore the size of the mask pattern for color reproduction after the reduction is small, resulting in a high density. It is also possible to perform processing such as subtly increasing the thinning rate of dark ink.

If the thinning-out ratio is an odd one depending on the reduction ratio, the thinning-out number of dark ink is increased and the thinning-out number of light ink is decreased, or the number of dots of light ink is positively increased slightly. It is also possible to perform flexible processing as desired by the user.

The same applies to image recording by the multi-dot method. In the multi-dot method, ink of a single density is ejected a plurality of times to approximately the same landing point, and the density of the dye at that landing point is increased to obtain density gradation. Therefore, of course, a method of simply masking all the dots and thinning them out is also conceivable. Then, further, according to the number of overlapping dots at each landing point, reduction is performed by a mask pattern according to the reduction ratio using a pseudo random number between those having the same number of overlapping, and then,
There is also a method of ORing the reduced images at each number of overlaps to obtain the final reduced image.

As described above, according to the third embodiment,
In the image recording method based on the density gradation method using multi-dots, dark and light ink, etc., it is possible to carry out the reduction processing while preserving the gradation.

[0108]

[Fourth Embodiment] In the fourth embodiment, a case where resolution conversion is performed will be described. Even when resolution conversion is performed, if a regular pattern is used, a change in tint will occur. Therefore, in the fourth embodiment, pseudo random numbers are used for resolution conversion processing.

A general method for converting an image having a resolution of 160 DPI (dots / inch) into an image having a resolution of 360 DPI will be described below with reference to FIGS. 14 and 15.

When an image of 160 DPI is converted to 360 DPI, the enlargement ratio on the image buffer is 4: 9 from the DPI ratio. Therefore, in terms of area ratio, one dot must be converted into a magnification including a fraction of 2.25 times 2.25 times 5.05 times. Therefore,
A tint change occurs depending on the fraction processing method.

FIG. 14A shows an example of a block of 4 × 4 dots of original image data of monochrome 160 DPI.
14B shows an example of a 9 × 9 dot block obtained by converting the resolution of FIG. 14A to 360 DPI.

When the area ratio by the number of dots and the number of blanks of each of (A) and (B) shown in FIG. 14 is calculated, it is 4:12, that is, 1: 3 in FIG. 14A. On the other hand, in FIG. 14B, it is 33:48, that is, 1 :.
You can see that it has become 1.45. That is, the original image and the image subjected to the resolution conversion have different densities, that is, tints.

FIG. 18 shows the device configuration of a printer capable of resolution conversion processing in the fourth embodiment. In FIG. 18, the same components as those in FIG. 1 of the first embodiment described above are designated by the same reference numerals, and the description thereof will be omitted. In FIG. 18, 31 is a pixel selection unit, 32 is a resolution conversion unit, and 33 is a smoothing unit.

Details of the resolution conversion processing in the fourth embodiment will be described with reference to FIG.

Similar to FIG. 14A, FIG. 15A shows an example of a 4 × 4 dot block of an original image of monochromatic 160 DPI, and FIG. 15B shows a diagram according to the fourth embodiment. 1
An example of a block of 9 × 9 dots obtained by converting the resolution of (A) of 5 to 360 DPI is shown.

In the fourth embodiment, first, the image data shown in FIG. 15A is stored in the image buffer 5.
In the pixel selection unit 31, from the image data in the image buffer 5, according to the pattern sent from the DRAM 8,
First, pixels are selected at a ratio of 1 dot to 8 dots in the column direction. The pattern of the DRAM 8 is created by pseudo random numbers and is stored in the ROM 7 in advance.

Then, in the resolution conversion unit 32, in addition to the predetermined resolution conversion processing, OR processing is performed on the selected pixel and its adjacent pixels. Therefore, 4 dots are converted to 9 dots.

Next, by performing the same processing in the raster direction, the resolution-converted image is output as shown in FIG. 15 (b).

That is, in FIG. 15B, the dot row indicated by the straight line A is selected from the 8 dots which are doubled in the column direction. Then, the dot row shown by the straight line B is added by performing the OR processing with the dot on the right side. The same applies to the straight lines C and D in the raster direction.

In FIG. 15B, the area ratio by the number of dots and the number of blanks is 20:61, that is, 1: 3.05.
And is almost the same as the ratio in the original image shown in FIG. 14 (A) or FIG. 15 (A).

Next, smoothing processing is performed in the smoothing section 32. This example is shown in FIG. That is,
The original image data of 160 DPI shown in (A) of FIG. 16 is once converted to 360 DPI as shown in (B) of FIG.
In FIG. 16, a known smoothing process is performed, and FIG.
The result shown in (B) is obtained.

That is, by the resolution conversion processing in the fourth embodiment, the image shown in FIG. 16 (a) finally becomes the image shown in FIG. 16 (b).

The resolution conversion processing in the fourth embodiment is shown in the flowchart of FIG. First, in step S401, image data is expanded in the image buffer 5 ((a) of FIG. 15). Then, in step S402, it is determined whether or not the resolution conversion process has been completed for all the image data stored in the image buffer 5, and if not completed, the process proceeds to step S403. Step S40
In 3, the pattern for determining the pixel is input from the DRAM 8, and in step S404, the pixel selecting unit 31 selects the pixel. Then, the process proceeds to step S405, and the resolution conversion process is performed while ORing the selected pixel and the adjacent pixel ((b) of FIG. 15). Then, the process returns to step S402, and the above process is repeated until the resolution conversion process is completed for all the image data.

If it is determined in step S402 that the resolution conversion process has been completed for all image data, step S402 is performed.
Smoothing processing is performed in 406, and the result is stored in the print buffer 9 ((b) of FIG. 16).
Then, in step S407, the data is output to the recording head 10.

Next, conversely, 360 DPI to 160 DPI
Considering the case of converting into, the same can be considered as the case of the reduction processing shown in the first embodiment.

A mask pattern is created from 360 DPI image data by using a pseudo random number at a decimation ratio of 4/9, and the data after thinning using this mask pattern is rearranged and output to obtain a resolution of 160 DPI. The conversion is achieved.

In addition, the above 160DPI to 360D
As described in the resolution conversion processing to PI, 360
For an image having a DPI resolution, first, a pixel is selected from the column direction by a pseudo random number, and the pixel is ANDed with its adjacent pixel.
By performing normal resolution conversion after processing,
For example, 9 dots can be converted into 4 dots. Then, similar processing is performed in the raster direction. This is also applicable to reduction processing.

As described above, according to the fourth embodiment,
Since the resolution conversion can be performed without the area ratio of the number of dots per unit area and the number of blanks largely deviating from the original image, the color density does not change significantly.

Although the resolution conversion processing has been described in the fourth embodiment, the enlargement processing can be realized by the same method as the processing for increasing the resolution in the fourth embodiment.

Further, by using the mask pattern created by the pseudo-random number described in the first embodiment, the resolution conversion processing to the high resolution of the image and the enlargement processing can be performed. For example, as shown in the fourth embodiment, a method of performing an OR process with an adjacent pixel on the pixel selected by the mask pattern can be considered.

In the above first to fourth embodiments, the mask pattern created by using the pseudo random number is written in the ROM 7 in the apparatus in advance, and the DRAM 8 is used when it is used.
Although the present invention is not limited to this, the present invention is not limited to this, and hardware and software having a function of generating random numbers as shown in FIG. It is also possible to generate a pseudo-random number and generate a mask pattern at any time.

Further, the printer 2 in each of the above-described embodiments may be any type of printer, for example, a laser beam printer, a thermal transfer printer, an inkjet printer, for example, a droplet is formed by utilizing film boiling by thermal energy. It may be a so-called bubble jet type printer using a discharge type head.

Further, it can be similarly applied to an image processing apparatus such as a copying machine or a facsimile.

The present invention may be applied to a system composed of a plurality of devices or an apparatus composed of one device. Further, it goes without saying that the present invention can be applied to the case where it is achieved by supplying a program to a system or an apparatus.

[0135]

As described above, according to the present invention, the original image is converted by using the pseudo random number pattern for scaling and resolution conversion, so that the density of each color is preserved, It is possible to perform image processing that preserves the tint and gradation of the original image.

Further, by separately processing the fine line or contour portion and the other area portion, the perfect preservation property is emphasized for the thin line or contour portion and the density preservation property is optimized for the area portion. Since the reduction method can be used, good image processing can be performed at higher speed in all of the thin line storability, gradation, and tint.

Further, even in the image recording method by the density gradation method using multi-dots, dark and light ink, etc., it is possible to carry out the reduction processing while preserving the gradation.

Furthermore, since it is not necessary for the user to perform image adjustment, it is possible to perform image processing that preserves the tint and gradation of the original image without requiring the user's skill level. Is obtained.

[0139]

[Brief description of drawings]

FIG. 1 is a block diagram showing a device configuration in a first embodiment according to the present invention.

FIG. 2 is a diagram showing an example of scaling characters.

FIG. 3 is a diagram showing an example of scaling a thin line.

FIG. 4 is a diagram showing an example of an original image before reduction.

FIG. 5 is a diagram showing an example of a regular mask pattern.

FIG. 6 is a diagram showing an example of a reduced image in which an original image has disappeared.

FIG. 7 is a diagram showing an example of image data providing a halftone in the present embodiment.

FIG. 8 is a diagram showing an example in which a regular mask pattern is applied to image data providing a halftone in the present embodiment.

FIG. 9 is a diagram showing a result of performing reduction processing by applying a regular mask pattern to image data providing a halftone in the present embodiment.

FIG. 10 is a diagram showing an example of a mask pattern created using pseudo random numbers in this embodiment.

FIG. 11 is a diagram showing a result of performing reduction processing by applying the mask pattern shown in FIG. 10 to image data providing a halftone in the present embodiment.

FIG. 12 is a diagram showing an example of thin contour extraction in the second embodiment according to the present invention.

FIG. 13 is a diagram showing a reduction process of a thin line contour or the like in the second embodiment.

FIG. 14 is a diagram showing a conventional example of resolution conversion in a fourth embodiment according to the present invention.

FIG. 15 is a diagram showing an example of resolution conversion using pseudo random numbers in the fourth embodiment.

FIG. 16 is a diagram showing an example in which smoothing processing is performed after resolution conversion using pseudo random numbers in the fourth embodiment.

FIG. 17 is a block diagram showing a device configuration of a second embodiment according to the present invention.

FIG. 18 is a block diagram showing a device configuration of a fourth embodiment according to the present invention.

FIG. 19 is a block diagram showing another device configuration of the first embodiment according to the present invention.

FIG. 20 is a flowchart showing reduction processing in the first embodiment.

FIG. 21 is a flowchart showing a reduction process by another device configuration in the first embodiment.

FIG. 22 is a flowchart showing reduction processing in the second embodiment according to the present invention.

FIG. 23 is a flowchart showing a resolution conversion process in the fourth embodiment according to the present invention.

[Explanation of symbols]

 1 Host Computer 2 Printer 3 Receive Buffer 4 Command Analysis / Image Development Section 5 Print Buffer 6 Magnification Processing Section 7 ROM 8 DRAM 9 Recording Head

─────────────────────────────────────────────────── ─── Continuation of the front page (51) Int.Cl. ⁶ Identification code Internal reference number FI Technical indication location H04N 1/387 101 1/46 (72) Inventor Kiichiro Takahashi 3-30-2 Shimomaruko, Ota-ku, Tokyo No. Canon Inc. (72) Inventor Kei Iwasaki 3-30-2 Shimomaruko, Ota-ku, Tokyo Canon Inc. (72) Inventor Daigoro Kanematsu 3-30-2 Shimomaruko, Ota-ku, Tokyo Canon Inc. In the company

Claims (28)

[Claims] 1. An input step of inputting image data, and a mask pattern generated by determining a predetermined number of predetermined pixel blocks to be masked for the image data input in the input step according to a pseudo random number. An image processing method comprising: a conversion step of performing masking using the output step; and an output step of outputting image data masked by the conversion step. 2. The image processing method according to claim 1, wherein the mask pattern is held in advance. 3. The method according to claim 1, further comprising a pseudo random number generating step of generating a pseudo random number, and a mask pattern generating step of generating the mask pattern by the pseudo random number generated in the pseudo random number generating step. Image processing method. 4. The image processing method according to claim 1, wherein the mask pattern is changed according to a conversion rate in the conversion step. 5. In the converting step, when the image data is represented by a plurality of colors, masking is performed for each color component, and at this time, the mask pattern for at least one color component is for the other color components. The image processing method according to claim 1, wherein the image processing method is different from the mask pattern. 6. In the converting step, when the image data is expressed in a gray scale method, masking is performed for each gray scale, and at this time, the mask pattern for at least one gray scale is used for other gray scales. The image processing method according to claim 1, wherein the image processing method is different from the mask pattern. 7. An input step of inputting image data, a thin line extracting step of extracting thin lines / contour lines from the image data, an area extracting step of extracting a portion having an area from the image data, and the thin line extracting step. A first conversion step of thinning out and converting thin lines / contours extracted by: and a predetermined number of predetermined pixel blocks for masking the area portion extracted by the area extraction step according to a pseudo-random number. A second conversion step of masking using the generated mask pattern, a logical sum of the image data converted by the first conversion step and the image data masked by the second conversion step are calculated. An image processing method, comprising: a combining step of combining by combining; and an output step of outputting the image data combined by the combining step. Law. 8. An input step of inputting image data, a selection step of selecting pixels from the image data input by the input step in accordance with a pattern generated by a pseudo-random number, and a selection step of the pixels selected by the selection step. An image processing method comprising: a conversion step of adding a pixel with reference to a neighboring pixel; and an output step of outputting the image data in which the pixel is added by the conversion step. 9. The image processing method according to claim 8, wherein in the converting step, a pixel is added by taking the logical sum of the pixel selected in the selecting step and the pixel adjacent thereto. 10. The image processing method according to claim 8, wherein the pattern is held in advance. 11. The image according to claim 8, further comprising a pseudo random number generating step of generating a pseudo random number, and a pattern generating step of generating the pattern by the pseudo random number generated in the pseudo random number generating step. Processing method. 12. The image processing method according to claim 8, wherein the pattern is changed according to a conversion rate in the conversion step. 13. An input step of inputting image data, a first converting step of thinning-converting the image data in a predetermined direction, and a second converting step of thinning-converting the image data in a direction perpendicular to the predetermined direction. A conversion step, and an output step of outputting the image data converted by the first conversion step and the second conversion step, and at least one of the first conversion step and the second conversion step. Is an image processing method characterized by determining pixels to be thinned out by a pseudo-random number and performing thinning-out conversion. 14. Input means for inputting image data, holding means for holding a mask pattern generated by determining a predetermined number of predetermined pixel blocks to be masked according to a pseudo random number, and input by the input means. An image processing apparatus comprising: a conversion unit that masks the image data using the mask pattern held by the holding unit; and an output unit that outputs the image data masked by the conversion unit. 15. The image processing apparatus according to claim 14, wherein the holding unit holds the mask pattern in advance. 16. The method according to claim 14, further comprising a pseudo random number generating means for generating a pseudo random number, and a mask pattern generating means for generating the mask pattern by the pseudo random number generated by the pseudo random number generating means. Image processing device. 17. The image processing apparatus according to claim 14, wherein the mask pattern is changed according to a conversion rate in the conversion means. 18. The converting means performs masking for each color component when the image data is expressed in a plurality of colors, wherein the mask pattern for at least one color component is for the other color components. The image processing device according to claim 14, wherein the image processing device is different from the mask pattern. 19. The converting means performs masking for each gradation when the image data is expressed by a gradation method, and at this time, the mask pattern for at least one gradation is for other gradations. The image processing device according to claim 14, wherein the image processing device is different from the mask pattern. 20. Input means for inputting image data, thin line extracting means for extracting thin lines / contour lines from the image data, area extracting means for extracting a portion having an area from the image data, and the thin line extracting means. First conversion means for thinning out and converting thin lines / contours extracted by: holding means for holding a mask pattern generated by determining a predetermined number of predetermined pixel blocks to be masked according to a pseudo-random number; Second conversion means for masking the area portion extracted by the area extraction means using the mask pattern held by the holding means; image data converted by the first conversion means; And a combining unit that combines the image data masked by the second converting unit by ORing the image data and the combining unit. The image processing apparatus characterized by an output means for outputting the image data. 21. Input means for inputting image data, holding means for holding a pattern generated by a pseudo-random number, and pixels from the image data input by the input means in accordance with the pattern held by the holding means. A selection unit for selecting; a conversion unit for adding a pixel by referring to a pixel adjacent to the pixel selected by the selection unit; and an output unit for outputting the image data to which the pixel is added by the conversion unit. An image processing device characterized by: 22. The conversion means adds a pixel by taking the logical sum of the pixel selected by the selection means and the pixel adjacent thereto.
1. The image processing device according to 1. 23. The image processing apparatus according to claim 21, wherein the holding unit holds the pattern in advance. 24. The image according to claim 21, further comprising: a pseudo random number generating means for generating a pseudo random number; and a pattern generating means for generating the pattern by the pseudo random number generated by the pseudo random number generating means. Processing equipment. 25. The pattern is changed according to a conversion rate in the conversion means.
The image processing device described. 26. Input means for inputting image data, first converting means for converting the number of pixels of the image data in a predetermined direction, and converting the number of pixels of the image data in a direction perpendicular to the predetermined direction. Second output means for outputting the image data converted by the first conversion means and the second conversion means, and a holding means for holding the pattern generated by the pseudo-random number, An image processing apparatus, wherein at least one of the first conversion unit and the second conversion unit determines a pixel to be converted according to a pattern held by the holding unit. 27. The image processing apparatus according to claim 14, wherein the output unit is an inkjet printer that ejects ink to perform recording. 28. The ink jet printer having a recording head for ejecting ink by utilizing thermal energy, wherein the output means comprises a thermal energy converter for generating thermal energy given to the ink. The image processing device according to claim 14, wherein