JP2004288198A - Expansion/reduction device and method of image data - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To execute a reduction process for an input image with a small amount of memory. <P>SOLUTION: The input image is divided into a plurality of small regions; each input image on the boundary between the small regions is included in any of the small regions according to a certain rule; and a pixel value of output pixels is calculated based on the output pixels in each small area. The calculation is carried out based on the pixel value obtained by sampling the input pixels in the small area at a predetermined interval. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an image data enlargement / reduction apparatus and method used for enlarging or reducing image data to be displayed or printed using an information processing apparatus at an arbitrary magnification.

  When transferring image data between applications having different image data resolutions in personal computers, printers, and other various information processing devices, image data enlargement / reduction processing for adjusting the resolution by increasing or decreasing the number of pixels is performed. Done. When storing image data having a large number of pixels in the memory, a reduction process of the image data for reducing the number of pixels is performed to reduce the storage capacity of the memory. In order to increase the transmission speed when transmitting and receiving image data via a communication line, a reduction process of image data for reducing the number of pixels may be performed.

Here, for example, when the number of pixels in the vertical and horizontal directions of the image data is respectively enlarged to an integral multiple, the number of pixels is increased by copying each pixel in the vertical and horizontal directions by the magnification. Therefore, for example, each pixel is copied N times in the X direction and M times in the Y direction to obtain image data composed of N × M pixels.
On the other hand, when performing enlargement / reduction at a magnification that does not become an integral multiple in either direction, such as 1.5 times or 2.5 times, a pixel whose number is increased by copying and a pixel which is not copied are determined. Mix appropriately.

When copying pixels, the simplest method is to increase the number of pixels having the same pixel value next to each other. However, in that case, in the case of an image expressing a halftone, unnatural shading occurs and the image quality deteriorates. This tendency is particularly remarkable when image data is enlarged / reduced at a magnification that does not become an integral multiple.
Therefore, appropriate arithmetic processing is performed with reference to a plurality of peripheral pixels so that the pixel values of the pixels increased by copying in the output image change smoothly with each other. This method is called a resampling process, and a primary interpolation method, a nearest neighbor method, or the like is used for calculating a pixel value of each pixel.

By the way, the conventional techniques as described above have the following problems to be solved.
As described above, when the input image data is to be enlarged / reduced in the X-axis direction or the Y-axis direction at an arbitrary real magnification, that is, at a magnification other than an integral multiple, the pixel value of the primary interpolation method or the nearest neighbor method is used. A calculation is made. At this time, the pixel values of the input pixels existing around the output pixel whose pixel value is to be obtained must be prepared in advance so that they can be used for the calculation. Therefore, it is necessary to read almost one page of image data or an amount necessary for referring to a pixel value, store the image data in a buffer memory in advance, and then receive and process the same image data again in order. In this case, it is not possible to obtain the output by sequentially processing the image data as it is.
Therefore, the prior art has a problem that the processing time is long, contrary to the object of efficiently using the memory in various systems.

The present invention employs the following configuration to solve the above points.
<Configuration 1>
In a method of enlarging / reducing image data by generating a plurality of output pixels by reducing a plurality of input pixels forming input image data into a plurality of output pixels at a predetermined magnification, the input image data is divided into small areas. The input pixels included in the area and the input pixels on the boundary of the small area are distinguished and recognized, and the input pixels in the small area are determined based on the input pixel value in the small area and the input pixel value on the recognized boundary. A method for enlarging / reducing image data, comprising calculating an output pixel value by calculating a value.

<Configuration 2>
In the configuration 1, the calculation of the input pixel value is performed based on an input pixel value obtained by sampling input pixels in the small area at a predetermined interval.

<Configuration 3>
In a second aspect, there is provided an image data enlargement / reduction method, wherein a sampling area for sampling an input pixel in the small area is designated, and an output pixel value is obtained by calculating a pixel value in the sampling area.

<Configuration 4>
In an image data enlarging / reducing apparatus for generating an output image by reducing a plurality of input pixels forming input image data to a plurality of output pixels at a predetermined magnification, the input image is reduced to a small area including the plurality of input pixels. A boundary line pixel determining means for detecting an input pixel positioned on a boundary line that separates adjacent small regions and determining any of the small regions including the input pixel based on a predetermined condition; And a pixel value calculating means for calculating a pixel value of an output pixel based on each pixel value of a plurality of input pixels included in the image data.

<Configuration 5>
In the fourth aspect, the pixel value calculating means samples a plurality of input pixels in the small area and calculates a pixel value of the output pixel based on the sampled input pixels. apparatus.

<Configuration 6>
In the fifth aspect, the pixel value calculating means sets a sampling area in the small area and calculates a pixel value of the output pixel based on an input pixel in the sampling area. Reduction device.

<Configuration 7>
The input image is equally divided into small regions by a boundary parallel to the main scanning direction and a boundary parallel to the sub-scanning direction, and the pixel values of the pixels included in each region are averaged to obtain the pixel value of the output pixel. , To obtain an output image obtained by reducing the input image,
An input image buffer that receives and holds one line of pixel values of pixels constituting the input image when viewed in the main scanning direction;
The pixel value of each pixel received in the input image buffer is sequentially accumulated in the main scanning direction, and is obtained before a boundary parallel to the sub-scanning direction and before a boundary pixel closest to this boundary is detected. An intermediate result buffer that holds the sum of pixel values in the same small area in small area units,
The input image is processed one line at a time in the sub-scanning direction, and a pixel value in each small area obtained before a boundary pixel closest to the boundary before the boundary parallel to the main scanning direction is detected. Is read from the intermediate result buffer, divided by the number of pixels included in each small area, an average value of the pixel values of each small area is obtained, and the average value is set as the pixel value of the pixel of the output image. A device for enlarging / reducing image data, comprising a unit.

<Configuration 8>
In the configuration 7, a parameter holding unit that sets and holds a sampling interval is provided in order to sample a part of the pixels included in the small region obtained by dividing the input image, and collect the pixel values, An image data enlargement / reduction device, wherein the intermediate result buffer refers to the parameter holding unit and totalizes and holds pixel values at each sampling interval.

<Configuration 9>
In the configuration 8, in order to divide the pixels included in the small region obtained by dividing the input image into a plurality of sampling regions including an arbitrary number of pixels that are continuous in the main scanning direction, and to collect pixel values for each of the sampling regions, , A sampling total counter is provided, and the control unit obtains an average value of pixel values in the sampling region based on the pixel values totalized for each sampling region and the number of pixels included in the sampling region. An apparatus for enlarging / reducing image data, wherein a sum of pixel values in the same small area, in which average values of pixel values are accumulated, is held in small area units.

<Configuration 10>
A first storage unit that holds a value of N digits after the decimal point in a multiplication result obtained by multiplying an integer value to be processed by a real number, and a second storage unit that stores a number of N digits after the decimal point of the real number Comparing the numerical value stored in the first storage unit with the numerical value stored in the second storage unit, and when the former numerical value is greater than or equal to the latter numerical value, the integer part of the multiplication result is used as the operation result. An integer magnification arithmetic unit, comprising: an arithmetic unit for outputting, and when the former numerical value is less than the latter numerical value, outputting a result obtained by rounding up the decimal point of the multiplication result below a decimal point as an arithmetic result.

<Configuration 11>
A product of the coordinate value of each pixel in the input image and a real number representing the magnification of the input image is obtained, and an integer not exceeding the result of the product is determined as the number of times of copying the pixel, and the output image data is determined. In the obtaining, a register that holds only a numerical value represented by N digits after the decimal point among the results of the product, and that invalidates the numerical value after the decimal point by overflowing, is provided each time an operation for obtaining the product is performed. The numerical value held in this register is compared with the numerical value represented by N digits below the decimal point of the real number representing the enlargement magnification. An image characterized by comprising a magnification calculator for determining the value of the copy to be the number of copies, and when the former is less than the latter, to determine the value of the product obtained by rounding up the decimal point below the decimal point to the number of copies. Expansion of data / Small devices.

<Configuration 12>
An output image is obtained by enlarging the input image at a predetermined real number magnification, and the input pixels are mapped on the output image, and a rectangular area created by the mapped output pixels is included in the nearby area as a nearby area. When calculating the number of output pixels arranged in the coordinate axis direction of the output pixels, a product of a coordinate value indicating the position of the neighboring area in the output image and the magnification is obtained, and an integer not exceeding the result of the product Is determined to be the number of the output pixels in the corresponding neighboring area. In the result of the product, only the numerical value represented by N digits after the decimal point is retained, and the numerical value after the decimal point is overflowed and invalidated. Each time the calculation for obtaining the product is performed, a numerical value held in this register is compared with a numerical value represented by N digits below a decimal point of a real number representing the magnification. If the former is greater than or equal to the latter, a value obtained by rounding down the decimal point of the result of the product is determined as the number of the output pixels.If the former is less than the latter, the decimal point of the result of the product is rounded up. An image data enlargement / reduction apparatus, comprising: a magnification calculator for determining a value of the output pixel to the number of the output pixels.

<Configuration 13>
The image data enlargement / reduction apparatus according to configuration 12, wherein the initial value of the output of the magnification calculator is a preset constant.

<Configuration 14>
A product of the coordinate value of each pixel in the input image and a real number representing the magnification of the input image is obtained, and an integer not exceeding the result of the product is determined as the number of times of copying the pixel, and the output image data is determined. In the obtaining, a register that holds only a numerical value represented by N digits after the decimal point among the results of the product, and that invalidates the numerical value after the decimal point by overflowing, is provided each time an operation for obtaining the product is performed. The numerical value held in this register is compared with the numerical value represented by N digits below the decimal point of the real number representing the enlargement magnification. Determine the truncated value as the number of copies, if the former is less than the latter, a magnification calculation unit that determines the value of the product rounded up to the nearest decimal point as the number of copies, and the end of the output image is printed Extrudes out of possible area The case, calculated on the basis of the magnification of the end of the output image information of the printable area, enlargement / reduction device of the image data, characterized in that it comprises clipping computing device as an initial value of the number of times of copying.

  According to the present invention, an input image is divided into small areas, input pixels on boundaries between the small areas are included in any of the small areas according to a certain rule, and output is performed based on the input pixels for each small area. Since the pixel value is calculated, the input image can be reduced with a small memory.

Hereinafter, embodiments of the present invention will be described using specific examples.
<Specific example 1>
FIG. 1 is an explanatory diagram of the operation of the enlargement / reduction processing unit according to the first example.
FIG. 3A shows an enlargement / reduction table used in the method of the present invention, and FIG. 3B shows input image data and output image data.
For example, when the image is enlarged by (x2 / x1) times in the X direction and by (y2 / y1) times in the Y direction of the input image data 3, as shown in FIG. And a predetermined number of copies in the Y direction. The pixel values are copied as they are. The number of pixels to be copied differs depending on the positions of the pixels of the input image. In this way, enlargement of a magnification that is not an integral multiple is realized. Here, in order to efficiently execute such enlargement / reduction processing, an enlargement / reduction table indicating a magnification in a corresponding direction for each pixel is prepared.

The left table shown in FIG. 1A shows the magnification in the X direction, and the right table shows the magnification in the Y direction. For example, the pixels in the 0th column and the 0th row of the input image data, that is, the pixels numbered 1 in (b) are copied twice in the X direction and three times in the Y direction with reference to these tables. You. The pixels indicated as No. 4 in the second row of the input image data are copied twice in the X direction and four times in the Y direction.
The image data is usually handled as a bit stream, and is processed one pixel at a time in the X-axis direction (main scanning direction), and the processing is repeated in the Y-axis direction (sub-scanning direction). The reason why the enlargement / reduction table as described above is newly provided is that it is possible to serially receive the input image data 3 in the scanning direction in this way and perform the enlargement / reduction processing in that order.

FIG. 2 is a block diagram of an image data enlarging / reducing device according to the first embodiment.
The illustrated device is a device for receiving input image data stored in the external storage device 5 and performing enlargement processing or reduction processing on the image data. The enlargement / reduction device 6 includes a current line buffer 7, an enlargement / reduction table 8, an enlargement / reduction processing unit 9, and an output image frame buffer 11. The current line buffer 7 is a memory for storing and holding image data input from the external storage device 5 in the scanning direction line by line. The enlargement / reduction table 8 stores the magnification table 1X in the X direction and the magnification table 1Y in the Y direction shown in FIG. The enlargement / reduction processing unit 9 is a part that performs the enlargement / reduction processing as shown in FIG. 1B while referring to the enlargement / reduction table 8. The image data after the enlargement / reduction processing is stored in the output image frame buffer 11. An external device (not shown) is connected to the output image frame buffer 11, to which the enlarged / reduced image data is transferred.

Here, a case where image data is stored at an integral multiple and a case where image data is stored at a magnification other than the integral multiple will be described in comparison.
FIG. 3 is a diagram illustrating an enlargement method of an integer magnification.
As shown in the figure, for example, when an original pixel 2 is present, if an attempt is made to double the size in the X direction and double the size in the Y direction, the result is as shown in FIG. Also, if an attempt is made to enlarge by a factor of 3 in the X direction and by a factor of 3 in the Y direction, the result is as shown in FIG. It becomes as shown in. Of course, the same result is obtained even if the magnification in the X direction and the Y direction is freely changed. At an integer multiple, the same processing is performed on all input pixels.

On the other hand, FIG. 4 shows an explanatory diagram of the enlargement / reduction processing by the nearest neighbor method.
In this example, the copy magnification is changed for each pixel in order to enlarge the image data at an arbitrary real magnification in the X and Y directions. For example, the pixel (1) shown in the figure is copied in the output image data 4 so as to be three times in the X direction and twice in the Y direction. The pixel of (2) is copied so as to be twice as large in the X direction and twice as much in the Y direction. Further, the pixel of (5) is copied so as to be three times in the X direction and three times in the Y direction. By such a combination, enlargement processing such as 1.2 times or 2.3 times as a whole is possible. As the reduction processing, for example, reduction in the direction from the output image data 4 to the input image data 3 can be considered. In such a case, each time one output pixel is obtained, processing is performed such as how many consecutive pixels are thinned out in the X direction and how many pixels are thinned out in the Y direction.

  In the process according to the first embodiment of the present invention, when input image data is serially input in the order of (1), (2), (3),... In the drawing, output image data 4 can be obtained immediately. An enlargement / reduction table shown in FIG. 1A was prepared.

FIG. 5 is a flowchart showing the operation of the apparatus shown in FIG. 2, that is, the enlargement / reduction method of the first embodiment.
First, in step S1, an enlargement / reduction table is created. This is a process for creating a table based on data obtained empirically in advance based on the enlargement / reduction magnification. The contents of such a table may be prepared in advance for each enlargement / reduction ratio, or may be calculated and created each time. Further, the information may be created by an operator using any appropriate means and stored in a memory or the like of the information processing apparatus.

  In the next step S2, one line of data (bit stream) is read from the external storage device 5 shown in FIG. In the next step S3, the enlargement / reduction processing unit 9 refers to the magnification table in the vertical direction of the enlargement / reduction table, that is, the Y direction. Further, in step S4, the magnification table in the horizontal direction, that is, the X direction is referred to. When the number of copies of the pixels in the X direction and the Y direction is recognized in this way, in step S5, dot copy is performed for each pixel of the input image. Dot copying refers to copying dots of the same pixel value in the vertical and horizontal directions and increasing the required number. Next, in step S6, it is determined whether or not the horizontal magnification has been copied. Thus, the input pixels are copied in the X direction by the number specified in the table.

Next, in order to perform the same processing sequentially in the X direction, it is determined in step S7 whether or not processing has been performed on all the pixels in the current line buffer 7. Thus, steps S4, S5, and S6 are repeated for the number of pixels in the current line buffer 7. When the process is completed, the process proceeds from step S7 to step S8, and proceeds to the process of the next line of the output image. That is, the processing of steps S4, S5, S6, and S7 is repeated by the number of magnification tables in the Y direction. When this process ends, the enlargement process in the X and Y directions for one line of the input image data ends. Then, the process proceeds from step S8 to the next step S9, in which enlargement / reduction processing is executed for the next line of the input image data.
By repeating the processing of steps S2 to S9 for the number of lines of the image data, the enlargement / reduction processing for all the pixels of the input image data is completed.

<Effect of Specific Example 1>
As described above, when an arbitrary enlargement / reduction magnification is set in an arbitrary direction, if a table displaying the enlargement / reduction magnification of each pixel is prepared for each direction, input image data can be set in the scanning direction. Enlargement / reduction processing can be performed sequentially while receiving serially. That is, there is no need to perform a process of previously storing one page of input image data in the buffer memory before the arithmetic processing, and the limited memory resources can be effectively used. In addition, since the enlargement / reduction processing can be performed only by referring to the table during the image processing, the processing can be speeded up.

  In the above example, only the case where the enlargement is performed is shown. However, if zero is displayed in the magnification portion in the X direction of the enlargement / reduction table, the pixel is deleted and zero is displayed in the magnification portion in the Y direction. Then, by making a rule that the line is deleted, it is possible to easily reduce a pixel or a line by thinning. The enlargement / reduction table may be any data that indicates information such as how many times the number of pixels is enlarged or reduced in an arbitrary direction, and the expression method and configuration may be freely set.

<Specific example 2>
In the above specific example 1, since the integer magnification allocated to each input pixel is held in the form of an enlargement / reduction table, the data amount of the table becomes relatively large depending on the magnification and the input image size. In the specific example 2, a method for reducing the data amount of the table is provided.
FIG. 6 shows a block diagram of an image enlargement / reduction apparatus using modulo arithmetic.
The device shown in the figure is characterized in that a magnification calculator 13 is provided in the portion of the enlargement / reduction device 6 of the device of the first embodiment shown in FIG. The magnification calculator 13 includes an enlargement / reduction table 8 and a modulo calculator 10. The contents of the enlargement / reduction table 8 are different from those of the first embodiment and are sufficiently reduced contents.

FIG. 7 is a diagram for explaining the redundancy of the enlargement / reduction table.
(A) shows, for example, the magnification table 1X in the X direction or the magnification table 1Y in the Y direction shown in FIG. The index (Index) indicates either a column number or a row number. The magnification table 1 </ b> X in (a) of the drawing indicates that the magnification is, for example, an integral multiple (here, four times) in the horizontal direction. However, in this table, since the magnification of all pixels is 4, magnification display data of the same content as the number of pixels is stored in the memory, which is substantially extremely redundant. (B) shows the contents of the table when the magnification is 1.5 times. In this case, the magnification of each pixel is such that 1, 2 is alternately repeated as 1, 2, 1, 2,.... Keeping all such regular data in the memory is also redundant, and prevents effective use of resources.

  Therefore, such an enlargement / reduction table is obtained by calculation. That is, the magnification for each pixel is obtained by arithmetic processing in consideration of the regular correspondence between the position of each pixel in the image data and the magnification / reduction magnification. In this way, the enlargement / reduction processing can be performed immediately using the data, or the enlargement / reduction table may be generated once by the arithmetic processing, and then the actual enlargement / reduction processing may be performed. In any case, there is an effect that it is not necessary to previously store a large amount of enlargement / reduction table data created for each enlargement magnification in the memory.

The modulo operation in FIG. 8 is a calculation for obtaining the remainder of the division. The line number is displayed at the left end of the figure. The operation value is set so that the 0th line is 0 and the 1st line is 1. Then, modulo operation processing for obtaining the remainder by dividing this by 2 is represented by%. Thus, as shown in the figure, the operation result is 0 for the 0th line, the operation result is 1 for the first line, the operation result is 0 for the 2nd line, and so on. , 1, 0, 1 are obtained. On the other hand, as shown in (b) of the figure, for example, in the case of performing 1.5-times enlargement, a table is prepared in which the index is 1 when the index is 0 and 2 when the index is 1. Thus, data indicating how many pixels are to be multiplied for each line is obtained based on the result of the modulo operation.
As described above, all enlargement / reduction processing can be performed with a small amount of table data as shown in FIG.

FIG. 9 shows an operation flowchart of the enlargement / reduction method according to the second embodiment.
This operation is similar to the case of the specific example 1 already described with reference to FIG. First, in step S1, an enlargement / reduction table is created. The configuration of the table is as described with reference to FIG. Next, in step S2, one line of data is read, and in step S3, a modulo operation as shown in FIG. 8A is executed. Then, the result is used as an index and the enlargement / reduction table is referred to. This processing is performed in the vertical direction in step S3, and is performed in the horizontal direction in step S4. In step S5, dot copy is performed as instructed in the table. In step S6, it is determined whether the copy for the horizontal magnification is completed. In step S7, it is determined whether copy for the input image line width is completed. . Then, in step S8, it is determined whether or not copying has been performed for the vertical magnification. When the processing for one line is completed, the process proceeds to step S9, where it is determined whether or not processing has been performed for all input lines. Thus, each loop is processed, and the enlargement / reduction processing is performed on all the input image data.

  As described above, in steps S3 and S4, a modulo operation is executed each time processing to refer to the enlargement / reduction table is performed, and processing is performed while generating a table of a corresponding portion (part of the table). There is no need to keep the entire table data. Alternatively, the entire enlargement / reduction table may be generated by executing a modulo operation in step S1. At least, if the enlargement / reduction table is generated immediately before such processing is required, the table storage memory can be saved sufficiently compared to the case where the entire table is stored in the memory for each enlargement magnification. .

<Effect of Specific Example 2>
In this example, each pixel is viewed in the enlargement / reduction direction without displaying, for example, how many times in the X direction and how many times in the Y direction each of the pixels of the input image data. When there is a regular correspondence between the position of each pixel in the input image data and the enlargement / reduction magnification, an enlargement / reduction table can be generated and referred to by arithmetic processing. Therefore, the size of the enlargement / reduction table to be stored in the memory in advance can be sufficiently reduced, and the storage capacity can be reduced.

<Specific example 3>
FIG. 10 is a block diagram of an enlargement / reduction device according to the third embodiment.
In this apparatus, a buffer for two lines of a previous line buffer 7A and a current line buffer 7B is provided in the portion of the enlargement / reduction apparatus 6 in the specific examples so far. Further, a primary interpolation enlargement / reduction processing unit 16 for performing a primary interpolation process to be described below is provided.

FIG. 11 is an explanatory diagram of resampling for pixel value correction which has been conventionally used for image enlargement / reduction processing. FIG. 12 is an explanatory diagram of a square lattice. Note that a square lattice refers to one in which the length of each of the vertical and horizontal sides is free, and pixels are arranged at the vertices of a so-called rectangle. Therefore, the four sides do not necessarily have to be a square, and may be a rectangle.
Output image data 4 is obtained by enlarging input image data 3 in FIG. When the enlargement process is performed, the interval between the input pixels and the interval between the output pixels do not always match. Also, the positions of the corresponding pixels in the image may not exactly match. In this case, the pixel value of each pixel of the output image data 4 is converted by performing arithmetic processing as follows in order to prevent the image quality of the output image from deteriorating.

  First, the position of each pixel of the output image data 4 in the input image data 3 is determined. In this case, as shown in FIG. 12, it is assumed that the output pixel at point X is located at a position surrounded by a square lattice of input pixels at points A, B, C, and D. At this time, an appropriate pixel value is calculated from the relationship between the pixel values of the four pixels at points A, B, C, and D and the distance between point X and points A, B, C, and D. The pixel value of the pixel at the point is used.

FIG. 13 is an explanatory diagram of a general calculation method of linear interpolation.
For example, as shown in FIG. 12, it is assumed that an output pixel exists at a point indicated by a cross. At this time, the distance from the upper side of the point x is q, and the distance from the left side is p. Both p and q are represented by decimal numbers between 0 and 1. At this time, the output value of the pixel at the point marked by x is represented by the equation shown in FIG. Here, as shown in (b), when the coordinates of the output pixel F on the output image, the coordinates of the input pixel A on the input image, and the enlarged view of the image are respectively set, p, q and each coordinate value, The relationship with the enlargement ratio is as shown in equation (c).
In order to perform such a process, it is necessary to store in advance all input image data around the pixel to be processed in the buffer memory, and then to calculate the pixel value of the output image data.

FIG. 14 is an explanatory diagram of the primary interpolation according to the third embodiment.
In this specific example, for example, the specific example 1 is performed to enlarge the input image data 3 four times in the X-axis direction and three times in the Y-axis direction. At this time, for example, in a 4 × 3 pixel block (matrix surrounded by a thick black line frame in the figure) of the output image data 4 obtained by increasing the number of pixels, for example, a pixel at the lower right is on a square lattice. It is defined as a pixel. This pixel is blacked out in the figure.

  For example, a pixel painted black at coordinates of X = 3, Y = 2 of the input image data 3 is copied to coordinates of X = 12, Y = 6 of the output image data 4. The pixel value of each pixel in the block including this pixel is linearly interpolated using the pixel values of four surrounding pixels which are painted as shown in the figure. This is because a high-quality output image is obtained by smoothly changing the pixel value of a new pixel added between adjacent pixels in the input image between pixels that were originally adjacent to each other.

  Here, if the image data of two lines of the previous line and the current line, that is, four pixel values of the hatched pixels and black pixels of the input image data 3 are held, a thick black line It becomes possible to perform arithmetic processing on the pixel values of all 12 pixels in the frame surrounded by. The calculation formula is shown in FIG. The meaning of each symbol is as shown below.

FIG. 15 is an explanatory diagram of a processing example of the primary interpolation according to the third specific example.
Here, the results of arithmetic processing when pixel values are actually given to each pixel according to the above definition are shown by numerical values. In the input image, the pixel values of the pixels at the lattice points are, for example, “0”, “100”, “50”, and “200”. If this is enlarged three times vertically and four times horizontally, each pixel value is copied to the lower right corner of the corresponding block. Then, for example, for a block including a pixel having a pixel value of “200”, the value calculated by the primary interpolation is written in the remaining 11 pixels. In the lower part of the figure, an example of pixel value calculation in the case of P = 2 and Q = 2 is illustrated. By calculating the pixel values in this way, the enlargement process can be performed without deteriorating the image quality.

FIG. 16 shows an operation flowchart of the device of the third embodiment.
In this flowchart, steps S1 to S4 are the same as the processing of the specific example 1 described with reference to FIG. That is, an enlargement / reduction table is created, line data is read, and then the enlargement / reduction table is referred to. Then, in the specific example 3, in step S5, the primary interpolation processing described above is performed. This processing is performed for all the pixels in the block, and further executed for all the blocks in the scanning direction. Other processes are the same as those in the first embodiment. Note that the pixel value of the input pixel is copied to the lower right corner of the block in order to enable arithmetic processing using only serially input image data for two lines in the buffer memory.
Note that the positions of the pixels that obtain such an effect may be any of the four corners of each block.

<Effect of Specific Example 3>
According to this specific example, the enlargement / reduction processing by the primary interpolation, which cannot be realized until the entire input image is read into the buffer memory, is executed only by holding the data of two lines in the buffer memory. It is now possible. As a result, high-quality enlargement / reduction processing can be realized with a sufficiently small amount of buffer memory.

<Specific example 4>
FIG. 17 is an explanatory view of the principle of the fourth embodiment.
Here, the coordinates of the square grid of the input image data 3 are converted into the coordinates on the output image data 4, and the output image data 4 is divided into regions formed by the corresponding square grid. This area is hereinafter referred to as a nearby area. In this figure, when a square grid is defined by four pixels (circles) surrounded by broken lines of the input image data 3, the corresponding neighboring areas are written in the output image data 4 by solid squares. The area surrounded by the square is called a neighborhood area, which includes, for example, nine output pixels (square marks) as shown in the figure. The pixel values of these pixels are obtained from the pixel values of the four pixels of the input image data 3 by the above-described linear interpolation method. In this way, the pixel value of each pixel included in the neighboring area can be obtained from only the pixel values of four adjacent pixels of the input image data. Therefore, data of about two lines may be stored in the buffer memory as in the third embodiment. In addition, the calculation process is easier than before, as described later.

FIG. 18 shows a block diagram of the device of the fourth embodiment.
Line buffers 7A and 7B are provided in the enlargement / reduction device 6 of this device in order to store data to be processed. In order to specify a pixel value to be processed in each line buffer, a previous line pointer 19A and a current pointer 19B are provided. Further, a neighborhood area table 18 for designating the neighborhood area described above is provided, and the primary interpolation enlargement / reduction processing unit 16 calculates the pixel value of each pixel in the neighborhood area.

FIG. 19 is an explanatory diagram of the neighborhood area table.
As with the enlargement / reduction table described in the first embodiment, there are one neighboring area table for performing a vertical operation and one for performing a horizontal operation. The table for the vertical direction is called a nearby area vertical table, and the table for the horizontal direction is called a nearby area horizontal table. In the example shown in (a), an input image of 3 × 3 pixels is enlarged to 5 × 5 pixels. The neighborhood area was set as shown by a broken-line grid in the output image of FIG. For example, one pixel exists in the area near the upper left corner of the output image, and 2 × 2 pixels exist in the area near the lower right corner. Thus, a vertical table and a horizontal table are provided to display the number of output pixels in each of the neighboring areas. The contents of this table can be generally obtained by an equation as shown in FIG. Note that the symbol A in FIG. 3B indicates the number of pixels in the vertical direction or the number of pixels in the horizontal direction of the input image. The symbol B indicates the number of pixels in the horizontal or vertical direction of the output image. The symbol X is a parameter indicating the number of the neighboring area from the beginning.

FIG. 20 is an explanatory diagram of a line buffer.
As described above, the image data for two lines is stored in the device during the arithmetic processing of the enlargement / reduction processing. The line buffers 7A and 7B alternately receive and store one new line of input data. The previous line pointer 19A and the current pointer 19B are used to indicate which line buffer has previously stored data. Therefore, the initial values indicate the line buffer 7A. The buffer to be pointed to by the previous line pointer 19A and the current pointer 19B can be obtained by, for example, an operation shown in FIG. This is based on the modulo operation described above. This makes it clear which line of the input image is stored in which line buffer.

  FIG. 3C shows the configuration of each line buffer. Each line buffer is one pixel larger than the width of the actual input image. The first pixel, that is, the first element of the buffer, stores the same value as the second element. This is because when the width of the input image is 1, data for four pixels for performing primary interpolation cannot be prepared as it is, so that dummy dots are stored.

FIG. 21 is an explanatory diagram of the image data storage processing.
With the above configuration, as shown in this figure, for example, the line buffer 17A stores the line just processed, and the line buffer 17B proceeds with the line currently being processed stored. When the processing of the line buffer 17B is completed, the data of the next new line is stored in the line buffer 17A. Accordingly, the current pointer 19B now points to the line buffer 17A, and the previous line pointer 19A points to the line buffer 17B.

FIG. 22 shows an enlarged view of the vicinity area.
Assuming that the above-mentioned neighboring area is constituted by, for example, pixels having pixel values A, B, C, and D, the pixel value F of the output pixel indicated by a solid square mark included in the neighboring area is as shown in FIG. It is determined by a simple arithmetic processing. This arithmetic processing itself is exactly the same as the equation described in the primary interpolation processing. Note that the grid spacing is α in the horizontal direction and β in the vertical direction. Further, the distance from the upper side of the target pixel is q, and the distance from the left side is p. However, α and β can be set to α = 1 / mx and β = 1 / my when the enlargement ratio of the image is mx and my in the X and Y directions, respectively.

FIG. 23 shows an operation flowchart of the fourth embodiment.
In the specific example 4, first, the horizontal table and the vertical table as described above are created in step S1. Then, in step S2, each line buffer is initialized. Thereafter, the line data is read in step S3, and the output pixel value calculation shown in FIG. 22 is executed in step S4. In a step S5, it is determined whether or not the processing for the horizontal size of the neighboring area is performed, and in a step S6, it is determined whether or not the processing for the input image width is completed. When the processing for one line is completed up to step S6, it is determined in step S7 whether or not the vertical size of the neighboring area has been completed. When the processing has been completed, the process proceeds to step S8 to update the buffer. Further, the process proceeds to the next line, and in step S9, it is determined whether or not the number of input image lines has been completed, and the process ends.

<Effect of Specific Example 4>
FIG. 24 is an explanatory diagram of the calculation contents of the specific example 4.
The effect will be described with reference to FIG.
As described above, all the pixel values of the nine pixels included in the neighboring area are calculated from the four pixel values as shown in FIG. Accordingly, if the input image is held for two lines and the processing is performed while changing the contents in order, the pixel values of all the output pixels can be sequentially calculated by the primary interpolation method and used. The amount of memory can be sufficiently reduced.

<Example 5>
In the above case, seven additions and ten multiplications are performed on each output pixel, that is, the output pixel included in the neighboring area. However, considering the regular relationship between these positions, the arithmetic processing can be further simplified.
FIG. 25 shows a block diagram of the device of the fifth embodiment.
This device stores pixels in the line buffers 31A and 31B and performs the same arithmetic processing as that of the fourth embodiment, while further simplifying the arithmetic processing. For that purpose, the primary interpolation enlargement / reduction processing unit 40 is configured as shown here. Here, a parameter calculation device 41, a left end pixel value storage device 42, an adder 43, a ΔY memory 44, a ΔX1 memory 45, an adder 46, a ΔΔX memory 47, a current pixel memory 48, and an adder 49 are provided. The output of the neighborhood area table 32 is input to the parameter calculation device 41. The output of the primary interpolation enlargement / reduction processing unit 40 is configured to be stored in the output image frame buffer 34.

FIG. 26 is a diagram for explaining the correlation between dots.
In this specific example 5, the calculation is simplified using the correlation between dots. That is, as shown in this drawing, it is assumed that, for example, nine pixels as described above are included in the vicinity area. In this case, the horizontal interval between these pixels can be displayed as ΔX1, and the vertical interval can be displayed as ΔY. As described above, since the interval between the pixels is regularly constant, by obtaining the pixel value of the left end, that is, the pixel value of the output pixel of D1 and ΔX1 and ΔY1 shown in FIG. Pixel values can be converted. That is, the difference between the pixel values of adjacent pixels can be obtained by ΔX1, ΔY, ΔΔX, and the like. In this specific example, the calculation process of each pixel value is simplified by utilizing the principle.

FIG. 27 is an explanatory diagram of the correlation between dots as in FIG.
This figure shows a calculation formula of each pixel value performed using the specific example 5.
As shown in the figure, if the pixel value of the leftmost pixel B1 is calculated, the pixel values of the pixels arranged in the right direction or the vertical direction can be calculated by a much simpler expression.

FIG. 28 shows an operation flowchart of the device of the specific example 5.
In step S1 in the figure, first, the pixel value of the upper left corner of the neighboring area is calculated. The calculation method has already been described with reference to FIG. Next, in step S2, calculation of ΔX1 is performed. Further, in step S3, ΔY is calculated. Next, in step S4, ΔΔX is calculated. Then, in step S5, the output pixel value is set, and in step S6, the output pixel value is updated. In step S7, it is determined whether the processing for the horizontal size of the neighboring area has been completed, and the loop of steps S6 and S7 is repeated. Next, when processing the line immediately below the neighboring area, the process proceeds to step S8, where ΔX1 is updated, and in step S9, the leftmost pixel value is updated. Thereafter, in step S10, it is determined whether or not the processing for the vertical size of the neighboring area has been completed, and if not completed, the processing of steps S5 to S9 is repeated. This completes the calculation process shown in FIG.

<Effect of Specific Example 5>
Through the above processing, seven additions and ten multiplications are performed for the leftmost pixel, but for other pixels, the pixel value can be obtained by a few additional additions. Thereby, the primary interpolation processing can be improved.

<Example 6>
FIG. 29 is a block diagram of the device of the sixth embodiment.
The following specific example is suitable for image reduction processing.
In the following specific example, the input image 51 shown in the figure is equally divided into small regions 51Z by a boundary 51H parallel to the main scanning direction and a boundary 51V parallel to the sub-scanning direction. Then, the pixel values of the pixels included in each of the small areas 51Z are averaged to obtain the pixel value of the output pixel. In this case, a large memory is required to hold the pixel values of all the pixels in the buffer of the apparatus that performs the actual processing. Therefore, a configuration as shown in FIG. 29 is adopted.
The pixel values of all the pixels of the input image 51 are stored in the external storage device 52. In order to process these, an input image buffer 53, an intermediate result buffer 54, a control device 55, and a frame buffer 57 are provided.

  The input image buffer 53 is a storage device that receives and holds pixels constituting the input image 51 one line at a time in the main scanning direction. The intermediate result buffer 54 is a memory that stores the total value of the pixel values for the number of equally divided small areas when the input image 51 is viewed in the main scanning direction. The output image 58 processed by the control device 55 is stored in the frame buffer 57. Note that the control device 55 controls the number of dots in the horizontal group xnum, the number of dots in the vertical group ynum, the input pixel horizontal counter IX, the input pixel vertical counter IY, and the output pixel horizontal counter required during these processes. OX, an output pixel vertical counter OY, and a horizontal direction total counter HT are stored.

  The number of dots in the horizontal direction xnum is a parameter that counts the number of pixels included in the equally divided small area 51Z and is stored for averaging processing. The horizontal direction is the main scanning direction and the vertical direction. In the sub-scanning direction. The input pixel horizontal counter IX is a parameter for counting the number of pixels of the input image 51 viewed in the main scanning direction and determining whether or not to end processing for one line. The input pixel vertical counter IY is a parameter for counting the number of pixels in the sub-scanning direction and determining whether processing for one page is completed. The output pixel horizontal counter OX is a parameter indicating at which position in the main scanning direction the output pixel value on the frame buffer is stored. The counter OY is a parameter indicating at which position in the sub-scanning direction the output pixel value is stored in the frame buffer. The horizontal sum counter HT is a data holding area for sequentially summing up the pixel values of the respective pixels stored in the input image buffer 53 and temporarily holding a total value on the way. This data is transferred to the intermediate result buffer 54 each time the summation for one small area is completed.

The grouping of pixels constituting the input image when the input image is equally divided into small areas will be described with reference to FIGS.
It is assumed that the pixels of the input image exist at the grid points indicated by broken lines in FIG. Here, consider a case where such an input image is reduced to an output image having a pixel array as shown by arranging square marks on the right side of the drawing. At this time, the coordinates on the input image corresponding to each output pixel A are obtained. The position is indicated by a square in the grid in the figure. The pixel value of the output pixel A is obtained by averaging the pixel values of the pixels of the input image existing around the output pixel A.

  For this purpose, as shown in FIG. 31, a line is drawn in the middle of each output pixel A to divide the input image equally. Thus, as shown in this figure, for example, assuming that the output pixels A are arranged at 2L intervals when viewed in the sub-scanning direction, that is, in the vertical direction, boundaries 51H parallel to the main scanning direction are set at 2L intervals. You. Similarly, a boundary 51L parallel to the sub-scanning direction is set. In this way, the pixels constituting the input image are grouped into small areas by the boundaries 51H and 51L.

In FIG. 32, input pixels corresponding to output pixels A are indicated by black circles. Here, the pixel value of the output pixel A at the lower right of the figure is the average of the pixel values of the input pixels of four corresponding black circles. In addition, in selecting a boundary, the group of input pixels corresponding to the output pixel B shown in the lower left of the figure is six black circles.
That is, when the input pixel exists exactly on the boundary, for example, a rule as shown in FIG. 33 is set. As shown in FIG. 33, any pixel existing directly above the boundary 51L or 51H is defined as belonging to, for example, a group of pixels included in the left or upper region.

FIG. 34 is an explanatory diagram of the area of the group.
With this drawing, a boundary pixel 71 in the vertical direction and a boundary pixel 72 in the horizontal direction are defined. The small area surrounded by the boundaries 51L and 51H includes input pixels represented by white circles and black circles as shown in the figure. At this time, one row of pixels closest to the boundary 51H parallel to the main scanning direction is defined as a horizontal boundary pixel 72. A pixel closest to the boundary 51L parallel to the sub-scanning direction is defined as a vertical boundary pixel 71. The apparatus shown in FIG. 29 recognizes these boundary pixels differently from other pixels, and when the boundary pixels are recognized, executes a predetermined tabulation process and an averaging process. As a result, the average value of the pixel values for the group of input pixels is obtained for each area using the intermediate result buffer 54 (FIG. 29) and the input image buffer 53 (FIG. 29) having a relatively small capacity.

FIG. 35 is an explanatory diagram of the averaging method using boundary pixels.
When the region setting and grouping as described above are performed, for example, as shown in this figure, input pixels are grouped by a frame 73, and a vertical boundary pixel 71 and a horizontal The boundary pixel 72 is read.

FIG. 36 is an explanatory diagram of a criterion for determining a boundary pixel.
In order to determine the boundary pixel as described above, a criterion for determining the boundary pixel as shown in FIG. As shown in the figure, the input image 51 is equally divided into units of a group region 51Z by a horizontal boundary 51H and a vertical boundary 51L. At this time, the discrimination function of the horizontal boundary pixel is set to border · x (X), and the vertical boundary pixel discrimination function is set to border · y (Y). The border x (X) is a function of dst x, src x, and X, as shown in FIG. dst · x is the width of the output image in the main scanning direction. Src · x is the width of the input image in the main scanning direction. X is the order of the pixel of interest when the input image is viewed in the main scanning direction. Assuming that the interval between input pixels is “1”, the width of all small regions is src · x / dst · x. Under these conditions, the condition that the X-th input pixel counted from the left becomes the boundary pixel is that the boundary of the area comes between the X-th input pixel and the X + 1-th input pixel. Since the boundaries of the regions are arranged at intervals of src · x / dst · x, the condition for the X-th input pixel to be the boundary pixel is as in the following equation (1).
X <((src · x * n) / dst · x) ≦ X + 1 (1)

Further, a condition for the X-th input pixel to be a boundary pixel is that an integer m that satisfies the following equation (2) exists.
X <((src · x * m) / dst · x) ≦ X + 1 (2)
In this equation (2), first, both sides are multiplied by dst · x / src · x. Since dst · x / src · x is positive, the direction of the inequality sign does not change.
(Dst · x * X) / src · x <m ≦
(Dst · x * (X + 1)) / src · x (3)
Here, since m is an integer, this relationship does not change even if Gauss symbols are added to both sides, so that the relationship of the following equation (4) holds.
[(Dst · x * X) / src · x] <m ≦ [(dst · x * (X + 1)) / src · x] (4)

Further, [(dst · x * X) / src · x] and [(dst · x * (X + 1)) / src · x] are integers, so [(dst · x * X) / src · x] <[ [(Dst · x * (X + 1)) / src · x], then ((dst · x * X) / src · x] <m ≦ [(dst · x * (X + 1)) / src · x] m exists. At least m = [(dst · x * (X + 1)) / src · x] satisfies the condition.
That is, [(dst · x * X) / src · x] <[(dst · x * (X + 1)) / src · x] is a condition for X to be a boundary pixel.
From the above, the definition of border · x (X) is as follows.
border · x (X) = 1: [(dst · x * X) / src · x] <[(dst · x * (X + 1)) / src · x] (5)
border · x (X) = 0: [(dst · x * X) / src · x] ≧ [(dst · x * (X + 1)) / src · x] (6)

Similarly, the discriminant function can be used similarly when viewed in the sub-scanning direction, that is, in the vertical direction.
border · y (Y) = 1: [(dst · y * Y) / src · y] <[(dst · y * (Y + 1)) / src · y] (7)
border · y (Y) = 0: [(dst · y * Y) / src · y] ≧ [(dst · y * (Y + 1)) / src · y] (8)

FIG. 37 is an explanatory diagram of the data flow (horizontal direction) of the averaging method.
The configuration of the intermediate result buffer 54 and the pixel value summing process executed in this specific example will be described with reference to this drawing.
For example, as shown in the figure, it is assumed that the pixels 74 forming the input image are stored in the input image buffer 53 shown in FIG. 29 continuously in the main scanning direction. This is sequentially processed from the left end shown in the figure. The pixel value of the first pixel is stored in the horizontal sum counter HT shown in FIG. The pixel value of the next pixel is added to the sum counter HT. Then, the pixel value of each pixel is successively accumulated and stored in the horizontal sum counter HT. When the boundary pixel of the group is detected, the pixel value is transcribed to the register 54A and the addition is completed. . The detection of the boundary pixel is determined from the value of border · x.

  Therefore, as shown in this figure, when the value of border · x becomes “1”, the register used in the intermediate result buffer 54 is switched from 54A to 54B. Then, the pixel values of the next group of pixels are sequentially added. Therefore, when the processing for one line is completed, the sum of the pixel values of the pixels included in the same small area is stored in registers corresponding to the number of small areas viewed in the main scanning direction provided in the intermediate result buffer 54. Is done.

FIG. 38 is an explanatory diagram of the data flow (vertical direction) of the averaging method.
The process of viewing in the main scanning direction proceeds as shown in FIG. When the processing for one line is completed, the processing for the next one line is advanced. The processing in the sub-scanning direction is performed as shown in FIG.
When processing in the sub-scanning direction is performed, the value of border · y is always referred to before starting the processing. When the value of border · y is “0”, the aggregation processing for one line shown in FIG. 37 is executed. The contents of each register of the intermediate result buffer 54 are added and accumulated line by line. Here, consider processing a line in which the value of border · y is “1”. Since this line is a group of pixel values arranged at the end of the area, when the pixel values are totaled for each area, the values held by the registers constituting the intermediate result buffer are all the values on this line. This is the sum of the pixel values of the small areas. Separately from this, the number of dots xnum in the horizontal direction and the number of dots ynum in the vertical direction of the parameter holding unit 60 shown in FIG. 29 are counted, so that the number of pixels constituting each area can be calculated. Therefore, an average value can be obtained by dividing the sum of the pixel values of each area by the number of pixels included in each area. This is stored in the frame buffer 57 and becomes the pixel value of the output pixel.

FIG. 39 shows a flowchart for sequentially explaining the operation of the above-described specific example 6.
Steps S1 to S4 are initialization processing. In step S1, an input pixel vertical counter IY and an output pixel vertical counter OY are set to "0". This enables reading from the first line. In step S2, the horizontal total counter HT is set to "0". This is for storing an intermediate counting result of pixel values. First, the leftmost pixel is specified. In step S3, the number of dots ynum in the vertical direction is set to "1", and the number of dots xnum in the horizontal direction is set to "1". Thus, counting of the number of pixels in the area is started in the main scanning direction and the sub-scanning direction. In step S4, the intermediate result buffer 54 is cleared. This clears the registers corresponding to all small area pixel value aggregation results.

  In the next step S5, the input pixel horizontal counter IX is set to "0", and the output pixel horizontal counter OX is set to "0". Thus, the following processing is repeated from the leftmost pixel. In step S6, the input image is read for one line (one line). In step S7, the IX-th element (pixel value) of the image buffer is added to HT. Thus, the HT temporarily holds the total pixel value of the pixel currently being processed. Next, in step S8, the value of border · x is checked. If this value is "0", the flow proceeds to step S11, the input pixel horizontal counter IX is incremented, and the flow proceeds to step S12. In step S12, it is determined whether or not IX does not exceed the width of the input image, and if not, the process returns to step S7.

  In this way, the pixel values are sequentially accumulated and held in the HT, and when the value of border · x becomes “1”, the process proceeds to step S9, and the value of the HT is added to the OX-th element (the register shown in FIG. 36) of the intermediate result buffer 54. Thus, the sum of the pixel values of the area including the pixel to be processed is stored in the corresponding register of the intermediate result buffer 54. Next, the output pixel horizontal counter OX is incremented, and the horizontal total counter HT for totaling in the area is reset to “0”. Then, the process returns to step S11, increments IX, and proceeds to step S12. In this way, the pixel values of one line are totaled for each area by the processing of steps S7 to S12 and stored in the intermediate result buffer 54.

When these processes are completed, the process advances to a step S13 to check the value of border · y. If the value of border · y is “0”, the process proceeds to step S15, IY is incremented, and the process proceeds to the next line. At the same time, the number of dots ynum in the vertical direction is incremented, and the process proceeds to step S16. In step S16, it is determined whether or not the input pixel vertical counter IY is equal to or less than the height of the input image. If the height is equal to or less than the height, the process returns to step S5. Thus, it is determined whether the processing for one screen is completed.
On the other hand, if the value of border · y becomes “1” in step S13, the process proceeds to the division process in step S14.

FIG. 40 shows a flowchart of the division processing.
In the division process, first, in step S1, an initial value "1" is substituted for the number xnum of dots in the horizontal direction. Further, an initial value “0” is substituted for the input pixel horizontal counter IX. Further, in step S2, an initial value “0” is substituted into the output pixel horizontal counter OX.
With these, preparations are made to start processing from the first pixel for one line.

  In the next step S3, the value of border.x is determined. When two or more pixels are included in one area when viewed in the main scanning direction, the value of border · x is usually “0” at first. Therefore, the process proceeds to step S8, where "1" is added to the input pixel horizontal counter IX. Further, the number of horizontal dots xnum for counting the number of horizontal pixels in the area is incremented. Then, the process proceeds to step S9, and if IX does not become larger than the input image width, the process returns to step S3 again. Thus, the processing of steps S3, S8 and S9 is repeated until the value of border · x becomes “1”. This process is a process for simply counting the number of pixels included in the region arranged in the main scanning direction, that is, the difference, and the number xnum of dots in the horizontal direction.

  The summation of the pixel values of this line has already been completed by the processing of steps S7 to S12 in FIG. Here, when the value of border · x becomes “1”, the process proceeds to step S4, and the value of the corresponding register of the intermediate result buffer is stored in the temporary file TMP. Further, in step S5, the average value is calculated, and the pixel value of the corresponding pixel on the frame buffer is determined. The answer obtained by dividing the value of the intermediate result buffer by the number of dots in the horizontal direction × the number of dots in the vertical direction is the average value. In step S6, the number of dots xnum in the horizontal direction is cleared to zero. This is a preparation for counting the number of dots in the next area. In step S7, "1" is added to OX. This is a process of incrementing the horizontal counter of the output pixel and designating the next output pixel.

  In step S8, the input pixel is moved right by one, "1" is added to xnum to initialize it, and it is determined again in step S9 whether the processing for all one line is completed. If the next area exists, the process returns to step S3, and the processing described so far is repeated. In this way, the average value is obtained by dividing the sum of the pixel values contained in each area stored in each register of the intermediate result buffer by the number of pixels constituting each area for the line where border · y is “1”. Is completed. When all of these processes are completed, ynum is cleared to zero in step S10 to prepare for the next process. Also, in step S11, the intermediate result buffer is cleared, and a new counting is started again from the next line.

<Effect of Specific Example 6>
According to the above example, the pixels constituting the input image are held for one line at a time, and while the boundary pixels of the small area when viewed in the main scanning direction are detected, the total value of the pixel values is obtained and the intermediate result buffer is obtained. And the boundary pixel when viewed in the sub-scanning direction is detected, and the average value of the pixel values in each area is obtained by dividing the total value of the pixel values of each small area by the number of pixels included in the area. . With this configuration, the memory for holding the pixel values constituting the input image is only the input image buffer for one line and the intermediate result buffer having a relatively small capacity, and the used memory amount can be reduced.

<Specific Example 7>
FIG. 41 shows a block diagram of the device of the seventh embodiment.
This device is different from the device of Example 6 in that a register for holding the sampling interval A is provided in the parameter holding unit 60. Then, instead of adding and averaging all the pixel values of each small area, the pixel values of partially sampled pixels are averaged.

FIG. 42 is an explanatory diagram of input pixels to be sampled.
As shown in the figure, the input image 1 is equally divided into small regions by a boundary 51V parallel to the sub-scanning direction and a boundary 51H parallel to the main scanning direction. Although this small area includes many pixels, as shown in the figure, a black circle pixel 74A and a white circle pixel 74B are set, and only the black circle pixel 74A is sampled. The pixel intervals at both ends of the pixels included in the area are set in the main scanning direction Dx and the sub-scanning direction Dy as shown in the figure. Then, the sampling interval was set to A. Here, in practice, every other pixel is sampled at intervals of A in both the main scanning direction and the sub-scanning direction.

FIG. 43 shows an image explanatory diagram after sampling.
The one shown on the left side of the figure is the original input image, and the one shown on the right side is a collection of sampled input pixels. As shown in this figure, when the sampling interval is set to be the same in the vertical and horizontal directions, a group of sampled input pixels becomes an image similar in shape to the original input image.

FIG. 44 shows an operation flowchart of the seventh embodiment.
This processing is almost the same as the operation flowchart of the specific example 6 shown in FIG. In the specific example of FIG. 44, steps S5, S8, and S9 are newly added. The other parts are the same as those in FIG. 39, and thus the description thereof will not be repeated. First, in step S5 in FIG. 44, the value of A is obtained. That is, the sampling interval is read here. When sampling is performed for every other pixel, the value of A is "2" as described above. Further, immediately after the input pixel is read in step S7, it is determined in step S8 whether or not the pixel is a sampling row by comparing 0 with the remainder obtained by dividing IY by A.

  Thus, it is determined whether the currently read line is a line to be summed or a line to be skipped in view of the sampling interval. If it is a line to be skipped, the process proceeds from step S8 to step S16. Note that a line that is not a sampling target may be a boundary of an area. Accordingly, the process proceeds from step S8 to step S16 to check the value of border · y. Step S16 and subsequent steps are the same as in the first embodiment, and are not shown.

  In step S8, it was determined whether the read line should be skipped. In step S9, when the processing of the line was started, whether or not the pixel of interest should be skipped was obtained by dividing IX by A. It is determined by comparing 0 and 0. If the pixel should be skipped, the process proceeds from step S9 to step S11 to determine whether the pixel is a boundary pixel. If it is determined that the pixel should be sampled, the process proceeds from step S9 to step S10, and the pixel value is added to HT and totalized.

When the remainder of IY and A or IX and A is obtained, the following processing is specifically performed.
Here, some parameters are set in advance.
(1) As in the first embodiment, an average is obtained for each group of input pixels corresponding to output pixels. However, unlike the specific example 1, the sum of all the input pixels in the group is not calculated.
(2) At regular intervals A, the input pixels to be summed are sampled. When A = 1, all input pixels are sampled. The sampling interval A is constant vertically and horizontally. This is because the image after sampling should be similar to the original image.

Next, how to obtain A will be described. To show how to find it, we set some parameters.
(1) Let N be the maximum number of input pixels that can be summed. N is determined by the accuracy of the total calculation and the number of gradations of the input pixel. For example, when the pixel value is 256 gradations (in this case, the maximum number of pixel values is 255) and the total is calculated by 16 bits, the maximum number that can be expressed by 16 bits is 65535. Considering this, it is necessary to satisfy N * 255 ≦ 65535. That is, N = 257.
(2) The number of pixels in the horizontal direction in the group is Dx, and the number of pixels in the vertical direction is Dy. When sampling at intervals of A, the number of pixels to be sampled is Dx / A in the horizontal direction and Dy / A in the vertical direction in the group. Since the sampling number must not exceed N, the interval A needs to satisfy the following expression.
(Dx / A) * (Dy / A) ≦ N (9)
Here, A is an integer.

Further, if A is made larger than necessary, the amount of sampling is reduced. Therefore, A needs to be the minimum number that satisfies the expression (9). That is, A-1 does not satisfy the expression (9), but A is a value that satisfies the expression (9). Such A can be obtained by rounding up the decimal part of A 'where (Dx / A') * (Dy / A ') = N.
The value of A ′ is as follows by solving (Dx / A ′) * (Dy / A ′) = N.
A ′ = sqrt ((Dx * Dy) / N) (10)

A is obtained by rounding up the decimal part of A ', and is as follows.
A = [A '] + 1 (when A' is not an integer) (11)
A = A '(when A' is an integer) (12)
Here, [A '] means the largest integer not exceeding A' in a Gaussian symbol, and sqrt means square root.

Note that the values of Dx and Dy differ depending on the group. That is, A obtained by Dx and Dy of a certain group may cause overflow in another group.
However, by using the maximum values of Dx and Dy when calculating A, it is possible to obtain a value of A that can be used without any problem in all groups.
The maximum values of Dx and Dy can be obtained from the input image sizes src · x and src · y by the following equations.
Dx: Rounded up src · x / dst · x Dy: Rounded up src · y / dst · y

<Effect of Specific Example 7>
As described above, if sampling is performed at a constant interval A, when the number of pixels included in the small area is large, the total can be performed by narrowing down to an arbitrary number of the pixels. As a result, when the total is obtained and stored in the intermediate result buffer, the total value does not increase more than necessary, and the memory capacity of the buffer can be sufficiently reduced.

<Specific Example 8>
FIG. 45 shows a block diagram of the device of the eighth embodiment.
In this specific example, an area for storing the sampling total counter ST together with the sampling interval A is added to the device of the specific example 7. Other parts have the same configuration as that of the seventh embodiment.

FIG. 46 is a process explanatory diagram of the specific example 8.
In the above processing, the pixel values are summed and the average can be obtained without overflowing the register of the intermediate result buffer by performing sampling. In this case, input pixels that are not sampled have been ignored. In this specific example, an average is also taken for pixels that are not sampled, thereby improving the image quality. In order to define the range for taking the average, the concept of a sampling area is introduced. The sampling area includes, for a line to be sampled, several input pixels including an input pixel to be sampled and an input pixel to be sampled immediately adjacent to the line. This is an area on the input image having a width of A and a height of one line. The pixels indicated by black circles in FIG. 46 are pixels on the line to be sampled. Then, two adjacent pixels are set in the sampling area 80 here. In this way, by averaging the pixels with respect to the original input image as shown on the left side of the figure, a group of input pixels similar in shape to the original input image as shown on the right side of the figure can be formed.

FIG. 47 shows an explanatory diagram of the sampling area.
For example, as shown in this drawing, when a large number of pixels exist in one small area set by the boundaries 51H and 51V, sampling is performed for each A line. At this time, the pixel 74A of the black circle on the first line and the pixel 47B on the right side thereof are included in the same sampling area 80. The pixel values of the pixels included in the same sampling area 80 are added and averaged each time by a sampling total counter ST shown in FIG. 45, and then accumulated in a horizontal total counter HT shown in FIG. In this way, by averaging the pixel values included in the sampling area each time, and accumulating the pixel values in the intermediate result buffer 54, the total value overflows even if the sampling number is substantially large. There is no fear.

FIG. 48 shows an operation flowchart of the specific example 8.
This flowchart is different from the flowchart of the specific example 6 described with reference to FIG. 39 only in steps S5 to S8. First, the initialization processing is performed in steps S1 to S4. When the processing shifts to processing of each pixel for one line in step S5, the IX-th input pixel buffer of the input pixel buffer is stored in the sampling total counter ST shown in FIG. Element. In the next step S6, a comparison is made between the IX + 1-th pixel, that is, the pixel adjacent thereto and the sampling number. If it is smaller than the sampling number, it is inside the sampling area. Therefore, in step S6, the process of adding all the pixel values of the pixels included in the same sampling area to the sampling total counter ST is repeated. When all the adding processes are completed, the process proceeds from step S6 to step S7, where the average of the pixel values in the sampling area is obtained by dividing the sampling total counter ST by the number of samples. Next, this is added to the total counter HT in the horizontal direction. In this way, after adding the average of the pixel values in the sampling area to HT, the sampling total counter ST is initialized in step S8, and the process proceeds to the next processing.
By including the processing of steps S5 to S8 in the specific examples so far, it becomes possible to calculate the average value in the sampling area.

FIG. 49 shows a flowchart of the initialization process of the specific example 8.
In step S1 of FIG. 48, an initialization process unique to the specific example 8 is performed. As shown in this figure, the contents of steps S31 to S34 are exactly the same as those of the previous initialization processing of steps 1 to S4 in FIG. In step S35, the value of the sampling interval A is determined in the same manner as in the process of the specific example 7 in FIG. Then, in step S36, the sampling total counter ST is initialized. Thus, the preparation for the total processing is completed.

<Effect of Specific Example 8>
According to this specific example 8, when the number of pixels included in the small area is large and when these pixel values are summed up and each register of the intermediate result buffer overflows in terms of the number of digits, the original image Averaging processing can be performed without deteriorating the image quality of the image. That is, the sampling area is averaged in advance, and then an accumulation method is used in which the average value is added to the intermediate result buffer, so that the intermediate result buffer does not overflow.
In the above example, an example in which the sampling area is set only in the main scanning direction has been described. However, it is possible to prevent the overflow by setting the same sampling area in the sub-scanning direction.

<Example 9>
In the examples described so far, for example, when an image is enlarged, it is necessary to calculate an integer magnification of how many times a pixel is copied for each row and each column. Based on the calculation result, an enlargement / reduction table is first prepared, and then enlargement / reduction processing is performed with reference to this table. In this case, since the enlargement / reduction magnification for each pixel can be obtained only by referring to the table, the speed of the image enlargement / reduction processing can be increased. However, depending on the image size before and after the enlargement, the data amount of the enlargement / reduction table becomes large, and the memory efficiency may be reduced. In this specific example, the calculation of the enlargement / reduction magnification can be performed easily at high speed, and conversely, the enlargement / reduction table is not required, and the memory area is saved.
In this specific example, description will be made below using terms such as a row and a line, which indicate the main scanning direction. It goes without saying that the same processing can be performed in the column direction, that is, in the sub-scanning direction.

FIG. 50 is an explanatory diagram of an appropriate algorithm to be implemented in this specific example.
(1) shown on the leftmost side of the figure is the original image, and a portion filled with white or black is a pixel group for one line. (2) shown in the middle of the figure shows a state in which the image of (1) is exactly 1.75 times in the vertical direction. If each line can be directly enlarged in the vertical direction at a magnification of a real number, that is, 1.75 times, the result shown in (2) is obtained.

  That is, the first line is expanded to 0.00-1.75, the second line is expanded to 1.75-3.50, etc., and the last eighth line is expanded to width 12.25-14.00. Is done. Therefore, in the enlarged image, eight lines of the original image are enlarged to a width of 14 lines. However, in the image data, each line can be enlarged / reduced only in integer units. That is, the boundaries between lines must be integers. Therefore, a boundary between lines is defined as an integer that does not exceed a value obtained by a real magnification. As a result, each line of the original image is integer-multiplied so that the first line is unchanged, the second line is doubled, the third line is doubled, the fourth line is doubled, and the fifth line is doubled. The original image is expanded from 7 lines to 14 lines.

The integer magnification of each line as described above is obtained by the following calculation.
MUL (n) = [n * mul]-[(n-1) * mul]
Here, mul = (size of output image) / (size of input image).
The meaning of each symbol used in the formula is as follows.
[]: Gaussian symbol (an integer not exceeding the internal real number)
n: line number (assume n = 1)

  The procedure of the enlargement process is exactly the same in the row direction and the column direction. Therefore, if the integer magnification assigned to each pixel is calculated in this way, enlargement processing can be performed. However, in this calculation, an integer operation is performed twice, a real number operation is performed twice, and a type conversion from a real number to an integer is performed twice, as shown in the above-mentioned integer magnification calculation formula. Such an operation is very time-consuming, and if this calculation is performed each time one pixel is processed, it takes too much time and is not realistic depending on the capacity of the CPU.

  The integer magnification distributed to each line will be analyzed by the above algorithm. The magnification of each line is at least an integral part of the real magnification. That is, at 1.75 times, the magnification of each line is at least 1 time, and at 2.5 times, 2 times. Also, the magnification is increased by 1 only when the decimal part carries. That is, assuming that the designated real number magnification is mul, all lines are at least BASE = [mul] times, and are BASE + 1 times only when the decimal part is raised.

  Therefore, a method of determining whether the decimal part has been raised is considered. When the decimal part of the designated real number magnification is DEC and the row number is n, when the decimal part of n * DEC is smaller than DEC, it can be determined that carryover has occurred.

FIG. 51 is an explanatory diagram of a method for determining the occurrence of carryover.
For example, consider the case where DEC = 0.3. The first line has a decimal part of 0.3. The second line has a decimal part of 0.6. The third has a decimal part of 0.9. In the fourth case, the decimal part becomes 0.2, and the number is advanced by one, so that one line is added. Here, the decimal part of the first, second, and third lines is always larger than DEC. The fractional part when the carry-over occurs is 0.2. At this time, the decimal part becomes smaller than DEC for the first time. The algorithm is summarized as follows.

The following values are calculated as preprocessing.
BASE = [mul]
DEC = mul-BASE
The magnification for each line is obtained as follows.
If the decimal part of DEC * n ≧ DEC, the magnification is BASE
If the decimal part of DEC * n <DEC, the magnification is BASE + 1
The algorithm described above requires one real number multiplication, one real number comparison (real number subtraction), and one process of extracting only a decimal part from a real number (real number subtraction). The number has decreased.

Here, the arithmetic processing of this algorithm is accelerated by utilizing the limit of the register width. For example, assume that the CPU width is 32 bits.
The following values are calculated as preprocessing.
BASE = [mul]
DEC = (mul-BASE) * 232 + 1
DEC is held in a 32-bit width integer register.
The BASE is an integer part, and the DEC is a decimal part. The reason why the value is set to +1 is to round up when a lower decimal part exists.

Multiply the DEC by the processing target line position n. This calculation result is DEC2.
DEC2 = DEC * n
DEC2 as a calculation result is held in a 32-bit integer register.
The integer magnification is determined by comparing the magnitudes of DEC and DEC2.
If DEC2≥DEC, the magnification is BASE
When DEC2 <DEC, the magnification is BASE + 1

  In the above processing, a 32-bit integer register is used, and the decimal part is represented by an integer from 0 to 232-1. In the calculation of DEC * n, the integer part overflows intentionally. As a result, an algorithm is used in which the integer part is invalidated and only the decimal part remains as the calculation result. This is a high-speed algorithm in which only one integer multiplication and one integer comparison (integer subtraction) are performed. However, in this algorithm, the decimal part is rounded to an integer from 0 to 232-1. Therefore, it may not exactly match the case where the calculation is performed with floating point precision. This processing can be extended to 64 bits, 128 bits, or the like depending on the register width of the CPU to be incremented, and the accuracy increases as the register width increases.

FIG. 52 shows a block diagram of the device of the ninth embodiment.
This device includes an external storage device 91 and a nearest-neighbor enlargement / reduction device 92. The nearest-neighbor enlargement / reduction device 92 includes a magnification calculator 93, a nearest-neighbor enlargement / reduction processing unit 94, and a line buffer 95. Further, the output of this device is configured to be taken out to the output image frame buffer 96.

  The external storage device 91 is a device that holds input image data before enlargement / reduction processing. The output image frame buffer 96 is a storage device that holds the output image after the enlargement / reduction by the nearest neighbor method.

  The nearest neighbor method enlargement / reduction processing unit 94 enlarges / reduces the line data in the line buffer 95 by the integer magnification calculated by the magnification calculation unit 93, and outputs image data to the output image frame buffer 96. It is a device to do. The magnification calculator 93 is a part that receives the coordinate value of the input pixel from the nearest neighbor enlarging / reducing processor 94 and calculates an integer magnification corresponding to the pixel. The line buffer 95 is a storage unit that stores input image data read one line at a time from the external storage device 91.

FIG. 53 is a block diagram of the magnification calculator 93 shown in FIG.
The magnification calculator 93 includes multiplication units 103 and 104, comparison / selection units 105 and 106, and a magnification calculator 107. The magnification calculator 107 is provided with registers DECX1, DECX2, BASEX1, BASEX2, DECY1, DECY2, BASEY1, and BASEY2. The multiplication unit 103 is a calculation unit that receives the X coordinate 101 and performs a predetermined integer multiplication. The multiplication unit 104 is a calculation unit that receives the Y coordinate 102 and performs a predetermined integer multiplication.

  The comparison / selection unit 105 is a unit that receives the outputs of the registers DECX1, DECX2, BASEX1, and BASEX2, selects one of them, and outputs the X-direction magnification 108. The comparison / selection unit 106 is a unit that receives the outputs of the registers DECY1, DECY2, BASEY1, and BASEY2, selects one of them, and outputs the Y-direction magnification 109. The X coordinate 101 and the Y coordinate 102 are the coordinate values of the processing target pixel specified by the nearest neighbor enlarging / reducing processing unit 94 shown in FIG.

  The X-direction magnification 108 and the Y-direction magnification 109 are calculation results output from the magnification calculation unit 93 and output to the nearest neighbor enlargement / reduction processing unit 94. As a result, an integer magnification corresponding to the designated coordinate value is output in each of the X direction and the Y direction.

FIG. 54 shows an operation flowchart of the ninth embodiment.
First, in step S1, a register in the magnification calculator 93 is set in accordance with the first specified real number magnification. The register setting will be described later in detail. Next, in step S2, one line of the input image is read from the external storage device 91 to the line buffer 95. In step S3, the magnification calculator 93 calculates an integer magnification corresponding to the Y coordinate of the read line data. In step S4, the magnification calculator 93 calculates an integer magnification corresponding to the X coordinate of the processing target image data in the line buffer.

Next, the process proceeds to step S5, where the pixel is copied and output to the output image frame buffer 96. Step S6 is a process for repeating this for the X-direction magnification. Step S7 is a part for performing control to repeat this processing for the input image line width. In step S8, control is performed to repeat the processing in steps S4 to S7 by the Y-direction magnification of the line data. In step S9, the above processing is repeated for the number of input image lines.
By the above processing, a copy of each pixel is sequentially output to the output image frame buffer from top to bottom of the input image data and from left to right.

FIG. 55 is an explanatory diagram of the enlargement / reduction processing.
Pixels indicated by black circles in the figure are pixels of the output image. Each area partitioned by the grid in the figure corresponds to one input pixel. Since the magnification is not an integer in both the X-axis direction and the Y-axis direction, the area of one input pixel corresponds to an output pixel having a different number of pixels.

FIG. 56 shows a flowchart of register setting.
The following register setting operation and magnification calculation method will be described only in the X direction. Since the Y direction is the same, the description is omitted.
First, the width of the registers DECX1, DECX2, BASEX1, and BASEX2 shown in FIG. 53 is set to N bits. Also, the designated real number magnification is represented by mul. As a specific example, a description will be given of a case where the register width is 32 bits (N = 32) and the magnification is 2.5 times (mul = 2.5).

  In step S11 of FIG. 56, first, the designated real number magnification is separated into an integer part and a decimal part. When mul = 2.5 in the specific example, BASE = 2 and DEC = 0.5. Then, the value of the register BASE indicating the integer part is set to BASEX1 (step S12). Further, in the case of carry-up, since a magnification larger by "1" is set, a value obtained by adding "1" to an integer value is set in the register BASEX2 in step S13. In a specific example, BASEX1 = 2 and BASEX2 = 3.

Next, the register DEC storing the decimal part is multiplied by 2N, and an integer value obtained by adding 1 is set in DECX1. That is, in the specific example, for example, the following calculation is performed.
DECX1 = DEC * 2N + 1
= 0.5 * 232 + 1
= 2,147,483,649

Next, a magnification calculation is performed.
FIG. 57 shows a flowchart of calculating the magnification in the X direction.
Here, a case where N = 32, mul = 2.5, and the X coordinate is 2 (X = 2) will be described as a specific example. The multiplication unit 103 shown in FIG. 53 multiplies the X coordinate specified by the nearest neighbor enlargement / reduction processing unit 94 shown in FIG. 52 by the contents of the register DECX1, and sets the result in the register DECX2 (step S21). In the next step S22, step S24 or step S25 is executed according to the result of the judgment processing (step S23).

That is, when the decimal part DECX2 obtained as a result of obtaining the product of the X coordinates is larger than or equal to the decimal part DECX1 of the real number magnification, no increment is performed. If it is less than the first decimal part, it is rounded up. If not, the contents of the register BASEX1 are output. When carrying forward, the contents of the register BASEX2 are output. Thus, the magnification in the X direction is obtained by selecting one of the contents of the registers BASEX1 and BASEX2.
According to the above, the calculation of the integral magnification according to the coordinate value is realized only by the integer multiplication and the comparison / selection.

<Effect of Specific Example 9>
According to this specific example, when enlarging / reducing the real magnification of image data by the nearest neighbor method, the calculation of the integer magnification allocated to each row / each column can be accelerated by utilizing the limit of the register width. This eliminates the need to prepare all enlargement / reduction tables in advance. Therefore, a memory for holding the enlargement / reduction table becomes unnecessary, and the memory use efficiency of the computer is improved. In addition, it is possible to perform high-speed enlargement / reduction processing of image data by the nearest neighbor method with a small memory capacity.

<Specific Example 10>
As a method of determining the pixel value of a copied pixel when an image is enlarged, there are a nearest neighbor method and a primary interpolation method. In the primary interpolation method described in Example 4 and the like, a likely pixel value is obtained using the pixel values of the four surrounding pixels and the distance to each pixel. As a result, jaggies when the enlargement processing is performed are made inconspicuous, and the image quality is improved. In this method, for example, a nearby area table shown in FIG. Here, the algorithm used in the specific example 9 can be adopted.

With reference to FIG. 58, the neighboring areas already described in some specific examples will be described again.
An input image is shown on the left side of FIG. 58 and an output image is shown on the right side.
As shown in the figure, when the grid formed by the input pixels is mapped to the output image, the area surrounded by the grid formed by the input pixels becomes the neighboring area. The primary interpolation process is performed in units of an area called a nearby area. The number of output pixels included in this neighboring area is obtained by the following equation.
When A = 1 MUL (n) = B
When A ≠ 1, MUL (0) = 1
MUL (n) = [n * mul]-[(n-1) * mul]
(N> 0)
Here, mul = (B-1) / (A-1).
The same effect was described in FIG. 19 of the fourth embodiment.

The meanings of symbols and operators in the formulas are as follows.
A: The size of the input image B: The size of the output image n: = Nearest area number (assume n = 0)
MUL (X): Number of pixels in the X-th neighboring area []: Gaussian symbol (the largest integer not exceeding the internal real number)
The same effect was described in FIG. 19 of the fourth embodiment.

  The above equation is basically the same as the equation of the nearest neighbor method. However, the top and left ends are always "1" in the primary interpolation. This is also as shown in FIG. The number of output pixels included in the neighborhood area in the primary interpolation and the integer magnification for each input pixel in the nearest neighbor method are basically the same.

FIG. 59 is a flowchart illustrating the difference in the processing order between the nearest neighbor method and the primary interpolation.
In FIG. 59A, in the nearest neighbor method, first, in step S31, the magnification in the X direction is calculated. Then, in step S32, the pixel for one pixel is copied, and in step S33, it is determined whether the copying of the pixel for the magnification in the X direction is completed. Thus, the pixels corresponding to the magnification in the X direction are copied. Further, when the duplication is completed, it is determined in step S34 whether or not the duplication of pixels for the input image line width has been completed. Thus, pixel duplication in the line width direction is performed. Thus, the pixel duplication in the X direction and the Y direction is completed.

In the primary interpolation method shown in FIG. 3B, first, in step S41, an initial value “1” is set to MULX indicating the current integer magnification. Next, in step S42, primary interpolation is performed, and in step S43, it is determined whether the processing for MULX has been completed. Then, step S42 is repeated for this number of times, and the process proceeds to step S44. In step S44, MULX is updated, and in step S45, it is determined whether the processing for the input image line width has been completed. Thus, the processing of steps S42 to S44 is repeated, and the primary interpolation processing for pixels corresponding to the width in the X direction is completed.
The same calculation is performed for the magnification calculation and the MULX calculation.

  Therefore, in the following description, the number of output pixels included in the neighboring area and the integral magnification are not distinguished, and the case of the primary interpolation is also described as the integral magnification. The primary interpolation process is performed from the vicinity area at the upper end to the bottom and from the vicinity area at the left end to the right. Therefore, in the loop for scanning all the neighboring areas, the enlargement magnification is "1" at the beginning of the loop, and thereafter, the integer magnification is obtained by the same calculation method as in the nearest neighbor method. The following two methods are conceivable for setting the integer magnification to “1” only in the first neighboring area.

(1) The loop is divided into the case of the upper end or the left end and the case of not.
(2) Conditional judgment is put into the formula for calculating the integer magnification, and when the pixel position is at the upper end or the left end, the integer magnification is set to "1".
However, the method (1) has a drawback that processing becomes complicated and a program size becomes large. In the method of (2), the condition determination is increased by one, so that the execution speed of the program is reduced. In this specific example 10, a method in which the program size does not become too large and the execution speed does not decrease is introduced. This can be achieved with the following concept.

(1) In addition to the variables used in the case of the nearest neighbor method of the specific example 9, a variable MULX indicating the current integer magnification is prepared.
(2) MULX is initialized to "1" at the beginning of a loop for scanning a nearby area.
(3) The calculation timing of the enlargement ratio is changed not to be at the head of the loop but at the rear.

By doing so, "1" is entered in MULX at the beginning of the loop, and BASEX1 or BASEX2 is entered thereafter.
Although this has been described only in the horizontal direction, the same applies to the vertical direction.

FIG. 60 shows a block diagram of the device of the tenth embodiment.
This device includes an external storage device 111, a primary interpolation enlargement / reduction device 112, and an output image frame buffer 119. The primary interpolation enlargement / reduction device 112 includes a magnification calculation unit 113, a primary interpolation enlargement / reduction processing unit 114, a previous line pointer 115, a current pointer 116, a line buffer 117, and a line buffer 118.

  This apparatus is different from the apparatus of the ninth embodiment in that a previous line pointer 115, a current pointer 116, a line buffer 117, and a line buffer 118 are provided. In order to form a neighboring area, two lines of pixels are required. Thus, a line buffer for two lines is prepared. Since the line buffers 117 and 118 for these two lines are alternately turned upside down, the pointer indicating the upper line is distinguished as the previous line pointer 115 and the pointer indicating the lower line is distinguished as the current pointer 116.

FIG. 61 shows a block diagram of the magnification calculator.
The magnification calculator 113 is a circuit that receives an X coordinate 121 and a Y coordinate 122 and outputs an X-direction magnification 124 and a Y-direction magnification 125, as in the case of the specific example 9. The magnification calculator 113 includes multiplication units 126 and 127, comparison / selection units 128 and 129, and a magnification calculation unit 123. The difference from the specific example 9 is that the MULX 131 is provided on the output side of the comparison / selection unit 128 and the MULY 132 is provided on the output side of the comparison / selection unit 129.

  These registers MULX and MULY are registers for storing the magnification. By setting "1" in the initial value of this register, the enlargement ratio of the first neighboring area can be set to "1".

FIG. 62 shows an operation flowchart of the specific example 10.
First, in step S1, register setting of the magnification calculator is executed. The values stored in these registers will be described in detail later, but it is important that “1” is put in each of the registers MULX and MULY. Next, in step S2, data is read from the external storage device into the line buffer 117 or 118 indicated by the current pointer 116.

  Then, in step S3, primary interpolation is performed using these line buffers. Step S4 is control for repeating the processing of step S3 by the magnification in the X direction. The register MULX indicating the magnification is initialized to “1”. When the X-direction enlargement / reduction loop is completed, the next X-direction enlargement ratio is calculated and stored in MULX. Then, in step S6, it is determined whether or not the above processing has been performed for a required line width.

In step S7, MULX is set to 1 in order to perform the processing of the next row. Step S8 is a control for executing the primary interpolation processing for one line from step S3 to step S7 for the enlarged width in the Y direction, that is, for MULY. The initial value of MULY is also set to “1”.
Next, in step S9, the magnification in the Y direction is calculated and stored in MULY. Step S10 updates by exchanging the buffer pointer. Then, in step S11, control is performed to repeat the processing from step S2 to step S10 for the number of lines of the input image.

FIG. 63 shows a register setting flowchart of the magnification calculator.
Here, as in the case of the specific example 9, the bit width of each register of the magnification calculator 113 shown in FIG. 61 is set to N bits. The real number magnification mul is obtained from the width A of the input image and the width B of the output image (step S11). Next, the obtained real number magnification mul is separated into an integer part and a decimal part (step S12). BASE is an integer part and DEC is a decimal part.

Next, BASE is set to BASEX1 (step S13). Further, BASE + 1 is set in BASEX2 (step S14). Further, a value obtained by multiplying DEC by 2N and adding 1 is set (step S15). Finally, in step S16, MULX is initialized to "1". For example, when the width of the input image is 3 and the width of the output image is 6, mul is obtained by the following equation.
mul = (6-1) / (3-1)
= 2.5
Further, DECX1 is obtained by the following equation.
DECX1 = DEC * 2N + 1
= 0.5 * 232 + 1
= 2,147,483,649

The comparison / selection unit 128 shown in FIG. 61 selects either BASEX1 or BASEX2 according to the magnitude relationship between DECX1 and DECX2, and sets the selected value in the MULX register as the X-direction magnification. However, DEC2 is the result of multiplying the X coordinate managed by the primary interpolation enlargement / reduction processing unit with DECX1. If the search result exceeds 2N, the rules for comparison / selection are as follows.
When DECX2 ≧ DECX1, the magnification is BASEX1
When DECX2 <DECX1, the magnification is BASEX2
If the above calculation is performed for each neighboring area, it is not necessary to hold the neighboring area table shown in FIG.

<Effect of Specific Example 10>
According to the above example, in the enlargement / reduction of the real number magnification of the image data by the primary interpolation method, the register holding the enlargement magnification is used, and the algorithm described in the ninth embodiment is used together with the memory by the neighborhood area table retention Efficiency reduction was eliminated. In addition, enlargement / reduction of the real number magnification of the image data by the primary interpolation method can be realized at high speed and with memory saving.

<Specific Example 11>
If the image to be printed extends beyond the printable area, it is necessary to cut out the image according to the size of the print area. This cutting operation is called clipping.
FIG. 64 shows an example explanatory diagram that requires clipping.
In this example, the image is printed by magnifying it five times by the nearest neighbor method. This is an image in which the black portion 135 in the figure is magnified 5 times by the nearest neighbor method. The dot configuration is shown below. Circles indicate each pixel.

  Here, assuming that a portion indicated by a white frame on the upper side of the drawing is a printable area, the left side of the black area 135 extends beyond the printable area. That is, the left side of this image is not printed but is clipped. The area 138 is an effective portion obtained by magnifying a pixel five times in the horizontal direction. The areas 137 and 136 have pixels enlarged five times in the horizontal direction, but the left area 136 is discarded because it is not printed. As described above, the boundary to be clipped usually comes in the middle of the enlarged image. In addition, the enlargement process only needs to be performed for an image within the print area, and need not be performed outside the print area. That is, the data of the black circle in the area 136 may be simply discarded. In view of the above, when clipping is considered, the edge of the image may have a different magnification than usual.

  In the example shown in the figure, when the boundary of the printable area is 139, all the white dots inside the boundary, that is, on the right side of the area 138, are printed, so that they are magnified five times. The white dot in the area 137 that is in contact with the boundary 139 is enlarged three times. Further, the dots of the black circles in the area 136 outside the boundary 139 are not printed and are not enlarged. In order to realize such clipping, it is necessary to control the partial magnification of the image differently from the normal magnification.

  This specific example provides a method for efficiently clipping the left side or the upper side in real number magnification / reduction. Note that the example described below is a method particularly suitable for upper or left clipping.

  In order to realize the above specific example 11, first, a register MULX or MULY holding an enlargement ratio is prepared. Note that these registers are collectively called a register MUL. For the left end and the upper end of the image, the initial value of MUL is used as the enlargement ratio instead of calculating the enlargement ratio. This is the same as in Example 10. The initial value of MUL is always "1" in the specific example 10, but in this specific example, it differs depending on conditions. Therefore, the enlargement ratio of the left end and the upper end is calculated in advance.

FIG. 65 shows a block diagram of the device of the eleventh embodiment.
This device includes an external storage device 141, a nearest neighbor enlarging / reducing device 142, and an output image frame buffer 143. The nearest neighbor enlarging / reducing device 142 includes a magnification calculator 144, a clipping calculator 145, a nearest neighbor enlarging / reducing device 146, and a line buffer 147.

  When this apparatus is compared with the apparatus of the ninth embodiment, a difference is that a clipping calculation apparatus 145 is added. The clipping calculator 145 is a part that calculates the magnification of the pixels at the upper end and the left end of the print area based on the position information of the pixels and the information of the printable area. This result is stored in registers MULX and MULY provided inside the magnification calculator 144.

FIG. 66 shows an operation flowchart of the eleventh embodiment.
First, in step S1, the enlargement magnification at the upper end and the left end is calculated using the clipping calculator 145. Next, in step S2, a register used in the magnification calculator is initialized. In this case, the values obtained in step S1 are set in the registers MULX and MULY. Next, in step S3, one line of data is read from the external storage device and stored in the line buffer.

  Next, in step S4, the pixels of the current input image are copied to the output image frame buffer. Next, in step S5, control is performed to repeat this processing for the X-direction magnification. In step S6, the content of the register MULX corresponding to the magnification in the X direction is updated. The method of calculating the magnification is the same as that of the specific example 10. That is, if DECX2 is larger than DECX1, BASEX1 is selected; otherwise, BASEX2 is selected.

  The processing from step S4 to step S6 is repeated for the input image line width (step S7). In order to perform the processing of the next row, the enlargement ratio of the leftmost pixel is set in MULX (step S7). Further, the processing from step S4 to step S8 is repeated the number of times in the Y direction (step S9). Further, the value of the register MULY is updated by calculating the magnification in the Y direction (step S10). The method of calculating the magnification is the same as that of the specific example 11. If DECY2 is larger than DECY1, BASEY1 is selected; otherwise, BASEY2 is selected. Control is performed to repeat the processing of steps S4 to S10 for the number of input lines (step S11), and the processing is executed for all the lines.

FIG. 67 shows a flowchart of the setting of the magnification calculation unit register.
The processing of steps S11 to S14 in the figure is the same as the processing of the specific example 9. That is, the integer part of the real number magnification mul is set to BASE, and the decimal part is set to DEC. Then, BASE is set in the register BASEX1, and BASE + 1 is set in the register BASEX2. After that, DEC * 2N + 1 is set in the register DECX1, and the enlargement ratio of the leftmost pixel calculated using the clipping calculator is set in MULX.

<Effect of Specific Example 11>
According to the above example, even when clipping is necessary in real-time enlargement / reduction of image data by the nearest neighbor method, the magnification is calculated in advance and set in the register for calculating the magnification at the head. Therefore, enlargement / reduction of the real number magnification can be realized at high speed with a small memory. Of course, it is possible to cope with clipping in various enlargement / reduction processes by primary interpolation.

FIG. 9 is an explanatory diagram of an operation of an enlargement / reduction processing unit according to a specific example 1. FIG. 2 is a block diagram of an image data enlarging / reducing device according to a specific example 1. FIG. 4 is an explanatory diagram of an enlargement method of an integer magnification. FIG. 11 is an explanatory diagram of the enlargement / reduction processing by the nearest neighbor method. 9 is a flowchart illustrating an enlargement / reduction method according to a specific example 1. FIG. 3 is a block diagram of an image enlargement / reduction device using a modulo operation. FIG. 4 is an explanatory diagram of redundancy of an enlargement / reduction table. It is explanatory drawing of calculation (modulo operation) which calculates | requires the remainder of division. 9 is an operation flowchart of an enlargement / reduction method according to a specific example 2. FIG. 11 is a block diagram of an enlargement / reduction device according to a third specific example. FIG. 9 is an explanatory diagram of resampling for pixel value correction which has been conventionally used for image enlargement / reduction processing. It is explanatory drawing of a square lattice. FIG. 3 is an explanatory diagram of a general calculation method of linear interpolation. FIG. 12 is an explanatory diagram of primary interpolation according to a specific example 3. FIG. 13 is an explanatory diagram of a processing example of primary interpolation according to a specific example 3. 14 is an operation flowchart of the device of the specific example 3. FIG. 14 is a diagram illustrating the principle of specific example 4. FIG. 14 is a block diagram of an apparatus of a specific example 4. It is an explanatory view of a neighborhood area table. FIG. 3 is an explanatory diagram of a line buffer. It is an explanatory view of image data storage processing. It is an enlarged view of the vicinity area. 14 is an operation flowchart of a specific example 4. FIG. 14 is an explanatory diagram of calculation contents of a specific example 4. FIG. 15 is a block diagram of an apparatus of a specific example 5. FIG. 3 is an explanatory diagram of a correlation between dots. FIG. 3 is an explanatory diagram of a correlation between dots. 15 is an operation flowchart of the device of the specific example 5. FIG. 14 is a block diagram of an apparatus of a specific example 6. FIG. 6 is an explanatory diagram (part 1) of a group definition. It is a group definition explanatory view (the 2). It is a group definition explanatory view (the 3). FIG. 8 is a diagram (part 4) for explaining group definitions. FIG. 4 is an explanatory diagram of a group area. It is explanatory drawing of the averaging method using a boundary pixel. FIG. 6 is an explanatory diagram of a criterion for determining a boundary pixel. FIG. 4 is an explanatory diagram of a data flow (horizontal direction) of the averaging method. FIG. 4 is an explanatory diagram of a data flow (vertical direction) of the averaging method. FIG. 4 is an explanatory diagram of input pixels to be sampled. 13 is an operation flowchart of a specific example 6. It is a flowchart of a division process. FIG. 21 is a block diagram of the device of Example 7. It is an explanatory view of an image after sampling. 14 is an operation flowchart of a specific example 7. It is a block diagram of the apparatus of the example 8. FIG. 21 is an explanatory diagram of a process in a specific example 8. It is an explanatory view of a sampling area. 15 is an operation flowchart of a specific example 8. 15 is a flowchart of an initialization process in a specific example 8. It is explanatory drawing of a proper algorithm. FIG. 4 is an explanatory diagram of a method of determining whether a carry-up has occurred. FIG. 21 is a block diagram of an apparatus of a specific example 9. FIG. 19 is a block diagram of a magnification calculator of a specific example 9; 15 is an operation flowchart of a specific example 9. It is explanatory drawing of the process of enlargement / reduction. It is a flowchart of a magnification calculation part register setting. It is a flowchart of X direction magnification calculation. It is explanatory drawing of a nearby area. FIG. 9 is an explanatory diagram illustrating a difference in the order of processing between the nearest neighbor method and the primary interpolation. It is a block diagram of the apparatus of the example 10. It is a block diagram of the magnification calculation part of specific example 10. 14 is an operation flowchart of a specific example 10. It is a flowchart of a magnification calculation part register setting. It is an example explanatory view which requires clipping. FIG. 21 is a block diagram of an apparatus of a specific example 11. 31 is an operation flowchart of a specific example 11. It is a flowchart of a magnification calculation part register setting.

Explanation of reference numerals

3 input image data 4 output image data 1X, 1Y enlargement / reduction table

Claims (14)

In a method of enlarging / reducing image data for generating output image data by reducing a plurality of input pixels forming input image data to a plurality of output pixels at a predetermined magnification,
The input image data is divided into small areas, input pixels included in the small areas and input pixels on the boundaries of the small areas are distinguished and recognized, and the input pixel values in the small areas and the input on the recognized boundaries are recognized. A method for enlarging / reducing image data, comprising calculating an input pixel value in a small area based on a pixel value and obtaining an output pixel value. The method of claim 1, wherein the image data is enlarged / reduced.
The method of enlarging / reducing image data, wherein the calculation of the input pixel value is performed using an input pixel value obtained by sampling input pixels in the small area at a predetermined interval. 3. The method of claim 2, wherein:
A method for enlarging / reducing image data, wherein a sampling area for sampling an input pixel in the small area is designated, and an output pixel value is obtained by calculating a pixel value in the sampling area. In an image data enlarging / reducing apparatus for reducing an input pixel forming input image data to a plurality of output pixels at a predetermined magnification to generate an output image,
The input image is divided into small areas including a plurality of input pixels, and any of the small areas including the input pixels is detected based on a predetermined condition by detecting an input pixel located on a boundary dividing an adjacent small area. A boundary pixel determining means for determining;
A pixel value calculating unit that calculates a pixel value of an output pixel based on each pixel value of a plurality of input pixels included in each of the small areas;
A device for enlarging / reducing image data, comprising: The image data enlarging / reducing device according to claim 4,
The image data enlargement / reduction device, wherein the pixel value calculation means samples a plurality of input pixels in the small area and calculates a pixel value of the output pixel based on the sampled input pixels. The image data enlargement / reduction device according to claim 5,
The image data enlargement / reduction device, wherein the pixel value calculation means sets a sampling area in the small area and calculates a pixel value of the output pixel based on an input pixel in the sampling area. The input image is equally divided into small regions by a boundary parallel to the main scanning direction and a boundary parallel to the sub-scanning direction, and the pixel values of the pixels included in each region are averaged to obtain the pixel value of the output pixel. , To obtain an output image obtained by reducing the input image,
An input image buffer that receives and holds one line of pixel values of pixels constituting the input image when viewed in the main scanning direction;
The pixel value of each pixel received in the input image buffer is sequentially accumulated in the main scanning direction, and is obtained before a boundary parallel to the sub-scanning direction and before a boundary pixel closest to this boundary is detected. An intermediate result buffer that holds the sum of pixel values in the same small area in small area units,
The input image is processed one line at a time in the sub-scanning direction, and a pixel value in each small area obtained before a boundary pixel closest to the boundary before the boundary parallel to the main scanning direction is detected. Is read from the intermediate result buffer, divided by the number of pixels included in each small area, an average value of the pixel values of each small area is obtained, and the average value is set as the pixel value of the pixel of the output image. A device for enlarging / reducing image data, comprising a unit. The enlargement / reduction device according to claim 7,
Sampling a part of the pixels included in the small region obtained by dividing the input image, and providing a parameter holding unit that sets and holds a sampling interval to collect those pixel values,
The intermediate result buffer is
An image data enlargement / reduction apparatus, wherein pixel values are totalized and stored at each sampling interval with reference to the parameter storage unit. The enlargement / reduction device according to claim 8,
The sampling sum counter is used to divide the pixels included in the small area obtained by dividing the input image into a plurality of sampling areas including an arbitrary number of pixels that are continuous in the main scanning direction, and to aggregate pixel values for each of the sampling areas. And
The control unit is
The average value of the pixel values in the sampling area is obtained from the pixel values totaled for each sampling area and the number of pixels included in the sampling area,
The intermediate result buffer is
An apparatus for enlarging / reducing image data, wherein a total of pixel values in the same small area, in which average values of pixel values in a sampling area are accumulated, is held in small area units. A first storage unit that holds a value of N digits after the decimal point in a multiplication result obtained by multiplying an integer value to be processed by a real number;
A second storage unit that stores a number of N digits below the decimal point of the real number;
Comparing the numerical value stored in the first storage unit with the numerical value stored in the second storage unit,
When the former value is greater than or equal to the latter value, the integer part of the multiplication result is output as the operation result, and when the former value is less than the latter value, the result of rounding up the decimal point of the multiplication result is rounded down. An integer magnification calculator including a calculation unit that outputs a calculation result. A product of the coordinate value of each pixel in the input image and a real number representing the magnification of the input image is obtained, an integer not exceeding the result of the product is determined as the number of times of copying of the pixel, and the output image data is determined. In what you get,
Among the results of the product, a register that holds only a numerical value represented by N digits after the decimal point and overflows and invalidates the numerical value after the decimal point,
Each time the calculation for calculating the product is executed, a numerical value held in this register is compared with a numerical value represented by N digits below a decimal point of a real number representing the magnification,
When the former is greater than or equal to the latter, a value obtained by rounding down the decimal point of the result of the product is determined as the number of copies, and when the former is less than the latter, a value obtained by rounding up the decimal point of the result of the product is rounded up. An apparatus for enlarging / reducing image data, comprising a magnification calculator for determining the number of copies. An input image is enlarged at a predetermined real number magnification to obtain an output image, input pixels are mapped on the output image, and a rectangular area created by the mapped output pixels is used as a neighborhood area.
When calculating the number of output pixels arranged in the coordinate axis direction of the output pixels included in the neighboring area,
A product of a coordinate value indicating a position in the output image of the neighboring area and the magnification is determined, and an integer not exceeding the result of the product is determined as the number of the output pixels in the corresponding neighboring area. At
Among the result of the product, a register that holds only a numerical value represented by N digits after the decimal point and overflows and invalidates the numerical value after the decimal point,
Each time the calculation for calculating the product is performed, a numerical value held in this register is compared with a numerical value represented by N decimal places or less of a real number representing the magnification,
When the former is greater than or equal to the latter, the value of the result of the product is rounded down to the decimal point and the number of the output pixels is determined.When the former is less than the latter, the decimal point of the result of the product is rounded up. An apparatus for enlarging / reducing image data, comprising a magnification calculator for determining a value to the number of output pixels. The enlargement / reduction device according to claim 12,
An image data enlarging / reducing device, wherein an initial value of an output of a magnification calculator is a preset constant. A product of the coordinate value of each pixel in the input image and a real number representing the magnification of the input image is obtained, an integer not exceeding the result of the product is determined as the number of times of copying of the pixel, and the output image data is determined. In what you get,
Among the results of the product, a register that holds only a numerical value represented by N digits after the decimal point and overflows and invalidates the numerical value after the decimal point,
Each time the calculation for calculating the product is executed, a numerical value held in this register is compared with a numerical value represented by N digits below a decimal point of a real number representing the magnification,
When the former is greater than or equal to the latter, a value obtained by rounding down the decimal point of the result of the product is determined as the number of copies, and when the former is less than the latter, a value obtained by rounding up the decimal point of the result of the product is rounded up. A magnification calculator for determining the number of copies,
When the edge of the output image is outside the printable area, a clipping calculation device is provided that calculates the magnification of the edge of the output image based on the information of the printable area and sets the initial value of the number of copies. An image data enlargement / reduction device.

Images