JP3467727B2 - Medium recording image processing program, image processing apparatus, and image processing method - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a medium recording an image processing program, an image processing apparatus and an image processing method.

[0002]

2. Description of the Related Art In a computer or the like, an image is represented by pixels arranged in a dot matrix, but in recent years, an object image is appropriately arranged in a virtual dot matrix area to form a single image. Is used. That is, an object image representing only characters and an object image representing an image are individually prepared,
The images are completed by superimposing them in a predetermined order. When handling such an image, one object image is often divided into a plurality of images for the convenience of computer processing. This is because, for example, as the size of the object image becomes larger, the amount of data also becomes extremely large, and the processing resources become heavy to be processed integrally.

On the other hand, it is possible to process an image in a plurality of stages by a computer, and in addition to the one which can be freely processed inside like an application, a memory or the like is provided by a driver or a module which functions as a part of an operating system. There are things that must be processed while being strongly restricted by. That is, there is a case where image processing is required without connecting the divided object data to generate the original object image. Conventionally, when a module executes processing of object data, it requests a driver to access the object data, but it is only an image area that the module is going to process.

[0004]

In the above-mentioned conventional apparatus, the object data is provided to the module in correspondence with the image area which is the original processing target. However, although the problem does not occur when the image processing is executed based on only the existing single pixel,
In order to execute the processing for the existing pixels, it may be necessary to incorporate the information about the peripheral pixels, and in such a case, the information about the necessary pixels can be referred to in the peripheral area of the image area. There was a problem of disappearing.

The present invention has been made in view of the above problems, and a medium and an image processing medium in which an image processing program capable of preventing the image processing from being disabled due to the sophistication of the image processing is recorded. An object is to provide an apparatus and an image processing method.

[0006]

In order to achieve the above object, the present invention according to claim 1 provides an object image in which an object image is appropriately arranged in an area representing an image composed of pixels arranged in a dot matrix. Multiple divided object data are generated to express
A medium for recording an image processing program for causing a computer to execute predetermined image processing for each object image, the image processing program including a driver to which the divided object data of the object image is input, and each object image. And a module for executing image processing, and the module is for performing individual image processing.
With multiple image processing objects to perform
In, the driver is adapted to spool the divided object data, when the available object data in the image area where the module is processed to expand from the spool file on the memory, the module
Each image processing object of
The required peripheral area to the image area to be processed.
Then, notify the remaining image processing objects and
In the later image processing object the marginal area was added
The image area is expanded on the memory .

In the invention according to claim 1 configured as described above, when the divided object data of the object image is input to the driver, the module executes the image processing for each object image. Is capable of spooling the divided object data and expanding the object data of the image area to be processed by the module from the spool file onto the memory for use. At this time, the driver expands on the memory by adding the peripheral area referred to in each image processing in addition to the image area to be processed by the module. That is, in this image processing program, when appropriately arranging an object image in an area representing an image composed of pixels arranged in a dot matrix, a plurality of divided object data is generated to represent the same object image, and each divided object data is generated. Although predetermined image processing is executed for each image, for convenience of processing, the driver spools the divided object data and the module expands the object data of the image area to be processed from the spool file on the memory. The area that is sometimes expanded on the memory is not only the image area that is the original processing target but also the peripheral area that is referred to in the image processing executed by the module.

In such a case, the module is not necessarily limited to a module that executes a single image process, and may be a module that can execute a plurality of image processes. Therefore, a peripheral area required for each image processing in a plurality of image processing objects is added in advance,
The driver develops an image area including the peripheral area on the memory.

When the peripheral area required for image processing of each image processing object is added in advance in this way, the image area for which the peripheral area required by each image processing object in its own image processing is to be processed. When there are a plurality of image processing objects, these image processing objects are linked to each other and each image processing object notifies the image area of the next image processing object including the peripheral area. Accordingly, by referring to the image area added with the peripheral area in the last image processing object, the image area added with the peripheral area necessary for all the image processing objects can be known, and the driver can determine the final image area. Just expand it in memory.

According to a second aspect of the present invention, in the medium in which the image processing program according to the first aspect is recorded, the driver includes an image area including a peripheral area and a memory in divided object data units. It is designed to be deployed on top. The object data expanded in the memory does not necessarily have to be the image area to be processed as it is, and may be expanded with a margin. That is, it is inconvenient if it is not expanded in the memory including the peripheral region to be referred to, but conversely, it is not a problem that it is expanded in excess. For this reason, claim 2 configured as described above
In the invention according to the second aspect, the driver expands the divided object data unit in the memory including the image area including the peripheral area.

When the number of divided object data becomes extremely large, the processing is unavoidably deteriorated. However, as a suitable example in such a case, the invention according to claim 3 is one of claim 1 and claim 2. In the medium in which the described image processing program is recorded, the driver is configured to limit the use of frequently used divided object data expanded in the memory. Since the divided object data expanded on the memory may not necessarily be required in all cases, in the invention according to claim 3 configured as described above, the divided object data that is frequently used is limited to be usable. As a result, it is possible to prevent processing speed and the like from being lowered without targeting unnecessary divided object data.

In the above, a recording medium in which software is recorded has been described as an example of embodying the idea of the invention. Of course, the recording medium may be a magnetic recording medium or a magneto-optical recording medium, and any recording medium developed in the future can be considered in exactly the same manner. In addition, the duplication stage of the primary duplication product, the secondary duplication product, and the like is absolutely the same. In addition, even when the communication method is used as the supply method, the present invention is still used. Furthermore, even when a part is software and a part is realized by hardware, the idea of the invention does not differ at all, and a part is stored on a recording medium and appropriately stored as necessary. It may be in a form that can be read.

However, it is obvious that the present invention is not used only as such software, and as an example thereof, the invention according to claim 4 is an area representing an image composed of pixels arranged in a dot matrix. In appropriately arranging the object images in the image processing apparatus, an image processing apparatus that generates a plurality of divided object data for expressing the object images and executes predetermined image processing for each object image, The image processing apparatus further comprises a data management unit for inputting divided object data and a data processing unit for executing image processing for each object image, and the data processing unit includes a plurality of images for executing individual image processing.
In addition to having a processing object, the data management means spools the divided object data and expands the object data of the image area to be processed by the data processing means from the spool file on the memory to make it available. , The data processing means has
Each image processing object that
The required peripheral area to the image area to be processed.
Then, notify the remaining image processing objects and
In the later image processing object the marginal area was added
The image area is expanded on the memory . The operation in the invention according to claim 4 configured as described above is the same as the function realized by the program.

Further, it is easy to understand that such a method does not necessarily have to be limited to a substantive device, and can also function as that method. Therefore, in the invention according to claim 5, when appropriately arranging an object image in an area representing an image composed of pixels arranged in a dot matrix, a plurality of divided object data are generated to represent the object image. An image processing method for executing a predetermined image processing for each object image, the data management step of inputting divided object data of the object image data, and the data processing step of executing image processing for each object image In addition, the above data processing step implements individual image processing.
With multiple image processing objects running ,
The data management unit is configured to spool the divided object data, when the available object data of an image area in which the data processing means is processed to expand from the spool file on the memory, the data
Each image processing object possessed by the data processing means
The peripheral area that is necessary for my image processing is to be processed
In addition to the image area to
Notification will be given and the last image processing object will
The image area added with the edge area is developed on the memory .

[0015]

As described above, according to the present invention, when it becomes necessary to refer to the peripheral region of the image region to be processed as the image processing is advanced, the peripheral region referred to by a plurality of image processes. Even when the values are different, it is possible to provide a medium in which an image processing program capable of reducing the troublesomeness of managing the necessary peripheral area is provided by each image processing object sequentially reporting the peripheral area. . Further, according to the invention of claim 2,
Since the driver spools in object data units, it is not necessary to further consider the necessary area and cut out, and the processing speed is improved. Furthermore, according to the third aspect of the present invention, it is possible to prevent a decrease in processing speed by not processing the divided object data that is used less frequently. Further, according to the invention of claim 4, it is possible to provide an image processing apparatus capable of achieving the same effect, and according to the invention of claim 5, it is possible to provide an image processing method.

[0016]

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a computer system 10 as an example of hardware that realizes an image processing system to which an image processing program according to an embodiment of the present invention is applied. The computer system 10 includes a scanner 11a, a digital still camera 11b, and a video camera 11c as image input devices for directly inputting image data, and is connected to the computer main body 12. Each input device can generate image data in which an image is expressed by pixels in a dot matrix shape and output the image data to the computer body 12. Here, the image data is displayed in 256 gradations in each of the three primary colors of RGB. , About 167
It is possible to express 0,000 colors.

A floppy disk drive 13a, a hard disk 13b and a CD-ROM drive 13c as external auxiliary storage devices are connected to the computer main body 12, and a main system-related program is recorded on the hard disk 13b. Necessary programs can be read from a floppy disk or a CD-ROM. Also, the computer body 1
A modem 14a is connected as a communication device for connecting 2 to an external network or the like, and can be connected to an external network via the same public communication line to download and introduce software and data.
In this example, the modem 14a is used to access the outside via the telephone line, but it is also possible to have a configuration for accessing the network via the LAN adapter.

Here, among the external auxiliary storage devices, the floppy disk drive 13a and the CD-ROM drive 1 are used.
As for 3c, the recording medium itself can be replaced, and by being supplied in a state where the image data is recorded on this recording medium, it can also be a means of the image input device. Further, when the network is accessed via the modem 14a or the LAN adapter, the image data may be supplied from this network, and in such a case, it may be a means of the image input device. In addition to this, a keyboard 15a for operating the computer main body 12 and a mouse 15b as a pointing device are also connected, and further, a speaker 18a and a microphone 18b are provided to support multimedia.
Is equipped with. On the other hand, a display 17a and a color printer 17b are provided as image output devices.
The display 17a has a display area of 800 pixels in the horizontal direction and 600 pixels in the vertical direction, and each pixel can display the above-mentioned 16.7 million colors. Of course, this resolution is just an example, 640 × 48
0 pixels or 1024 × 768 pixels,
It can be changed as appropriate.

A color printer 1 as a printing device
Reference numeral 7b denotes an inkjet printer, which is capable of printing an image by using dots of CMYK four color inks to print dots on a printing paper as a recording medium. Image density is 360
High-density printing such as × 360 dpi or 720 × 720 dpi is possible, but the gradation table is represented by two gradations such as whether or not color ink is applied. Color inks are not limited to these four colors, but it is also possible to reduce the conspicuity of dots by six colors including light cyan and light magenta. It is also possible to adopt an electrophotographic method or the like. Since an image is input using such an image input device and displayed or output on the image output device, the computer main body 1
In 2, the predetermined program will be executed. Of these, the operating system (OS) 12a operates as a basic program, and a display driver (DSPDRV) that causes the operating system 12a to display on the display 17a.
A printer driver (PRT DRV) 12c for causing the 12b and the color printer 17b to perform print output is incorporated. These types of drivers 12b and 12c depend on the model of the display 17a and the color printer 17b, and can be added and changed to the operating system 12a according to the model. Also, depending on the model, it is possible to realize additional functions beyond the standard processing. That is, it is possible to realize various additional processes within an allowable range while maintaining a common processing system on the standard system called the operating system 12a.

The application 12d is executed on the operating system 12a as the basic program. The processing contents of the application 12d are various, and the keyboard 15a and the mouse 1 as operation devices are used.
The operation of 5b is monitored, and when operated, various external devices are appropriately controlled to execute corresponding arithmetic processing, and further, the processing result is displayed on the display 17a,
It will be output to the color printer 17b. In such a computer system 10, image data can be acquired by reading a photograph with a scanner 11a, which is an image input device, image data taken by a digital still camera 11b, or taken by a video camera 11c. Image data as a moving image can be acquired. Although such image data is finally displayed on the display 17a as an image output device or printed by the color printer 17b, there are often problems such as poor image quality with the original image data. In such a case, some kind of correction is made. Generally, the application 12d for photo retouching or the like makes this correction, but in the image processing system, the printer driver 12c applies the same to the object data output when the application 12d executes the print processing. Perform correction processing. In such a printing process, the application 12d outputs the object data to the operating system 12a.

FIG. 2 shows a change in processing unit of a print image which is object data output from the application 12d. In the figure, the print image PI generated by the application 12d is output to the operating system 12a. Then, the operating system 12a replaces the input print image PI with a predetermined drawing command based on the drawing command group 12a1 to generate print data. Here, the print data replaced by the drawing command by the operating system 12a is, for convenience of processing, the print image PI formed by keeping the coordinates of the originally drawn image in page units as random rectangular object data. Is divided into Then, the operating system 12a
Arranges the divided rectangular object data at random positions irrespective of the page unit coordinates, that is, at random positions not corresponding to the image on which the print image PI is drawn. (N)
To form.

That is, although the internal data of the area divided by the rectangle in each of the divided object data a (1) to a (n) represents the data corresponding to the area where the coordinates are continuous, Adjacent divided object data a (1) to a (n) have no continuity in terms of coordinates. Therefore, the adjacent divided object data a (1) to a (n) are discontinuous data, and printing is performed based on the arrangement order of the formed divided object data a (1) to a (n). However, it is impossible to reproduce the normal print image PI. In this way, the divided object data a
When printing the print image PI divided into (1) to a (n), the divided object data a (1)
.. to a (n) are input to the printer driver 12c, and image processing such as color tone processing and enlargement / reduction processing is appropriately executed. After these image processings, the raster data b (1) to
b (n) is formed and output to the color printer 17d.

In such a case, the printer driver 12c is
In order to sequentially form the raster data b (1) to b (m) described above in band units, the divided object data a (1) to a (n) randomly arranged are related to the divided object data a. (1) to a (n) are selected and stored in the spool file 12c1. Then, a predetermined data area is extracted from the divided object data a (1) to a (n) stored in the spool file 12c1 and is expanded on the memory 12c2, and the above-mentioned color tone processing and enlargement / reduction processing are executed. The printer driver 12c can be used in the module 12c3 that executes image processing. The memory 12c2 may be a predetermined storage area provided in the hardware printer driver 12c, or a recording area such as an EEPROM (not shown) attached to the computer body.

FIG. 2 shows a change in processing unit of a print image which is object data output from the application 12d. In the figure, the print image PI generated by the application 12d is output to the operating system 12a. Then, the operating system 12a replaces the input print image PI with a predetermined drawing command based on the drawing command group 12a1 to generate print data. Here, the print data replaced by the drawing command by the operating system 12a is divided into object data composed of a plurality of rectangles for the convenience of processing in the operating system 12a. Then, the operating system 12a arranges the divided rectangular object data at a random position regardless of the coordinates of the page unit, that is, at a random position without corresponding to the image on which the print image PI is drawn. (1) to a (n) are formed.

That is, although the internal data of the area divided by the rectangle in each of the divided object data a (1) to a (n) represents the data corresponding to the area in which the drawing coordinates are continuous, The divided object data a (1) to a (n) adjacent to each other are not necessarily continuous in terms of coordinates. Therefore, the adjacent divided object data a (1) to a (n) are discontinuous data, and printing is performed based on the arrangement order of the formed divided object data a (1) to a (n). However, it is impossible to reproduce the normal print image PI. When printing the print image PI divided into the divided object data a (1) to a (n), the predetermined divided object data a (1) to a (n) are input to the printer driver 12c. In addition, image processing such as color tone processing and enlargement / reduction processing is appropriately executed. Then, after these image processes, the raster data b that can be processed by the color printer 17b is processed.
(1) to b (n) are formed and output to the color printer 17d.

In such a case, the printer driver 12c is
In order to sequentially form the raster data b (1) to b (m) described above in band units, the divided object data a (1) to a (n) randomly arranged are related to the divided object data a. (1) to a (n) are selected and stored in the spool file 12c1. Then, the module 12c3 included in the printer driver 12c for executing the image processing such as the color tone processing and the enlargement / reduction processing described above from the divided object data a (1) to a (n) stored in the spool file 12c1 performs the image processing. The data area to be processed is extracted, and the same module 12c3 is used.
Are expanded in the memory 12c2 in a usable state.

Next, FIG. 3 shows a schematic configuration of the system in which the printer driver 12c is incorporated in the operating system 12a. In the figure, when there is a print request from the application 12d, the API layer accesses the function management object P1 provided by the printer driver 12c. This function management object P
1 executes the management of the divided object data a (1) to a (n) by the divided image management object P2, and acquires the processed image by the processed image management object P3. When acquiring the processed image, the function management object P1 is the same as the processed image management object P3.
To the required area, and as a precondition for the processing, the divided image data a (1) to a (n) are subjected to the divided image registration processing in advance.

That is, the processed image management object P3
The enlargement processing object P4 that executes the actual image processing
Since the divided image management object P2 is notified of the image area to be processed via the emphasis processing object P5, the divided image management object P2 is already registered in the divided object data a (1) to a (n). Only the necessary ones are expanded on the memory 12c2 and made available, and the emphasized processing object P5 and the enlargement processing object P4 execute image processing using the expanded results. Therefore, in the image processing program according to the present invention, the function management object P1 described above is used.
The divided image management object P2 and the processed image management object P3 constitute a driver according to the present invention, and the enlargement processing object P4 and the emphasis processing object P5 constitute a module for executing the image processing according to the present invention. To do.

FIG. 4 shows the input divided object data and the acquired processed image. In the figure,
If the original image is called a source image and the image subjected to the enlargement processing and the emphasis processing is called a destination image, the input divided object data is divided into nine S-Units. ． a to i. Here, the destination image can be processed as a unit, but in this case as well, it is assumed that the divided image is processed separately, and each divided image is processed by the D-Unit. Called A to C. D-Unit. A to C
It is necessary to be able to use the unprocessed image area in order to obtain S-Unit. a
It is not known whether or not all of them are available through ~ i. Therefore, the corresponding S-U from the processed image management object P3 to the divided image management object P2
nit. a-i are requested to be made available, and thus made available by S-Area. a to c. However, this S-Area. a to c are D-Unit. It does not match A to C, but includes a peripheral region. The reason why the peripheral region is included in this way is that when the image processing is performed by the enlargement processing object P4 and the emphasis processing object P5, the processing cannot be performed only by the processing target pixel, and the surrounding pixels must be referred to. is there.

Next, the peripheral area referred to in each image processing is shown in FIGS. Although details of specific processing are not described in detail, it is necessary to refer to one pixel on the upper and left sides and two pixels on the right and lower sides with respect to the target pixel in the enhancement processing shown in FIG. Further, in the enlargement processing shown in FIG. 6, it is necessary to refer to one pixel on the right and left sides and two pixels on the upper side with reference to the target pixel. Filtering is an example of a specific calculation that needs to refer to the peripheral region. If applied to the example of the emphasis process and the enlargement process in this case, a filter for 4 × 4 pixels is used in the emphasis process and a filter for 3 × 4 pixels is used in the enlargement process.
It can be said that a peripheral area is needed. FIG. 7 shows a process in which the processing image management object P3 notifies the divided image management object P2 of the required area. In the figure,
When the processing image management object P3 requests the area of the finally acquired processing image as the first required area S-Area ', the processing image management object P3 notifies the enlargement processing object P4 of this. Then, in the enlargement processing object P4, when the enlargement magnification of itself is 2 times, the image area which is the source of the necessary area S-Area 'is 1/2 times. However, the reference pixel is
The emphasis processing object P5 is notified that there are 1, 2, 2, and 1 pixel for each of the right side, the lower side, and the left side. Since the enhancement processing object P5 does not perform enlargement, what is originally required is the image area required by the enlargement processing object P4.
It is 1/2 times a ′ and (1,
2, 2, 1) pixels. However, it is necessary to refer to the peripheral area even in self, and further, (2
1, 1, 1) Pixel-added image management object P
Notify 2. That is, the image area S-Area that has been modified in this way is an area that is 1/2 times the required area S-Area 'and (3,3,3,2) pixels in the peripheral area thereof. . Of course, the size of such a peripheral area depends on the enlargement processing object P4 and the emphasis processing object P.
5 depends on the calculation method of No. 5, and in another calculation example, 2 pixels are required for all of the upper, lower, left and right sides in the emphasizing process, while one pixel is required for the upper and left sides and 2 pixels for the right and lower sides in the enlarging process There is also something like doing.

On the other hand, the divided image management object P2 is
Individual divided object data is input via the function management object P1, and while the information as an area is managed, the substance is stored in a spool file and the divided image registration is performed. Since the spool file is stored on the hard disk 13b, other processing objects cannot be directly referenced or used. However, the divided image management object P2 is expanded on the memory so that the image area S-Area notified as described above can be used by other objects. At this time, the required image area S-Area
8 is not expanded on the memory as it is, but as shown in FIG. 8, the S-Unit. a to i is investigated and all applicable S-Unit. Expand a to i on the memory. Here, if the number of divided object data is small, the S-Unit. a
It is easy to determine which is ~ i. Each S-
Unit. The actual data of a to i are stored in the hard disk 13
Although it is stored in b, the header information about each area is stored in a table as shown in FIG. The following S-Unit. A pointer next_ptr indicating the information start position of a to i is provided. Originally, by tracing this pointer, all S
-Unit. Although it is possible to refer to the header information of a to i, each S-Unit. a to i are image areas S-Area
It is necessary to repeat some comparison operations to determine whether or not some of them overlap, which results in a large number of operations. On the other hand, not all S-Unit. There is no need to compare with a to i, and in reality, S-Uni that should be referred to
t. a to i are limited. For example, in the case of the example shown in FIG. 9, when the S-Area is expanded, an S-
Unit. It suffices if only a to i can be referred to, and temporarily, the pointer next_pt in this table.
I try to transfer r.

In the present embodiment, the pointer next
S-Unit._referenced by _ptr. a-i is transferred to form S-Area indirectly to form S-Unit. a
~ I is specified and a configuration capable of generating S-Area at high speed is adopted, but of course, the method for enabling rapid generation of S-Area is not limited. As shown in FIG. 21, the S-Unit. a ~
i may be stored in a memory such as a main memory or a cache memory that can be accessed at a relatively high speed as compared with a hard disk, and may be referred to when the S-Area is generated. Unit. a to i
D 1 to 9 are distributed, and S-Unit. It is also possible to form an ID table that is arranged in such an order that a to i can form the original image of the source image and refer to the table when generating the S-Area.

As described above, all S-Us in which the divided image management object P2 includes the image area S-Area.
nit. After expanding a to i on the memory, the emphasis processing object P5 executes the emphasis processing, and then the enlargement processing object P4 executes the enlargement processing. In the enhancement process, (2,1,1,1) pixels are required as the peripheral region of the target pixel, and the image region generated as a result of the enhancement process is shown in FIG.
As shown in 0, the peripheral area is an area within a broken line in which (2,1,1,1) pixels are omitted. Similarly, in the enlargement process, (1, 2, 2, 1) pixels are required as the peripheral region of the target pixel, and the image region generated as a result of the emphasis process is defined as the peripheral region as shown in FIG. 1, 2,
2, 1) It becomes an area within a broken line excluding pixels. Of course, since the enlargement processing interpolates and generates grid points inside,
The obtained processed image is vertically and horizontally doubled, and as a result, coincides with the first required area S-Area '.

Next, another embodiment in which the divided image management object P2 expands S-Area on the memory will be described. FIG. 23 shows a schematic configuration of the system in which the printer driver 12c in this embodiment is incorporated in the operating system 12a. In the figure,
The function management object P100 provided by the printer driver 12c is accessed from the API layer, and the function management object P100 manages the divided object data by the divided image management object P200, and enlarges and colors the processed image management object P300. Image data for which image processing related to
Each line is acquired, and the acquired image data for each line is accumulated to generate image data forming a destination image.

Specifically, in each module, the color tone processing object P500 is the divided image management object P
The color tone processing is performed on the image data of a predetermined line unit delivered from the unit 200 to form image data of a predetermined line unit, and the image data is delivered to the enlargement processing object P400. Next, the enlargement processing object P400 performs enlargement processing on the image data that has been subjected to this color tone processing,
One line of image data is formed and passed to the processed image management object P400, and the function management object P100
Acquires the image data line by line from the processed image management object P300 and accumulates the image data to generate a destination image.

Here, in the present embodiment, since the enlargement processing object P400 generates the image data after the enlargement processing of one line, it requires five lines of image data including the one line and the reference line. . Therefore, the color tone processing object P500 is notified of the delivery of the image data of 5 lines. Further, since the color tone processing object P500 generates the image data after the color tone processing of one line, only the image data of the one line is necessary. Therefore, the divided image management object P200 is requested to deliver one line of image data. Of course, the number of lines required for these processes is
It is not particularly limited, and can be appropriately changed according to the processing content of each object.

Next, FIG. 24 shows the divided object data input and the acquired processed image. In the figure, the original image will be referred to as a source image, and the processed image subjected to the enlargement processing and the color tone processing will be referred to as a destination image. In addition, the input divided object data is S-Unit. A to I. here,
The destination image can be processed as a unit, but in the present embodiment, it is divided into line units and generated for each line, and the generated destination images are stacked for each final image. Shall be generated. In addition, each divided image for each line that divides the destination image is a D-line. 0-n
Call. Here, n is an integer and indicates the total number of lines of the generated destination image. First, D
-Line. In order to obtain 0, the processed image management object P300 sets 1 for the enlargement processing object P400.
Notify the delivery of the line. Here, the enlargement processing object P400 needs the image data of 5 lines as described above in order to execute the enlargement processing of 1 line. Therefore, the next color tone processing object P500 is notified of the delivery of five lines. The color tone processing object P500 can process the color tone processing with one line of image data, and therefore notifies the divided image management object P200 of the delivery of one line of image data.

Then, the divided image management object P20
0 indicates divided image data S-Unit. A predetermined line of image data is formed from A to I, and is transferred to the color tone processing object P500. Color tone processing object P500
Performs the tone processing on the delivered data of one line, and when the tone processing is completed, the enlargement processing object P4
Since 5 lines are requested from 00, the divided image management object P is displayed until the color tone processing for 5 lines is completed.
200 is notified of the delivery of one line, and the divided image management object sequentially produces one line according to the request and passes it to the tone processing object. Then, the color tone processing object P500 sequentially performs color tone processing on the delivered image data of one line. Color tone processing object P500
When the color tone processing for the five lines ends, the five lines are handed over to the enlargement processing object P400. The enlargement processing object P400 refers to the four back lines of the delivered five lines and performs the enhancement process of the first one line. Then, the color tone processing and the emphasis processing are performed 1
A line destination image is generated and delivered to the processed image management object P300.

When the first one-line destination image is generated, the destination images are sequentially generated line by line up to n lines. In generating the image of one line, the processed image management object P300 notifies the enlargement processing object P400 of the delivery of one line. Here, the enlargement processing object P400 has already been handed over five lines for which the color tone processing has been completed. Therefore, in order to treat the first one of the five lines as a non-reference and to perform the enlargement process for the second line, the tone processing object P5
00 is notified of the delivery of one line. Upon receiving this notification, the color tone processing object P500 notifies the divided image management object P200 of the delivery of one line.
The divided image management object P200 is S-Unit.
A predetermined one line is formed from A to I and delivered to the color tone processing object P500. Color tone processing object P50
0 performs color tone processing on the delivered one line and delivers it to the enlargement processing object P400. The enlargement processing object P400 adds the delivered one line to the end of the already delivered four lines to form a processing area of five lines, and performs the enlargement processing on the second line described above. When the enlargement processing is completed for this second one line, it is delivered to the processed image management object P300. Function management object P10
0 sequentially accumulates the image data of each line in which each process is performed by each object acquired by the process image management object P300 in this way to generate a destination image.

As described above, first, the divided image management object P200 develops and delivers a one-line image area to the color tone processing object P500 on the memory, and the color tone processing object P500 executes the color tone processing to obtain the color tone. When the image data of 5 lines is generated in the processing object P500, the enlargement processing object P40 is generated.
Deliver to 0 and execute enlargement processing. Then, the image data of one line generated from the five lines is transferred to the processed image management object P300. Then, after that, one line of transfer notification and formation is performed among the processed image management object P300, the enlargement processing object P400, the color tone processing object P500, and the divided image management object P200, or one line of image data for which image processing has been executed. Are sequentially delivered in the reverse direction, and are stacked in the function management object P100 to generate a destination image. In the present embodiment, the image data of one line delivered from the divided image management object P200 to the color tone processing object P500 and the image data of five lines or one line delivered from the color tone processing object P500 to the enlargement processing object P400 are S-Area. It goes without saying that it will be configured. Further, in the present embodiment, the order in which the image processing is executed is the tone processing object P500 → enlargement processing object P400, but of course, the present invention is not limited to this, and the enlargement processing object P400 → the tone processing object P500 may be used. Alternatively, only one of the enlargement processing object P400 and the color tone processing object P500 may be executed according to a predetermined setting.

Here, the printer driver 12c is shown in FIG.
Shows the flow of procedures in. Although FIG. 3 shows a schematic configuration of the printer driver 12c incorporated in the operating system 12a, FIG. 3 shows the printer driver 12c from the viewpoint alone. The process is divided into a process close to the function of the driver and a process close to the additional function, and the driver function is summarized in the left column and the module function is summarized in the right column. That is, in procedure 1, there is a source image acquisition process as a driver function, which can be said to be a function of the function management object P1 and the divided image management object P2. Next, in procedure 2, there is a photo instance acquisition process, which is for confirming the current execution process target in order to process each object image separately and in parallel.

The above corresponds to the pre-processing, and in the process flow, the process image area is notified from the module side to the driver side in the procedure 3 as described above, while in the procedure 4, the requested process image area is transmitted. Source image (S-
Unit. The driver side registers a to i), and subsequently, in step 5, the emphasis process and the enlargement process are executed as image processing. In the image processing, the entire object image is evaluated and the processing is executed based on the evaluation result. For example, if a certain object image is entirely dark, it may be brightened by image processing. In this case, since the object image has been divided into divided object data, each object data is evaluated collectively, or the object data is evaluated individually, but finally, each object image is evaluated. Need to be put together.

Originally, there is usually no correspondence between the divided object data and the object image, and this correspondence must be made on the printer driver 12c side. As one method of this correspondence,
There is a method of expanding the divided object data in the virtual area and connecting the object images, and another method is to judge whether or not they are the same object image based on the overlapping of the divided object data and the adjacency. Which method is used depends on the system.

On the other hand, as described above, in order to evaluate an object image for image processing, it is effective and simple to sample pixel information over the entire object image. Such sampling may be performed before or after the correspondence between the object image and the divided object data is known. That is, it is possible to sample each divided object data before the correspondence is known, and integrate the sampling results after the correspondence is known, or the divided object data corresponding to each object image after the correspondence is known. Can also be sampled. As described above, the execution timing of sampling varies depending on the conditions, and in FIG. 12 as well, it is indicated by a broken line corresponding to three executable timings. It should be noted that it is possible to prepare a module for sampling even if it is performed on the driver side.

The image processing in step 5 is executed by using this sampling result, and the generated image becomes a destination image and is registered in step 6. Then, the registered destination image is output on the driver side in step 7. Then, when the destination image is finally acquired, the source image is released from the memory in step 8. Here, the release timing of the source image is not particularly limited. For example, one S-A
If registration / release is performed for each rea, the used memory area can be reduced, but the work is troublesome. On the other hand, if the used memory area is less limited, it can be said that the work of registration / release does not need to be performed frequently.

In the above example, the required area is notified in the sense of acquiring the destination image, and the generated destination image may be expanded in any memory area. On the other hand, there are cases in which it is desired to perform enlargement processing on the spool file itself. in this case,
The enlarged image may be added to the spool file, and the pointer of the original image file may be linked to the enlarged image file. For example, suppose that there is a process in which a virtual image is constructed by reading from a spool file, image processing is performed, and then the original spool file is rewritten. In this case, if the enlargement process is applied to the image file in the spool file, the enlargement process need not be realized on the virtual image. However, since the enlargement process makes the image file larger than the image file in the spool file, it cannot be rewritten with the enlarged image file. Therefore, the enlarged image data is added after the spool file so that the pointer links are switched.

Next, a specific method of enlargement processing will be described. In general, a process of newly generating pixels between lattices of an image composed of dot matrix pixels is called an enlargement process and is widely executed. This is to solve the problem that, when the resolution of the display 17a and the resolution of the color printer 17b are different, if they are assigned in pixel units, they are not displayed in a certain size. Here, the following method is known for the enlargement processing. 1. Nearest-neighbor interpolation method (simple padding copy) 2.3 Convolutional convolutional interpolation (hereinafter referred to as cubic interpolation) The former one is the mathematically fastest enlargement method, and the latter one obtains a clean enlargement result. On the other hand, it has a feature that it requires a large amount of calculation mathematically and takes time. In any case, these are called filter processing in the technical term of image processing. Here, FIG.
3 and FIG. 14 show the principle of generating the enlarged image A from the unenlarged image a by using separate filters [1] and [2]. In this case, one point of the image A after enlargement can be obtained by applying the filters [1] and [2] using several points of the image a before enlargement. Therefore, the calculation is essentially repeated for all the pixels of the image A after enlargement.

By the way, there should be a difference in the processing results between the filters [1] and [2]. That is, the former looks rough and the latter looks smooth. However, when printing is performed using the enlargement result, the difference cannot always be recognized due to the limit of recognition of human eyes. That is, a filter that requires a high degree of computation [2]
In some cases, it is not possible to recognize the difference in the enlargement result between the case of enlargement by itself and the case of enlargement by using the filters [1] and [2] together. FIG. 15 shows the latter procedure,
Enlargement processing is performed on the original image a by using the filter [2], and once the image a ′ is generated, enlargement processing is executed by using the filter [1] to obtain the image A. ing. Needless to say, the enlargement process of the filter [2] requires cubic interpolation and therefore may be executed by a module, and the enlargement process of the filter [1] may be realized by a driver. In this case, of course, the difference can be seen with the naked eye depending on the magnification of the filter [1] and the filter [2]. However, if the combination is in a range in which such a difference is unknown, the filter [2] that requires a long processing time can be used. Since the area of the generated image a'is small, high-speed processing can be expected. This is because the calculation amount increases in proportion to the area of the image after the enlargement processing.

FIG. 16 shows the arrangement of existing grid points and interpolation points in the case of cubic interpolation, and Equation 1 shows the filter processing of this cubic interpolation by a matrix calculation formula.

[Equation 1] ---- shiki ---- Regarding the function f (t), f (t) = {sin (πt)} / πt , By replacing U or V with W, t0 = 1+ (W- | W |) t1 = (W- | W |) t2 = 1- (W- | W |) t3 = 2- (W- | W |) Can be expressed as

Although such a cubic interpolation calculation generally requires a large amount of calculation, it can be speeded up depending on the position of the interpolation point, and more specifically, it is limited to an integral multiple expansion. The throughput can be reduced considerably. It should be noted that the integer multiple referred to here is a magnification at which the origin is placed on the intersection of the grid lines, and does not mean the ratio of the number of grid points before and after the enlargement process. FIG. 17 is a two-fold enlargement in this definition, and FIG. 18 is a three-fold enlargement. In the figure, the large white circle is the origin and the small black circle is the interpolation point. As can be seen from these figures, in the case of integer multiple enlargement, some of the interpolation points are arranged on the grid line. The specific speed-up means will be described below.

(1) Simplification of Calculation of Interpolation Points on Lattice Line In the integral multiple expansion, some of the interpolation points are arranged on the lattice line. Therefore, the expression 1 is simplified (the calculation amount is reduced). That is, the existence of the interpolation points on the grid line means that W (either U or V) becomes zero. Therefore, t0 = 1, t1 = 0, t2 = 1, t
3 = 2. At this time, f (t) is as follows from the above equation. f (0) = 1, f (1) = 0, f (2) = 0 Therefore, when the Y-axis exists on the grid line, the interpolation point on the X-axis is

[Expression 2] ---- shiki ---- will be calculated, and the interpolation points on the Y axis when they are on the grid line with respect to the X axis are

[Equation 3] It will be calculated by ---- shiki ----. As is clear from the equations 2 and 3, the calculation of the enlargement processing can be simplified.

(2) Speed-up by preparing a plurality of filters The interpolation point located on the grid line at the time of integer multiple is the most peculiar example, but the magnification is fixed and the interpolation is performed even when it is not on the grid line. If you prepare filter processing for each point,
Since f (t) can be made constant, the arithmetic processing can be speeded up. In such a case, if f (t) is made constant,

[Expression 4] ---- shiki ---- will be represented. Where A to D and K
˜N can be uniquely determined by the location W of the interpolation point, and may be calculated in advance and stored in the table.

Here, referring to FIG. 17 for the case of doubling in the enlarging process, it is necessary to locally interpolate four points.
In case of expanding to, four filters will be prepared. This is shown in FIG. 19, and assuming that a plurality of filter processes are prepared, f (t) can be made constant. The specific speed-up that realizes the constant f (t) is as follows. First, f
(T) can be made constant and the speed can be increased by itself. This is because the constantization of f (t) means removal of the operation of the cubic interpolation function represented by f (t). Next, the speed can be increased by changing the calculation type. Generally, the same one-time multiplication for the CPU
“Constant * Variable” is faster than “Variable * Variable.” Therefore, when comparing Equation 1 and Equation 4, Equation 4
It turns out that is faster. Furthermore, by using one of the constants and substituting the multiplication of "constant * variable" with the operation table, the speed can be increased.

The effects of the above speedup can be summarized as follows. According to the conventional method of performing one filtering process in order to obtain one interpolation point, it is necessary to calculate a cubic interpolation function and to calculate 20 times "variable * variable". However, as described above, when a plurality of filter processes are assumed, it can be realized by: 16 times access to the operation table; 4 times "constant * variable" operation. Therefore, the speedup can be realized by preparing a plurality of filters. Further, the simplification of the calculation of the interpolation points on the grid line described above can be realized by preparing a plurality of filter processes in the same manner. And speeding up by preparing such multiple filter processing,
Speeding up by simplifying the formula of the interpolation points on the grid line is effective at any multiple as long as it is an integral multiple.

(3) Other speedups (a) Simplification of arithmetic expression of peculiar interpolation point in n-th power expansion of 2 In n-th power expansion of 2 (n is an integer of 1 or more), Interpolation points are placed on the grid line (broken line in FIG. 17) that connects the origin on the side and the point at a location that is half the origin, but on the X axis,

[Equation 5] ---- shiki ---- Is represented by, and on the Y-axis,

[Equation 6] It is represented by ---- shiki ----. In this case, by utilizing the symmetry of the vector, it is possible to obtain the interpolation point by only accessing the calculation table 16 times and calculating the "constant * variable" twice.

(B) Saving the operation amount by saving the operations that can be shared between the filters It has already been described that the speed can be increased by preparing the filters for the number of interpolation points, but the operations that can be shared by the filters are saved. By doing so, the amount of calculation can be saved. (C) Example of speeding up in 4 times expansion FIG. 20 shows a coding example in 4 times expansion. The lines to which the above-mentioned speedup is specifically applied are annotated. That is, the speedup is represented by the following methods: -copying the origin-simplified formula on the grid line-storing operations that can be shared between filters-simplified formula with a singularity of n times the power of 2.

As described above, the processing amount can be considerably reduced only by the interpolation multiplication of an integral multiple. Therefore, it was found that specifying the interpolation position locally is effective for speeding up. When applying the method of interpolation enlargement by such an integral multiple, it is conceivable to apply not only interpolation of integral multiple but also interpolation enlargement of a small number. Here, with respect to another embodiment of the enlarging process, a small number of times, specifically, 1.
Consider 25 times the interpolation magnification. FIG. 25 shows the local effect of this 1.25-fold interpolation enlargement. In the figure, the local 1.25 times means that the origin of 4 points is set to 5 points including 1 point of interpolation points. That is, it means expanding the 16 origins to 25 points including the interpolation points on the plane.

Therefore, as shown in FIG. 25, the coordinates of the interpolation point can be preliminarily estimated, and the efficiency of the calculation and the reduction of the calculation amount by that are the same as those in the embodiment by the above-described integral multiplication by the integral multiple. Is. Therefore, it suffices to prepare an optimum filter for each interpolation point.
Here, the filter for each interpolation point is called a child filter, and 25 points of pixels including interpolation points are generated from the origin of 16 points. The entire filter using these child filters is called a filter 16to25. Here, the vector elements required for the child filters that form the filter 16to25 are shown. 1024-times vector element P1: {0, 1024, 0, 0} required to obtain P1 to P5 P2: {VA, VB, VC, VD} P3: {VE, VF, VG, VH} P4 : {VH, VG, VF, VE} P5: {VD, VC, VB, VA} Note that VA to VH are constants that are obtained in advance from the three-dimensional interpolation function and its interpolation position.

In this way, when considering an image to be multiplied by 1.25 times, the filter 16to25 is periodically passed through 16 points. However, it is self-evident that, in general, there is a surplus area that cannot pass the filter 16to25. Therefore, when applying the filter 16to25, it is necessary to consider the influence of the reference pixel. This extra area will be passed through another filter, resulting in non-uniformity and distortion. However, this is assumed to be within the error of the human eye.

Here, the relationship between the sizes of the source image and the destination image when passing through the filter 16to25 will be shown. If the length of one side of the source image is sL, the length dL of one side of the destination image obtained through the filter 16to25 is as follows. -DL = {(sL-1) / 4} * 5 + 1 {} is an integer part ... Formula (1). However, if there are a plurality of continuous local portions and there is no influence of the reference pixel, then: dL = {sL / 4} * 5 ... Equation (2).

Next, when the number of pixels forming the image data is a multiple of 4, it will be verified that 1.25 times the interpolation enlargement is performed. Specifically, in this embodiment, it is said that “1280 pixels * 960 pixels”, which is required for interpolation enlargement of a digital camera, is interpolated and enlarged by 1.25 times, and is corrected to “1600 pixels * 1200 pixels”. Verify that. In such a case, the X coordinate and the Y coordinate have a pixel number of 4 * N of 5 when N is an integer.
It indicates that the number of pixels is converted to * N. Substituting 4 * N into sL using the equation (2), dL_1 = [4 * N / 4] * 5 ... (3) = [N] * 5 = 5 * N It can be seen that a typical 1.25 times is available. However, when considering the overall size, equation (1)
Since it must be considered based on the following, dL_2 = [4 * (N-1) / 4] * 5 + 1 ... (4) = [N-1 / 4] * 5 + 1 ... (4-1 ) = 5 * N-4 ... (4-2). Expression (4-2) shows a state where the destination image is insufficient by four pixels, and Expression (4-1) is (N−
1) Indicates that the filter 16to25 is passed only once. From this, filter 1 in the source image
Pixels to which 6to25 can be applied are 4 * (N-
It can be seen that 1) point and 4N-4 (N-1) = 4 points remain unprocessed. In addition, the pixels that can be extracted by the filter 16to25 as the destination image are
5 * (N-1), which means that 5N-5 (N-1) = 5 points cannot be generated. Therefore, the remaining 4 of the source image
It is necessary to consider a method for generating the missing 5 points in the destination image from the points.

FIG. 26 shows a method of generating the insufficient 5 points in the destination image from the remaining 4 points of the source image. In the figure, three points are locally set to four points, that is, 4/3 = 1.3333 ... Here, the vector elements required for this local 1.3-fold interpolation enlargement are as follows. 1024 multiplied vector elements P1: {0, 1024, 0, 0} required to obtain P1 to P4 P2: {VK, VL, VM, VN} P3: {VX, VY, VY, VX} P4 : {VN, VM, VL, VK} Note that VK to VN, VX, VY are constants obtained in advance from the three-dimensional interpolation function and its interpolation position.

From the above, with respect to the part which cannot be processed by the filter 16to25, the filter 12to25X is in the X direction and the filter 12to25Y is in the Y direction.
To use. In addition, the filter 9to16 is used for a portion that cannot be multiplied by 1.25 in both the X and Y directions. Here, a correlation diagram showing the correlation between the origin and the interpolation point when using this filter 12to15Y is shown in FIG. 27 (filter 12to
25X is a figure rotated 90 degrees. ). in this way,
In the 1.25 times interpolation enlargement, the 1.25 times and 1.3 times interpolation enlargements are locally executed. In such a case, the filter 16to25, the filter 12to20X, the filter 12
When the to20X and the filter 9 to 16 are used, the interpolation enlargement can be performed, and accordingly, the interpolation enlargement processing can be speeded up.

When the vector elements required by these filters are put together, 14 vector elements are required. Therefore, multiplying each vector element by 0-255, 2
It is possible to reduce the number of operations by using 14 operation tables formed of 56 elements. Here, if the size of one element of this operation table is 4 bytes, the size of one operation table is 1024 bytes (1 KB). Since there are 14 of these, the memory required for the operation table is 14 KB.

In this way, after the source image acquisition processing (procedure 1) and the photo instance acquisition processing (procedure 2), the module side notifies the driver of the processed image area (procedure 3). ) At this time, by adding the necessary peripheral area to each image processing module, the driver side registers the source image (S-Unit) after adding the necessary peripheral area to the requested processed image area. (Procedure 4), the image processing (enhancement processing and enlargement processing (Procedure 5)) is sequentially executed using this, and even when the image processing requires the peripheral area, the necessary area is secured very simply. Then, the processing can be executed.

[Brief description of drawings]

FIG. 1 is a block diagram of a computer system that executes an image processing program according to an embodiment of the present invention.

FIG. 2 is a diagram showing a change in a processing unit of a print image.

FIG. 3 is a diagram showing a schematic configuration of a printer driver installed in an operating system.

FIG. 4 is a diagram showing a processing unit of an image.

FIG. 5 is a diagram showing a peripheral area necessary for an emphasis process.

FIG. 6 is a diagram showing a peripheral area necessary for enlargement processing.

FIG. 7 is a diagram showing a process of notifying a required area from a module side to a driver side.

FIG. 8 is a diagram showing a relationship between S-Area and S-Unit.

FIG. 9 is a diagram showing a pointer table of S-Unit.

FIG. 10 is a diagram showing a substantial processing target area when executing emphasis processing.

FIG. 11 is a diagram showing a substantial processing target area when executing enlargement processing.

FIG. 12 is a diagram showing a procedure flow in a printer driver.

FIG. 13 is a diagram showing enlargement processing by the first filter processing.

FIG. 14 is a diagram showing an enlargement process by a second filter process.

FIG. 15 is a diagram showing an enlargement process by a two-step filter process.

FIG. 16 is a diagram showing a relationship between lattice points of cubic interpolation and interpolation points.

FIG. 17 is a diagram showing the relationship between grid points and interpolation points for double interpolation.

FIG. 18 is a diagram showing a relationship between grid points and interpolation points for triple interpolation.

FIG. 19 is a diagram showing an enlargement process by cubic interpolation using four filter processes.

[Fig. 20] Fig. 20 is a diagram illustrating a coding example in a 4-fold enlargement.

[Fig. 21] Fig. 21 is a diagram when S-Units to be processed are separated and stored.

FIG. 22 is a diagram showing an S-Unit processing area table.

FIG. 23 is a diagram showing the configuration of a printer driver installed in an operating system according to another embodiment.

FIG. 24 is a diagram illustrating an image processing unit according to another embodiment.

FIG. 25 is a diagram showing a relationship between grid points and interpolation points of 1.25 times interpolation.

FIG. 26 is a diagram showing a relationship between grid points and interpolation points for 1.3-fold interpolation.

FIG. 27 is a correlation diagram showing the correlation between the origin and the interpolation point when using the filter 12to15Y.

[Explanation of symbols]

10 ... Computer system 11a ... Scanner 11a2 ... Scanner 11b ... Digital still camera 11b1 ... Digital still camera 11b2 ... Digital still camera 11c ... video camera 12 ... Computer body 12a ... Operating system 12b ... Display driver 12c ... printer driver 12d ... application 13a ... Floppy disk drive 13b ... hard disk 13c ... CD-ROM drive 14a ... Modem 14a2 ... Modem 15a ... keyboard 15b ... mouse 17a ... display 17b ... Color printer 18a ... speaker 18b ... Mike

─────────────────────────────────────────────────── --Continued from the front page (58) Fields surveyed (Int.Cl. ⁷ , DB name) G06T 1/20 G06T 5/00

Claims (5)

(57) [Claims] 1. When appropriately arranging an object image in a region representing an image composed of pixels arranged in a dot matrix, a plurality of divided object data are generated to represent the same object image, and each object image is generated. A medium for recording an image processing program for causing a computer to execute predetermined image processing, the image processing program executing a image processing for each object image with a driver to which the divided object data of the object image is input. A plurality of image processing objects for executing individual image processing.
In addition, the driver spools the divided object data, and when the object data of the image area to be processed by the module is expanded from the spool file on the memory and made available , each image of the module is used. Processing objects sequentially, self
The peripheral area required for image processing of
Of the remaining image processing objects in addition to the image area
Knowing, the edge in the last image processing object
A medium on which an image processing program is recorded, in which an image area added with an area is expanded on a memory . 2. The medium on which the image processing program according to claim 1 is recorded, wherein the driver includes an image area including a peripheral area and expands the divided object data unit on a memory. A medium on which the image processing program is recorded. 3. A medium having the image processing program according to claim 1 or 2 recorded therein, wherein the driver limits the frequently-used divided object data expanded on the memory. A medium having an image processing program recorded thereon, which is characterized by being made available. 4. When appropriately arranging an object image in a region representing an image composed of pixels arranged in a dot matrix, a plurality of divided object data is generated to represent the same object image, and each divided object data is generated. An image processing apparatus for executing a predetermined image processing, comprising: a data management unit to which the divided object data of the object image data is input; and a data processing unit for executing the image processing for each object image, , The data processing means includes a plurality of image processing objects for executing individual image processing.
And has a, the data management unit is configured to spool the divided object data, when the available object data of an image area in which the data processing means is processed to expand from the spool file on the memory, the Each image processing object that the data processing means has
Sequentially, the peripheral area required for self image processing is processed.
In addition to the target image area, the remaining image processing objects
The last image processing object.
The image area to which the peripheral area has been added is expanded on the memory.
The image processing apparatus characterized by 5. When appropriately arranging an object image in a region representing an image composed of pixels arranged in a dot matrix, a plurality of divided object data are generated to represent the same object image, and each divided object data is generated. An image processing method for executing predetermined image processing, comprising: a data management step of inputting divided object data of the object image data; and a data processing step of executing image processing for each object image, and , The data processing step is a plurality of image processing objects for performing individual image processing.
And has a, the data management unit is configured to spool the divided object data, when the available object data of an image area in which the data processing means is processed to expand from the spool file on the memory, the Each image processing object that the data processing means has
Sequentially, the peripheral area required for self image processing is processed.
In addition to the target image area, the remaining image processing objects
The last image processing object.
The image area to which the peripheral area has been added is expanded on the memory.
An image processing method characterized by: