JPH10302055A - Image reducing method and storage medium recording program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image reducing method capable of reducing an image without reducing picture quality and a storage medium recording a program for allowing a computer to execute the method. SOLUTION: A calculation target pixel section in an original image which is to be used for calculating the density data of pixels to be calculated in a reduced image is determined in accordance with the reduction rate of the image (step S1). Plural pixels representing mutually related calculation target pixel sections of the original image are selected based on the similarity of density data values of respective pixels in the calculation target pixel section determined in the step S1 and the similarity of distances of respective pixels (step 52). Processing (step S3) for adopting the mean value of density data of respective pixels selected in the step S2 as the density data of pixels to be calculated in the reduced image is repeated (step S4) and the density data of respective pixels in the reduced image are found out to obtain the reduced image of the original image.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image reduction method for obtaining a reduced image by reducing a digital original image and a storage medium storing a program for causing a computer to execute the method.

[0002]

2. Description of the Related Art As shown in FIG. 22, this kind of conventional image reduction is performed by one pixel row (pixel row 1, pixel row 2,...) Of an original image OG arranged in a desired reduction direction (X direction in the figure). , For each pixel row Z), a reduced image SG in which the original image OG is reduced in a one-dimensional reduction direction by reducing the original image OG in a desired reduction ratio n / m (n, m is a positive number of n <m). I'm trying to get

In this type of image reduction, an original image OG is usually used.
The processing range SH can be set in the reduction direction of. This is to prevent the unnecessary pixels from being reflected in the reduced image SG, for example, when there is an unnecessary portion (unnecessary pixel) unrelated to the image at the end of the pixel row in the reduction direction of the original image OG. . FIG. 22 shows image reduction when the range between the dotted lines is the processing range SH. However, if there is no unnecessary pixel in the original image OG, the entire pixel row in the reduction direction is processed as the processing range SH.

Conventionally, the image reduction for each pixel example is performed by averaging the weight of adjacent pixels by the weight allocated according to the position of the pixel in the pixel row of the original image as shown in FIG. In FIG. 23, the reduction ratio n / m is 2/7. In addition, each symbol in the figure is as follows.

[0005] s is a pixel number (s = 1, 2,..., S _(MAX ) of pixels constituting one pixel column (pixel column 1, pixel column 2,..., Pixel column Z) to be processed of the original image OG. ₎ : S _(MAX) is not shown, but the number of pixels in one pixel column to be processed in the original image OG), and P (s) is each pixel constituting one pixel column to be processed in the original image OG Is the density data t of the reduced image S
Pixel No. (t = 1, 2,..., T _(MAX) : t ₎ of pixels constituting one pixel column of G (pixel column 1, pixel column 2,..., Pixel column Z)
_(MAX) is not shown, but the number of pixels in one pixel column of the reduced image SG), Q (t) is density data of each pixel constituting one pixel column of the reduced image SG, s (T) is a pixel number of a pixel of the original image OG which is referred to when calculating the Q (t) among pixels constituting one pixel column to be processed of the original image OG, and s (1) is an original pixel number. The pixel No. and ah of the first pixel of the processing range SH in one pixel column to be processed of the image OG are P
(S (1)) load correction amount (ah = 0, 1,..., (N−
1)), R (t) is a calculation target area of the original image OG used for calculating the Q (t), and is within each pixel of the original image OG used for the load calculation for obtaining the Q (t). G (t) is a pixel section to be calculated of the original image OG used for calculating the Q (t), and the original image used for the weight calculation for obtaining the Q (t). This is a section indicating the range of a plurality of adjacent pixels of the OG.

[0006] The conventional method is expressed by the following equation. Q (t) = ((n−a (t)) / m) × P (s (t)) + {(n / m) × P (i)} [i = s (t) +1 to s (t + 1) ) -1] + (a (t + 1) / m) × P (s (t + 1)) (1) where s (t) = s (1) + int [(ah + (m × (t−1))) / N] a (t) = (ah + (m × (t−1))) mod n

In the above equation, int [A /
B] is an integer part of the result of dividing A by B with an integer function, A
mod B is a function for calculating the remainder when A is divided by B.

In the processing, t = 1, 2, 3,... And t are sequentially counted up, and Q (1), Q (2), Q (3),.
In this order, density data of each pixel constituting one pixel row of the reduced image SG is obtained, and reduction of one pixel row is performed. Such processing is performed in each pixel column (pixel column 1, pixel column 2,...) Arranged in parallel in a direction orthogonal to the reduction direction (Y direction in FIG. 22).
The process is performed for each pixel row Z) to reduce the original image OG in the reduction direction at a reduction rate of n / m.

[0009] As is clear from FIG.
In this conventional method, each pixel constituting one pixel column to be processed of the original image OG is divided into n pieces for convenience, and 1 /
m, and the maximum load of one pixel of the original image OG is set to n / m. Starting from the (ah + 1) th division of the s (1) th pixel, the total load is m / m (100%). R (t) is determined so that
A plurality of adjacent pixels (pixels constituting G (t)) in the pixel column are assigned a load according to the number of R (t) divisions, and the weighted average result of the load is reduced in density data of one pixel. And Then, each R (t) for each Q (t) is continuously determined, and the density data of each pixel in one pixel column of the reduced image SG is sequentially obtained.

According to this conventional method, as is apparent from the arithmetic expression for determining s (t), for example, the reduced image S
The pixel [s (k)] in the pixel row to be processed of the original image OG referred to in the calculation of the density data [Q (k)] of the k-th pixel in the pixel row to be processed G is s (1 ), It is approximately the [(m / n) × k] th pixel. Therefore, a pixel at an appropriate position according to the reduction ratio is selected as a reference pixel in the original image OG for each pixel of the reduced image SG. Then, since the density data of each pixel of the reduced image SG is obtained by the weighted average of adjacent pixels near each reference pixel, the entire processing range SH of the original image OG in the reduction direction is n / m.
The size can be reduced almost evenly.

When the two-dimensional digital original image is reduced in each of the two-dimensional directions (X direction and Y direction), the original image OG is reduced in the X direction by the above method as shown in FIG. Then, the original image OG is reduced to 2 by reducing the reduced image SG1 in the Y direction by the above method.
An image SG2 reduced in the dimensional direction is obtained.

[0012]

However, such a conventional image reduction method has the following problems. Referring to FIG. FIG. 25A shows binarization of black and white (pixels indicated by oblique lines are black) (here, density data of black pixels is “0.00”, density data of white pixels is “1.00”). FIG. 25 (b) shows the original image OG that has been
5A shows density data of each pixel of the reduced image SG obtained by reducing the original image OG in the XY directions in the XY directions in the conventional manner with a reduction ratio of 2/7, s (1) = 1, and ah = 0, respectively. .

If the density data of each pixel of the two-dimensional original image OG is P (s _X , s _Y ), and the density data of each pixel of the reduced two-dimensional image is Q (t _X , t _Y ), For example, Q
(1, 3) is a calculation target pixel section G _X (1) in the X direction of FIG. 25A and a calculation target pixel section G _Y (3) in the Y direction.
The two-dimensional calculation target region R _X (1) and the Y-direction calculation target region R _Y (3) for each pixel included in the two-dimensional calculation target pixel section surrounded by Is the load average based on the load allocated according to the calculation target area, and can be obtained by the following calculation.

Q (1,3) = 2/7 × (2/7 × P (1,8) + 2/7 × P (2,8) + 2/7 × P (3,8) + 1 / 7 × P (4,8)) + 2/7 × (2/7 × P (1,9) + 2/7 × P (2,9) + 2/7 × P (3,9) + 1 / 7 × P (4,9)) + 2/7 × (2/7 × P (1,10) + 2/7 × P (2,10) + 2/7 × P (3,10) + 1 / 7 × P (4,10)) + 1/7 × (2/7 × P (1,11) + 2/7 × P (2,11) + 2/7 × P (3,11) + 1 / 7 × P (4,11)) = 2/7 × (2/7 × 1.00 + 2/7 × 1.00 + 2/7 × 0.00 + 1/7 × 0.00) + 2/7 × (2/7 × 1.00 + 2/7 × 0.00 + 2/7 × 0.00 + 1/7 × 0.00) + 2/7 × (2/7 × 1.00 + 2/7 × 0.00 + 2/7 × 0.00 + 1/7 × 0.00) + 1/7 × (2/7 × 1.00 + 2/7 × 0.00 + 2/7 × 0.00 + 1/7 × 0.00) = 18/49 ≒ 0.37

The density data of the other pixels of the reduced image SG are calculated in the same manner. As is clear from FIG. 25, as in the conventional method, when the density data of the pixels of the image SG after the reduction is obtained by the weighted average by the load allocated according to the position of the pixels in the original image OG, for example, Q ( 1,3),
Like Q (2,1), Q (2,3), Q (2,4)
The original image OG is so divided as to divide the two-dimensional calculation target area of the original image OG for calculating the density data of these pixels into approximately two.
, The density data of the pixels of the reduced image SG is an intermediate value (gray). Also, Q
The density data may decrease (become dark gray) as in (1, 4) or Q (2, 2). On the other hand, Q
As in (3,1) and Q (4,1), if the monochrome edge of the original image OG does not pass through the two-dimensional calculation target area of the original image OG used for calculating the density data of these pixels, the density data May not decrease. Thus, the original image OG
There is a problem that the image is blurred or not blurred depending on the passing state of the black-and-white edge, and the image quality of the reduced image SG is degraded.

SUMMARY OF THE INVENTION The present invention has been made in view of such circumstances, and an image reduction method capable of reducing an image without deteriorating image quality and a program for causing a computer to execute the method are provided. It is an object of the present invention to provide a recorded storage medium.

[0017]

The present invention has the following configuration in order to achieve the above object. That is, the invention according to claim 1 is an image reduction method for reducing a digital original image to obtain a reduced image.
1) a step of determining a pixel segment to be calculated of an original image used for calculating density data of a pixel to be calculated in a reduced image according to the reduction ratio of the image; and (1-2) the above (1-1). Based on the closeness of the value of the density data between each pixel and the closeness of the distance between each pixel in the calculation target pixel section of the original image determined in the step, the calculation target pixel section of the original image that is interconnected (A) selecting a plurality of pixels representing
Making the average value of the density data of each pixel selected in the step (1-2) the density data of the pixel to be calculated in the reduced image. It is characterized in that a reduced image obtained by reducing an original image is obtained by obtaining density data.

According to a second aspect of the present invention, there is provided an image reducing method for obtaining a reduced image by reducing a digital original image, wherein (2-1) calculating density data of a pixel to be calculated for the reduced image. Determining the calculation target pixel section of the original image to be used in accordance with the reduction ratio of the image; and (2-2) the center position in the calculation target pixel section of the original image determined in the step (2-1). And (2-3) selecting a pixel whose density data value and distance are close to the center pixel from the pixels other than the pixel (center pixel). A step of setting an average value of each density data of the center pixel as density data of a pixel to be calculated of the reduced image,
By obtaining the density data of each pixel of the reduced image in the step consisting of, the reduced image obtained by reducing the original image is obtained.

According to a third aspect of the present invention, the two-dimensional digital original image is simultaneously reduced in the two-dimensional direction by the image reducing method according to the first or second aspect. It is.

According to a fourth aspect of the present invention, an image reduction process is performed by the image reduction method according to the first or second aspect for each pixel row of the original image in which pixels are arranged in a one-dimensional reduction direction. The original image is reduced in the reduction direction.

According to a fifth aspect of the present invention, there is provided a storage medium storing a program for causing a computer to execute a process of reducing a digital original image to obtain a reduced image, wherein: A step of determining a pixel segment to be calculated of an original image used to calculate density data of a pixel to be calculated later in the image in accordance with a reduction ratio of the image; and (1-2) the step of (1-1). Based on the closeness of the value of the density data between the pixels in the calculated target pixel section of the original image and the closeness of the distance between the pixels, the calculated target pixel sections of the original image that are interconnected are represented. Selecting a plurality of pixels; and (1-3) setting the average value of the density data of each pixel selected in the step (1-2) as density data of a pixel to be calculated in the reduced image. And the density data of each pixel of the reduced image It is obtained by recording a program for executing a process of obtaining a reduced image obtained by reducing the original image by obtaining the data on the computer storage media.

According to a sixth aspect of the present invention, there is provided a storage medium storing a program for causing a computer to execute a process of reducing a digital original image to obtain a reduced image, wherein (2-1) reduction A step of determining a pixel section to be calculated of an original image used to calculate density data of a pixel to be calculated in a subsequent image in accordance with the reduction ratio of the image; and (2-2) the step of (2-1). (2-3) a step of selecting, from the pixels other than the pixel at the center position (center pixel) in the calculated target pixel section of the original image, a pixel whose density data value and the distance are close to the center pixel; Using the average value of the density data of the pixel selected in the step (2-2) and the density data of the center pixel as density data of a pixel to be calculated in the reduced image;
A program for causing a computer to execute a process of obtaining a reduced image obtained by reducing the original image by obtaining density data of each pixel of the reduced image in the step consisting of is recorded on a storage medium.

[0023]

The operation of the first aspect of the invention is as follows. The density data of each pixel of the reduced image is represented by the following (1-
It is determined sequentially in steps 1) to (1-3).

In the step (1-1), the calculation target pixel section of the original image used for calculating the density data of the pixel to be calculated of the reduced image is determined according to the reduction ratio of the image. The method of determining the calculation target pixel section of the original image can be determined, for example, by the same calculation as in the related art. For example, in the case where image reduction in a one-dimensional reduction direction is performed for each pixel column of an original image in which pixels are arranged in the reduction direction as in the invention described in claim 4, the formula (1) of the conventional method is used. The pixel segment to be calculated can be determined based on When the image is simultaneously reduced in the two-dimensional direction as in the third aspect of the present invention, the two-dimensional section surrounded by the calculation target pixel section in each direction determined based on Expression (1) of the conventional method is used. (1-
What is necessary is just to set it as the calculation target pixel section of the original image determined in the step 1).

In the step (1-2), the proximity of the density data value between the pixels and the proximity of the distance between the pixels in the pixel segment to be calculated of the original image determined in the step (1-1) are described. Based on the above, a plurality of pixels representing the calculation target pixel section of the original image which are connected to each other are selected.

It is possible to know the connection state between the pixels by mutually complementarily evaluating the proximity of the value of the density data between the pixels and the proximity of the distance between the pixels in the pixel section to be calculated of the original image. it can. If both the value of the density data between pixels and the distance between the pixels are closer, the connection between the pixels is stronger, and conversely, if both the value of the density data between the pixels and the distance between the pixels are farther, the distance between the pixels is longer Connection becomes weaker,
Even when the value of the density data between pixels (or the distance between pixels) is short, if the distance between the pixels (or the value of the density data between pixels) is large, the connection between the pixels is correspondingly weakened. The connection state between the pixels is examined by an evaluation function (or an evaluation method) that complementarily evaluates the proximity of the value of the density data between the pixels and the proximity of the distance between the pixels.

In the step (1-2), all the combinations of the two-pixel set (the calculation of the original image) are performed for each pixel in the target pixel section of the original image determined in the step (1-1). If the number of pixels in the target pixel section is pn (pn-
1)! , And the connection between the two pixels is evaluated based on the closeness of the value of the density data between the pixels and the closeness of the distance between the pixels as described above. Then, the connection between each pair of two pixels is checked to search for a pixel having a connection between each pixel. For example, pixels p1-p2, pixels p2-p3, pixels p1-p
3 are connected to each other, the pixels p1-p2-p3
Are interconnected. In this way,
A plurality of pixels that are connected to each other are selected, and a plurality of pixels that represent the calculation target pixel section of the original image are determined. When only one group of a plurality of interconnected pixels is selected, the group of pixels is set as a plurality of pixels representing the calculation target pixel section of the original image. If there are two or more groups of interconnected pixels, the pixel group of the group having a large number of pixels is regarded as a plurality of pixels representing the pixel segment to be calculated in the original image.

In the step (1-3), the average value of the density data of each pixel selected in the step (1-2) is used as the density data of the pixel to be calculated in the reduced image.

By reducing the image in this way, pixels that are not connected in the pixel section to be calculated in the original image are excluded, and a plurality of pixels representing the pixel section to be calculated in the original image that are connected to each other are removed. Using the density data, the density data of the pixel for which the reduced image is to be calculated can be obtained, and the image quality can be prevented from lowering due to the image reduction.

According to the second aspect of the present invention, the first aspect is provided.
According to the same method as the step (1-1) of the invention described in (1), the calculation target pixel section of the original image used to calculate the density data of the calculation target pixel of the reduced image is determined according to the image reduction ratio. (Step (2-1)), and in step (2-2), the pixels other than the pixel at the center position (center pixel) in the calculation target pixel section of the original image determined in step (2-1) From the pixels,
A pixel whose density data value and distance are close to the center pixel is selected, and in step (2-3), the average value of the density data of the pixel selected in step (2-2) and the center pixel is reduced. The density data of the pixel to be calculated in the subsequent image is used.

That is, according to the second aspect of the present invention, the density data value and the distance between the center pixel in the original image calculation target pixel section and other pixels in the original image calculation target pixel section are close to each other. The density data value and the distance are closer to the center pixel and the center pixel among the pixels in the calculation target pixel section of the original image (the connection to the center pixel is stronger).
The density data of the pixel to be calculated for the reduced image is obtained by using the pixel. In this case, the pixel to be calculated in the reduced image is easily affected by the center pixel, but the center pixel often represents the rough density distribution state of the pixel block to be calculated in the original image. The density data of the pixel to be calculated for the reduced image can be obtained using the central pixel representing the image calculation target pixel section and the pixel strongly connected to the central pixel. Can be prevented. According to the first aspect of the present invention, it is necessary to check the connection state with respect to all the pixels in the calculation target pixel section of the original image. However, in the second aspect of the present invention, the center pixel and the other pixels are not connected. Since it is only necessary to check the connection state of, the processing time required to obtain the density data of one pixel of the reduced image can be reduced.

According to the third aspect of the present invention, the two-dimensional digital original image is simultaneously reduced in the two-dimensional direction, and
It can be suitably performed.

According to the fourth aspect of the present invention, as in the conventional method, image reduction processing is performed for each pixel row of an original image in which pixels are arranged in a one-dimensional reduction direction, and the original image is reduced in the reduction direction. Can be suitably performed.

According to the fifth aspect of the present invention, by causing a computer to read the program recorded in the storage medium, the computer executes the image reduction processing according to the first aspect of the present invention.

According to the sixth aspect of the present invention, by causing a computer to read a program recorded in a storage medium, the computer executes the image reduction processing according to the second aspect of the present invention.

[0036]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing an example of a hardware configuration for implementing an image reduction method according to the present invention.

FIG. 1 is constituted by a computer system. A CPU 10 that executes image reduction processing for reducing a digital original image to obtain a reduced image is performed by a bus line 20.
Is connected to an internal memory 30 such as a RAM via a. The internal memory 30 has various areas such as a program memory 31 into which a program is ported when executing image reduction processing, an original image memory 32 for storing original images, and a reduced image memory 33 for storing reduced images. Are set respectively. Further, the CPU 10 controls the driver 4 for the external storage device via the input / output interface 40.
1, connected to an original image input device 42, an output device 43, a setting device 44, and the like.

The driver 41 is loaded with an external storage device 45. The external storage device 45 stores an image reduction processing program created in advance. External storage device 4
Reference numeral 5 includes a magneto-optical disk, a CD-ROM, a floppy disk, a hard disk, a magnetic tape, and other storage media. When the power of the apparatus is turned on and the image reduction processing according to the present embodiment is started, the image reduction processing program is read from the external storage device 45 and the program memory 3 is read.
1 and the CPU 10 executes an image reduction process described later according to the image reduction process program. The external storage device 45 storing the image reduction processing program is:
It corresponds to a storage medium on which a program according to the present invention is recorded.

The original image input device 42 is a device for inputting an original image, for example, a digital camera, an input scanner, an image capturing device using a line sensor such as a CCD disclosed in Japanese Patent Application Laid-Open No. 3-16367 and the like. It consists of. The original image input by the original image input device 42 is stored in the original image memory 32, and the original image is subjected to image reduction processing described later, and the reduced image is stored in the reduced memory 33.
Is stored. The original image input in advance is stored in an external storage device, the original image is read from the external storage device, stored in the original image memory 32, and the original image is subjected to image reduction processing. You may comprise.

The original image memory 32 includes, as shown in FIG.
It is configured to be able to store a two-dimensional digital original image, and the reduced image memory 33 includes, as shown in FIG.
It is configured to be able to store a two-dimensional digitally reduced image.

The output unit 43 is for outputting the reduced image generated in the reduced image memory 33, and includes, for example, a display, a recording scanner, a printer, and the like. Note that the reduced image may be stored in an external storage device.

The setting unit 44 is used to make various settings, designations, instructions, and the like, and includes a keyboard, a mouse, switches, a setting monitor, and the like.

Hereinafter, the first image reduction processing according to the above configuration will be described with reference to the flowchart shown in FIG. FIG. 4 is a flowchart in the case where the two-dimensional digital original image is simultaneously reduced in the two-dimensional direction. When the processing is started, the original image is stored in the original image memory 32.
Is stored.

In the following description, s, P (s), t,
Q (t), s (t), s (1), ah, R (t), G
(T) has basically the same meaning as in the conventional method.
When it is necessary to distinguish between the direction and the Y direction, a suffix indicating the direction is added to each code (X direction [s _X , t _X , s _X (t
_X ), s _X (1), ah _X , R _X (t _X ), G
_X (t _X )], Y direction [s _Y , t _Y , s _Y (t _Y ), s
_Y (1), ah _Y , R _Y (t _Y ), G _Y (t _Y )]),
When each pixel of the original image is represented in two dimensions, the two-dimensional coordinates (s
_X , s _Y ), and when the density data of each pixel of the original image is represented in two dimensions, it is represented by two-dimensional notation (P (s _X , s _Y )),
Similarly, when each pixel of the reduced image is represented two-dimensionally, the density data is represented by two-dimensional coordinates (t _X , t _Y ).
When it is expressed in dimensions, it is expressed in two-dimensional notation (Q (t _X , t _Y )). Also, as shown in FIG. 5, R _x (t _x ) and R _x (t _x )
A two-dimensional calculation target area surrounded by _Y (t _Y )
_XY (t _X, t _Y) expressed in, G _X (t _X) and G _Y (t _Y)
And the two-dimensional calculation target pixel section enclosed by G _XY (t _X ,
t _Y ).

Step S1 of FIG. 4 ((1-1) of the present invention)
): A (two-dimensional) calculation target pixel section (G _XY () of the original image used to calculate the density data (Q (t _X , t _Y )) of the calculation target pixel of the reduced image t _X ,
t _Y )) is determined according to the image reduction ratio (n / m).

This calculation target pixel section G_XY(T_X, T_Y)
Can be determined, for example, based on the conventional equation (1).
You. That is, the calculation target pixel section G in the X direction
_X(T_X), The calculation target pixel section G in the Y direction_Y(T_Y)
Each G is determined based on the equation (1)._X(T_X)
And G_Y(T_Y) And the two-dimensional calculation target pixel section enclosed by
And G_XY(T_X, T_Y). Pixel to be calculated in X direction
Section G_X(T_X) Is s for the X direction of the original image._X(T
_XS) from the pixel_X(T_X+1) th pixel
This is a section including pixels. Where na_X(T_X) = 0
(If the coefficient of the first term on the right side of the equation (1) is “0”)
) In the X direction of the original image (s_X(T_X) +1)
S from the pixel_X(T_X+1) pixels up to the pixel
It becomes a section containing. Similarly, the calculation target pixel section in the Y direction
G_Y(T_Y) Is s for the Y direction of the original image. _Y(T_Y)
S from the pixel_Y(T_Y+1) pixels up to the pixel
(Including na_Y(T_YIf) = 0
About the Y direction of the original image (s_Y(T_Y) +1) th stroke
From element_Y(T_Y+1) Area including pixels up to the pixel
Picture).

Note that a _x (t _x ) = (ah _x + (mx)
(T _X -1))) mod n and a _Y (t _Y ) =
_{(Ah Y + (m × (} t Y -1))) is a mod n.

Further, ah _X and ah _Y are uniquely defined as “0” and (a _X (t _X ) = (m × (t _X −1)) mod
n, a _Y (t _Y ) = (m × (t _Y −1)) mod
n), G _X (t _X ) and G _Y (t _Y ) are determined and G
_XY (t _X, t _Y) may be determined.

For example, in the case of FIG.
_XY (1, 1) is (1-4, 1-4) of the original image, that is, (1,1), (2,1), (3,1), (4,
1), (1, 2), (2, 2), (3, 2), (4,
2), (1,3), (2,3), (3,3), (4,
3), (1,4), (2,4), (3,4), (4,
4) a section composed of 16 pixels, G _XY (2, 1) is a section composed of 16 pixels (4 to 7, 1 to 4) of the original image, and G _XY (3, 1) is an original image , A section composed of 16 pixels (8 to 11, 1 to 4),..., G _XY (1, 2) is a section composed of 16 pixels (1 to 4, 4 to 7) of the original image,
...

As described above, the calculation target pixel section G _XY (t _X ,
t _Y ), and the density data Q (t) of the pixel to be calculated for the reduced image using the pixels in G _XY (t _X , t _Y ).
_X , t _Y ), as shown in FIG. 6, the area surrounded by the processing range SH in each of the X and Y directions of the original image OG.
It is possible to obtain a reduced image SG in which the entire dimensional processing range (the range surrounded by the dotted line) is reduced substantially evenly to n / m times. If there are no unnecessary pixels in the X direction and / or the Y direction of the original image OG, the direction in which there is no unnecessary pixel
Is processed as the processing range SH. The processing range SH in the X direction (Y direction) is s _X (1), ah _X (s _Y
(1), ah _Y ), etc., but the pixel No (s) of the last pixel in the processing range SH in the X direction (Y direction)
_{X (LIM)} (s _{Y (LIM)} )).

The reduction ratio (n / m), s _X (1), a
_{h X, s Y (1)} , ah Y necessary data, such as _{(s X (LI M),} s Y (LIM)) , prior to the process of step S1, is set etc. setter 44.

Step S2 in FIG. 4 ((1-2) of the present invention)
): The closeness of the value of the density data between the pixels and the closeness of the distance between the pixels in the pixel segment G _XY (t _X , t _Y ) for calculation of the original image determined in step S1 Based on this, a plurality of pixels representing the calculation target pixel section G _XY (t _X , t _Y ) of the original image which are connected to each other are selected.

The connection state between the two pixels (p1, p2) can be evaluated, for example, by the following evaluation formula F (e).

F (e) = α × [Two target pixels p1,
Proximity of the density data value between p2] + β × [target 2
The proximity of the distance between the pixels p1 and p2] [alpha] and [beta] are coefficients for setting which of the proximity of the value of the density data between the pixels and the proximity of the distance between the pixels is important.

[Nearness of the value of the density data between the target two pixels p1 and p2] can be evaluated by, for example, the following evaluation formula Fd (e).

Fd (e) = {D _MAX −ABS (D _p1 −D _p2 )} Note that D _MAX is the maximum value of the density data of the pixels of the original image, and the density data of each pixel of the original image is “0”. .00 "~
If it is expressed by "1.00", _DMAX is "1.00"
In it, D _MAX if the 8-bit representation (0 to 255) is "255". D _p1 is the density data of the pixel p1 and D _p2 is the density data of the pixel p2, which is read from the coordinate values of the pixels p1 and p2 in the original image memory 32. ABS () indicates an absolute value.

This Fd (e) becomes maximum when the density data of the pixel p1 and the density data of the pixel p2 are the same, increases as the values of both density data approach, and conversely, the values of both density data are separated. Becomes smaller according to

[Nearness of the distance between the target two pixels p1 and p2] can be evaluated, for example, by the following evaluation formula Fb (e).

Fb (e) = {1− (B _p1−p2 / B _MAX )} Note that B _p1−p2 is the distance between the two pixels p1 and p2. As shown in FIG. 7, X of the pixel of the center points of the pixels, (the coordinates of _{p1 (s Xp1, s Yp1)} , the coordinates of p2 (s _Xp2, is set to s _Yp2)) Y-coordinate if , B
_p1-p2 can be obtained by Pythagorean theorem. Also, B _MAX is _{G XY (t X, t Y} ) is the inter-pixel maximum distance in, as shown in FIG. _{8, G XY (t X,} t Y) the upper left corner of the pixel among the pixels in the p _LU and pixel p in lower right corner
_RD (may be pixel p _{RU at} upper right corner and pixel p _{LD at} lower left corner).

This Fb (e) increases as the distance between the pixels p1 and p2 decreases, and decreases as the distance between the two increases.

Accordingly, the value of F (e) becomes larger as the value of the density data between the two pixels becomes closer and the distance between the two pixels becomes closer. The value becomes smaller as the distance between them increases. Further, even when one factor (the value of the density data between two pixels (or the distance between the two pixels)) is close, the other factor (the distance between the two pixels (or the value of the density data between the two pixels)) is small. If it is far away, F
(E) becomes smaller.

The state of connection between two pixels is such that as the value of the density data between the two pixels approaches, the connection increases as the distance between the two pixels approaches, the value of the density data between the two pixels increases, and The connection disappears as the distance between them increases. Even when the value of the density data between the two pixels is close, if the distance between the two pixels is long, it is estimated that the connection is low. Even when the distance between the two pixels is short, the value of the density data between the two pixels is low. If they are far apart, it can be estimated that the connection is low. Therefore, the connection state between two pixels can be known by evaluating the value of F (e).

In step S2 of FIG. 4, first, G _XY (t
_X , t _Y ) for each pixel, all combinations of two pixels (if the number of pixels in the calculation target pixel section of the original image is pn, (pn−1)! Combinations)
And F (e) is obtained for each set of two pixels.
For example, in G _XY (t _X , t _Y ) shown in FIG.
Since there are pixels (pa, pb, ..., ph, pi),
The combination is as shown in FIG.

Next, F (e) of each pair of two pixels is compared with a predetermined threshold value, and a pair of two pixels of F (e) equal to or smaller than the threshold value is excluded. The threshold value is determined in advance based on the maximum density data of the original image, the reduction ratio, α, β, and the like, which can be estimated to have a connection between each pixel of the set of two pixels.
That is, a set of two pixels having a connection between the pixels remains.

Then, the connection between each pair of the remaining two pixels is checked to search for a pixel having a connection between the pixels. This search is performed, for example, as follows.

First, attention is paid to one pixel (for example, pa) included in the set of the two remaining pixels. A pixel connected to this pixel is searched based on the set of the remaining two pixels. For example, it is assumed that a pixel connected to the target pixel pa is a pixel indicated by La in FIG.
Next, one pixel in La is set as the next target pixel (hereinafter referred to as pb), and a pixel in La connected to the target pixel is
The search is performed based on the set of two pixels remaining above. At this stage, pixels having connections with pa and pb are obtained. For example, it is assumed that a pixel connected to each of the pixels pa and pb is a pixel indicated by Lab in FIG. Next, one pixel in Lab is set as the next pixel of interest (hereinafter referred to as pd), and a pixel in Lab connected to the pixel of interest is searched based on the pair of two pixels remaining above.
As shown in FIG. 10C, the same process is repeated until one pixel is connected to the target pixel at that time. As a result of FIG. 10, the pixels pa, pb, pd, and pe are selected as mutually interconnected pixels.
Then, the pixels pa, pb,
If a pixel other than pd and pe is included, the process is repeated in the same manner as above with that pixel as the target pixel.

As a result of the above search, a group of a plurality of pixels (for example, pixels pa, pb, p
If only one group consisting of d and pe) is selected, the pixel group of that group is a plurality of pixels representing the calculation target pixel section of the original image. In addition, two or more groups of a plurality of interconnected pixels (for example, a pixel p
a, pb, pd, pe group 1 and pixel p
If there is a group 2) consisting of h and pi, the pixel group of the group having the largest number of pixels (group 1) is a plurality of pixels representing the calculation target pixel section of the original image.

When there are two or more groups of a plurality of pixels connected to each other, and there are two or more groups having the largest number of pixels, the load allocated to each pixel by the conventional method is taken into consideration. Decide one group. The weight of each pixel is calculated by the above-mentioned R _XY (t _X , t _Y ) occupied by each pixel when the calculation target region R _XY (t _X , t _Y ) is superimposed on the calculation target pixel section G _XY (t _X , t _Y ). _Y ) corresponding to the area. For example, for G _XY (1, 1) in FIG. 25A, the load of each pixel of (1 to 3, 1 to 3) is “4/49 (= n
² / m ² ) ", pixels (1-3, 4) and (3,1-
The weight of the pixel of 3)) is “2/49 (= 1/2 × n ² / m)
² ) ”, the weight of the pixel of (4, 4) is“ 1/49 (= 1 /
4 × n ² / m ² ) ”. Accordingly, the sum of the loads of the pixels belonging to each of the two or more groups having the largest number of pixels is calculated, and the pixel group of the group having the largest sum of the loads is divided into a plurality of pixels representing the calculation target pixel section of the original image. Pixels.

In this manner, a plurality of pixels representing the calculation target pixel section of the original image which are connected to each other are selected.

The evaluation formulas other than the above F (e) include, for example, [proximity of density data between two target pixels p1 and p2] and [distance of two target pixels p1 and p2]. It can also be evaluated by an evaluation formula such as multiplying by (closeness). In addition, Fd (e) and Fb (e) are also expressed by the following evaluation formula other than the above, for example, [the proximity of the density data between the target two pixels p1 and p2], [the target two pixels p1 ,
shortness of the distance between p2] can also be evaluated.

Fd (e) = {D _MAX −ABS (D _p1 −D _p2 )} / D _MAX Fb (e) = {B _MAX −B _p1-p2 }

Further, for example, each pixel of G _XY (t _X , t _Y ) is focused on the value of the density data, and the pixels are grouped with the pixels having similar density data values, and each pixel obtained by the grouping is obtained. For the group, next, the closeness of the distance may be evaluated, and a plurality of pixels representing the calculation target pixel section of the original image which are finally connected to each other may be selected.

As a result of the processing in step S2, for example,
The pixel segment G _XY (1,
3) is divided into two groups in FIG. 11A and finally group 2 is selected. G _XY (2,1) is divided into two groups in FIG. 11B and finally group 2 is selected. Chosen,
For G _XY (3, 1), one group shown in FIG. 11C is selected.

Step S3 in FIG. 4 ((1-3) of the present invention)
: The average value of the density data of each pixel selected in step S2 is used as the density data Q (t _X , t _Y ) of the pixel to be calculated for the reduced image.

For example, pixels pa, pb, p shown in FIG.
When d and pe are selected, Q (t _x , t _Y ) = ([density data of pixel pa] + [density data of pixel pb] + [density data of pixel pd] +
[Density data of pixel pe]) / 4.

As a result, the pixels having no connection in G _XY (t _X , t _Y ) are excluded, and the densities of a plurality of pixels representing the G _XY (t _X , t _Y ) having mutual connection are removed. The density data Q (t _x , t _y ) of the pixel to be calculated for the reduced image SG can be obtained by using the data, so that the image quality can be prevented from deteriorating due to the image reduction.

For example, the original image shown in FIG.
When the image is reduced by the image reduction process shown in FIG. 12, the density data of each pixel of the reduced image is prevented from being blurred or reduced as compared with FIG. 25B, and the image is appropriately reduced. ing.

Returning to FIG. 4, the processing of steps S1 to S3 is repeated until the following end judgment is satisfied, and each Q (t
_X , t _Y ) are sequentially obtained, a reduced image obtained by reducing the original image is generated, and the process ends when the end determination is satisfied (step S4).

It should be noted that Q (t _X , t _Y ) is shown in FIG.
, X-direction priority, that is, Q (1,1),
Q (2,1),..., Q (t _{X (MAX)} , 1), Q (1,
2), Q (2, 2),..., Q (t _{X (MAX)} , 2),.
(1, t _{Y (MAX)} ), Q (2, t _{Y ( MAX)} ),..., Q (t
_{X (MAX)} , t _{Y (MAX)} ) in FIG.
As shown in (b), priority in the Y direction, that is, Q (1,
1), Q (1, 2),..., Q (1, t _{Y (MAX)} ), Q
(2,1), Q (2,2),..., Q (2, t _{Y (MAX)} ),
..., Q (tX _(MAX) , 1), Q (tX _(MAX) , 2), ..., Q
(TX _(MAX) , tY _(MAX) ).

If the number of pixels (t _{X (MAX)} , t _{Y (MAX)} ) of the reduced image in the X direction and the Y direction is predetermined, t (t _x , t _Y ) _X is in the range of 1 to tX _(MAX) ,
And each range t _Y is _{1~t Y (MAX) Q (t} X, t Y)
The seeking _{Q (t X (MAX),} t Y (MA X)) and ends the process when the is Motoma'.

In the X direction and the Y direction, the processing range SH, s _Y (1 ₎ from the s _X (1) -th pixel to the last pixel (s _{X (MAX)} -th pixel) of the original image is obtained. ) -Th pixel to the last pixel (s _{Y (MAX)} -th pixel) are processed as the processing range SH in the Y direction, and the X direction is used to calculate Q (t _X , t _Y ). The processing is performed until the pixels arranged in the X direction of the original image reach the s _{X (MAX)} -th pixel, and the Y direction is calculated in the Y direction of the original image used for calculating Q (t _X , t _Y ). The processing is performed in a range until the arranged pixels reach the s _{Y ( MAX)} -th pixel, and the pixels of the original image used for calculating Q (t _X , t _Y ) in the _X and Y directions are the s _{X (MAX)} -th pixels , S _{Y (MAX)} th pixel, the process ends.

Further, in the X direction and the Y direction,
Pixel No. of the tail pixel (s_{X (LIM)}, S _{Y (LIM)})
In the case of X direction, Q (t_X, T_Y) Calculation
The pixels arranged in the X direction of the original image used for output are s_{X (LIM)}Th
Processing is performed in the range up to the pixel, and for the Y direction
Is Q (t_X, T_Y) In the Y direction of the original image
Pixels lined up s_{Y (LIM)}Processing up to the pixel
Q (t) in both the X and Y directions_X, T_Y) Calculation
Pixels of the original image used for_{X (LIM)}Th, s_{Y (LI M)}Th
When the pixel is reached, the process ends.

Note that all pixels in the X direction of the original image are processed.
When the target SH is set, s_X(1) = 1 (processing range S
The pixel number of the tail pixel of H (s_{X (LIM)})
Is s _{X (LIM)}= S_{X (MAX)}) And the X direction of the original image
When a predetermined number of pixels at the end of are truncated, s
_X(1) = [number of pixels to be truncated on the top side + 1] (processing range
Pixel No. (s) of the tail pixel of SH_{X (LIM)})
Is s_{X (LIM)}= [S_{X (MAX)}−Truncation pixels on the tail side−
1)). The processing range SH in the Y direction is also the X direction
Can be determined in the same manner as the processing range SH.

The reduction ratios in the X and Y directions may be the same.
The difference between the reduction ratio in the X direction and the reduction ratio in the Y direction
It may be reduced. In this case, the calculation target pixel section of the original image
Picture G _XY(T_X, T_Y) When calculating the X direction
Pixel section G_X(T_X) Is determined according to the reduction ratio in the X direction,
Calculation target pixel section G in Y direction_Y(T_Y) Indicates reduction in the Y direction
It should be decided according to the rate.

Next, a second image reduction process according to the present invention will be described with reference to FIG.
This will be described with reference to the flowchart shown in FIG. This second
The image reduction processing of (2) simultaneously performs image reduction in the two-dimensional direction of the two-dimensional digital original image. Note that this second
It is assumed that the original image is stored in the original image memory 32 at the time when the process is started, similarly to the first image reduction process.

Step S11 in FIG. 14 ((2-
1)): Step S of the first image processing
In the same manner as in 1, the (two-dimensional) calculation target pixel section (G _XY ) of the original image used to calculate the density data (Q (t _X , t _Y )) of the calculation target pixel of the reduced image (T _x , t
_Y )) is determined according to the image reduction ratio (n / m).

Step S12 of FIG. 14 ((2-
2)): From the pixels other than the pixel at the center position (center pixel) in the pixel segment G _XY (t _X , t _Y ) to be calculated of the original image determined in step S21, To select a pixel whose value is close to the density data value.

The center pixel in G _XY (t _X , t _Y ) is determined, for example, as follows. First, the calculation target region R in the X direction
_X (t _X ) and the calculation target area R _Y (t _Y ) in the Y direction are determined based on equation (1) of the conventional method.
_X (t _X) and R _Y (t _Y) and de 2-dimensional calculation target region surrounded _{R XY (t X, t Y} ) obtained with.

As shown in FIG. 15, the X and Y directions of each pixel
Where n is the interval of_XY(T_X, T _Y) X direction, Y direction
Direction center, and the intersection is R_XY(T_X, T_Y) Heart
A point CP is defined as a pixel including the center point CP._XY(T_X,
t_Y) Is the central pixel (the pixel indicated by oblique lines in the figure).

Note that, as shown in FIG.
_When the center point CP of _XY (t _X , t _Y ) is located at the center of the four pixels, a pixel at a predetermined position (for example, the upper left pixel of the center point CP) among the four surrounding pixels is set as the center pixel. And Further, as shown in FIGS. 16B and 16C, R
_XY (t _X, t _Y) when the center point CP is located at the center of two pixels arranged in the X direction or Y direction of a predetermined position of a pixel of its two pixels (e.g., and FIG. 16 (b) In the case of (a), the pixel on the left side of the center point CP, and in the case of FIG.

In step S12, the center pixel in G _XY (t _X , t _Y ) determined as described above is
_The above F (e) is obtained for each pair of two pixels with each pixel other than the center pixel in _XY (t _X , t _Y ). For example, FIG.
With respect to G _XY (t _X , t _Y ) consisting of 9 pixels in (a) (the center pixel is pe), the above F (e) is obtained for each two-pixel combination of the combination shown in FIG. .

Then, as shown in FIG.
The center pixel of the set of pixels and the paired pixels are arranged in descending order of F (e), and a predetermined number of pixels are selected in descending order of F (e). In the figure, three pixels pa, pb, and pd are selected. The number of pixels to choose, for _{example, G XY (t X, t} Y) ratio with respect to the center pixel other than the number of pixels in the (eight in the drawing) _{(e.g., G XY (t X, t} Y) within the 1/3 or 30% of the number of pixels other than the center pixel). If a decimal number appears in the calculation of the ratio, the calculation is rounded up. For example,
In the case of the figure, if the number of pixels other than the central pixel in G _XY (t _X , t _Y ) is １ ／, (8/3) is 2.66. .

Step S13 in FIG. 14 ((2-
3)): The average value of the density data of the pixels (pa, pb, and pd in FIG. 17B) and the central pixel (pe in FIG. 17B) selected in step S22 is reduced. The density data Q _XY (t of the pixel to be calculated in the subsequent image
_X , t _Y ).

For example, in the case of FIG. 17B, Q (t _X , t _Y ) = ([density data of pixel pe] + [density data of pixel pa] + [density data of pixel pb] +
[Density data of pixel pd]) / 4.

Since G _XY (1,2) in FIG. 25 (a) has a center pixel of (2,6) (white), in step S12, the center pixel of (2,6) As a result, Q (1,2) becomes white (1.00), and G _XY (2,1) (the center pixel is a (6,2) pixel) or G _XY (2 , 2) (the central pixel is the pixel of (6, 6)), the central pixel is (black), so in step S12, several black pixels around each central pixel are selected.
(2,1) and Q (2,2) are black (0.00).

When the original image of FIG. 25A is reduced by the second image reduction processing, the result is as shown in FIG.
Compared with (b), the density data of each pixel of the reduced image is prevented from being blurred or reduced, and the image is appropriately reduced.

When the image is reduced in this manner, the pixel for which the reduced image is to be calculated is easily affected by the center pixel, but the center pixel has a rough density distribution state of G _XY (t _X , t _Y ). G _XY (t _X ,
Q _XY (t _X , t _Y ) can be obtained by using a central pixel representing t _Y ) and a plurality of pixels strongly connected to the central pixel, thereby preventing a reduction in image quality due to image reduction. . In the first image reduction process, G _XY (t
_X , t _Y ), it is necessary to check the connection state for all the pixels. In the second image reduction processing, it is only necessary to check the connection state between the center pixel and the other pixels. The processing time required to obtain Q _XY (t _X , t _Y ) can also be reduced.

Step S14 in FIG. 14 is the same as step S4 in the first image reduction process, and the other processes in the second image reduction process are the same as those in the first image reduction process. The details are omitted.

Next, the third image reduction processing of the present invention is shown in FIG.
9 and will be described with reference to the flowchart shown in FIG.
In the third image reduction processing, the original image is reduced in the reduction direction by performing the same image reduction processing as in the first image reduction processing for each pixel row of the original image in which pixels are arranged in a one-dimensional reduction direction. Is what you do.

In this image reduction process, image reduction for one pixel column to be processed is performed in steps T2 to T7 in FIG.
This process is sequentially performed for each pixel column arranged in parallel in the direction orthogonal to the reduction direction to reduce the entire two-dimensional original image in the one-dimensional reduction direction. Note that in the flowcharts of FIGS. 19 and 20, the processing range SH in the direction orthogonal to the reduction direction (in the case of reducing the image by removing the pixel rows on the end side) is stored in the original image memory 32. I-th pixel column in the direction orthogonal to the reduction direction of the original image (i = s _Y (1), s _Y (1) +1, s _Y (1) + when reduced in the X direction)
2,... At the time of reduction in the Y direction, i = s _X (1),
s _X (1) +1, s _X (1) +2,...)
Although processing is performed so as to store the j-th pixel row (j = 1, 2, 3,...) In the direction orthogonal to the reduction direction of the reduced image memory 33, the original image stored in the original image memory 32 is processed. If all pixel rows in the direction orthogonal to the image reduction direction are to be processed, the processing may be performed with i = j (1, 2, 3,...).

For example, in the case of image reduction in which the X direction in FIG. 2 is a reduction direction, each pixel row arranged in the Y direction is sequentially processed as one pixel row to be processed. In this case, Q in one pixel column (i-th pixel column) to be processed of the original image
Of the pixels included in the calculation target pixel section G _x (t _x ) for (t _x , j) calculation, the density data (P (s _x , i)) of the pixel used for the average calculation is read from the original image memory 32. The image is reduced by (t) in the image memory 33 after reduction.
_X, the density data Q (t _X pixel coordinate values of j), j) will be stored in the reduced after image memory 33 as. On the other hand, FIG.
In the case of image reduction in which the Y direction is a reduction direction, the pixel rows arranged in the X direction are sequentially processed as one pixel row to be processed. In this case, one pixel column (i
Of pixels included in the calculation target pixel section G _Y (t _Y ) for calculating Q (j, t _Y ) in the (th pixel row), the density data (P (i, s _Y )) of the pixel used for the average calculation ) to read from the original image memory 32 and image reduction, the result of reduced post-image memory 33 (j, t _Y) density data Q (j pixel coordinate values of the reduced after image memory 33 as t _Y) I will remember.

Step T1: FIG. 19: Initial setting is performed.
Set “1” to j, and set s to i in the case of reduction in the X direction.
_Y (1) is set, and i is s _X for reduction in the Y direction.
Set (1). Note that s _Y (1), s _X (1),
Reduction ratio (n / m), ah _X (in the case of reduction in the X direction),
Necessary data such as ah _Y (in the case of reduction in the Y direction) is set from the setting unit 44 and the like prior to the processing in step T1.

Step T2 in FIG. 19: Initial setting of image reduction processing for one pixel row is performed. T for reduction in the X direction
_X is set to “1”, and in the case of reduction in the Y direction, “1” is set to t _Y.

Step T3 in FIG. 19 ((1-
1)): an original image (of the original image) used to calculate the density data of the pixel to be calculated in the reduced image (the pixel to be calculated in the pixel column to be processed in the reduced image) The calculation target pixel section (within the processing target pixel column) is determined according to the image reduction ratio (n / m).

The calculation target pixel section can be determined, for example, based on the conventional equation (1). That is, in the case of reduction in the X direction, the s _X (t _X ) -th pixel to the s _X (t _X +1) -th pixel in the i-th pixel row of the pixel rows arranged in the Y direction of the original image Area up to the pixel of (however,
When n−a _X (t _X ) = 0, (s _X (t _X ) +
The (1) -th pixel to the s _X (t _X +1) -th pixel) is defined as a calculation target pixel block G _X (t _X ). Also,
In the case of reduction in the Y direction, the s _Y (t _Y ) -th pixel to the s _Y (t _Y +1) -th pixel in the i-th pixel row of the pixel row arranged in the X direction of the original image Lot to the pixel (although in the case of _{n-a Y (t Y)} = 0 is, (s
And _Y (t _Y) +1) th pixel from s _Y (t _Y +1) th section to the pixel) is calculated pixel partitioning G _Y (t _Y).

In the case of FIG. 25A, G _X (1) is a section composed of four pixels (1 to 4, i), G _X (2)
Is a section composed of four pixels (4 to 7, i), G
_X (3) is a section composed of four pixels (8-11, i),..., G _Y (1) is a section composed of four pixels (i, 1-4), G _Y ( 2) is a section composed of four pixels of (i, 4 to 7), and G _Y (3) is 4 of (i, 8 to 11).
, A section made up of pixels.

Also in this processing, when reducing in the X direction, ah _X is uniquely defined as “0” to determine G _X (t). In the case of reducing in the Y direction, ah _Y is uniquely defined. "0"
G _Y (t) may be determined as

By determining the pixel segment to be calculated in this way and obtaining the density data of the pixel to be calculated of the reduced image using the pixels in the pixel segment to be calculated, the processing range in the reduction direction of the original image is obtained. The entire SH can be reduced substantially evenly to n / m times.

Step T4 of FIG. 19 ((1-
2)), Step T5 ((1- (
3) is a process similar to steps S2 and S3 of the first image reduction process. That is, in the third image reduction process, in step T3, a calculation target pixel section is determined for one pixel column to be processed of the original image.
A plurality of pixels representing the calculation target pixel section which are connected to each other are selected, and the density data of the calculation target pixel of the reduced image is obtained by averaging these pixels. Thus, in the image reduction in the one-dimensional reduction direction, the same effect as the first image reduction processing can be obtained.

In this image reduction processing, the maximum distance B _MAX between pixels when Fb (e) of the two pixels p1 and p2 is evaluated by the above-described evaluation expression is G when the image is reduced in the X direction.
Equivalent to the number of pixels in _X (t _x ), and G _Y when reduced in the Y direction
This corresponds to the number of pixels in (t _Y ). 7B, the distance B _p1- p2 between the two pixels p1 and p2 when reducing in the X direction is the distance B between the two pixels p1 and p2 when reducing in the Y direction.
_p1-p2 is obtained according to FIG.

[0111] In step T6 of FIG. 19, it is determined whether the image reduction processing is completed for one pixel row of the current processing target, if not completed, when the reduction in the X-direction is t _X
Is counted up, and when reducing in the Y direction, t _Y is counted up (step T7), and the process returns to step T3 to return the density data of the next pixel in the current processing target pixel column of the reduced image. Ask. Thereafter, steps T3 to T3 are performed until the image reduction processing for the current pixel row to be processed is completed.
7 is repeated, and in the case of reduction in the X direction, t _X
= 1, 2, 3,... And Q (1,
j), Q (2, j), Q (3, j),..., the density data of each pixel constituting the j-th pixel column in the Y direction of the reduced image in the i-th direction in the Y direction of the original image. , And in the case of reduction in the Y direction, t _Y = 1, 2, 3,... Are sequentially counted up, and Q (j, 1), Q (j,
2), Q (j, 3),..., The density data of each pixel constituting the j-th pixel column in the X direction of the reduced image is obtained from the i-th pixel column in the X direction of the original image. . When the image reduction processing for one pixel row to be processed is completed, it is determined in step T8 in FIG. 20 whether or not the image reduction processing for all pixel rows to be processed has been completed. j is counted up (step T9), and the process returns to step T2 in FIG. 19 to perform the reduction processing on the next pixel row. When the image reduction processing on all the pixel rows to be processed ends, the processing ends.

In the case of reduction in the X direction (reduction in the Y direction), the end determination of step T6 is performed as follows. The number of pixels in the X direction (Y direction) of the reduced image (t _{X (MAX)} (t
_{Y (MAX)} )) is predetermined, then Q (t
_{When X (MAX)} , j) (Q (j, tY _(MAX) )) is obtained, the image reduction processing of one pixel column to be processed is ended.

In the X direction (Y direction), the s _X (1) (s _Y (1))-th pixel to the last pixel (s _{X (MAX)} -th pixel (s _{Y (MAX)} ) of the original image ) Is processed as the processing range SH in the X direction (Y direction), the processing target of the original image used to calculate Q (t _X , j) (Q (j, t _Y )) pixels in one pixel column performs image reduction processing of s _{X (MAX)} th pixel (s Y _(MAX) th pixel) in a range until a 1 pixel string to be processed, Q (t _X, j )
When a pixel in one pixel column to be processed of the original image used for calculating (Q (i, t _Y )) reaches the s _{X (MAX)} -th pixel (s _{Y (MAX)} -th pixel), The image reduction processing for one pixel row is completed.

Further, the processing range SH in the X direction (Y direction)
Hara used to calculate the pixels of the tail of the pixels _{No (s X (LIM) (} s Y (LIM))) if they decide _{is, Q (t X, j)} (Q (i, t Y)) to The pixel in one pixel column to be processed is s
Image reduction processing of one pixel column to be processed is performed until the pixel reaches the _{X (LIM)} -th pixel (s _{Y (LIM)} -th pixel).
_{(T X, j) (Q} (i, t Y)) pixels s _X in one pixel row of the process target of the original image used for calculating the _(LIM) th pixel (s Y _(LIM) th pixel) Is reached, the image reduction processing for one pixel column to be processed ends.

In the case of reduction in the X direction (reduction in the Y direction), the end determination of step T8 is made as follows. If the number of pixel rows in the Y direction (X direction) of the reduced image (t _{Y (MAX)} (t _{X (MAX)} )) is predetermined, j = t
_When the reduction processing of the pixel row of _{Y (MAX)} (j = t _{X (MAX)} ) is completed, the processing ends.

In the Y direction (X direction), the s _Y (1) (s _X (1))-th pixel to the last pixel (s _{Y (MAX)} -th pixel (s _{X (MAX)} ) of the original image ) Is processed as the processing range SH in the Y direction (X direction) when the reduction process of the pixel row of i = s _{Y (MAX)} (i = s _{X ( MAX)} ) is completed. Ends the processing.

Further, the processing range SH in the Y direction (X direction)
If the pixel number _{(sY (LIM) (sX (LIM)} )) of the _last pixel is determined, the pixel row of i = _{sY (LIM)} (i = _{sX (LIM)} ) is reduced. The process ends when the process is completed.

Note that the processing ranges SH in the X and Y directions are
As described in the first image reduction process, s _X (1)
_{(S X (LIM)),} s Y (1), may be determined a _{(s Y (LIM)).}

Further, for example, when an image capturing apparatus using a line sensor captures a pixel row in each main scanning direction and immediately reduces the image of the pixel row, the original image memory 32 is stored as shown in FIG. Each time data of one pixel row in the main scanning direction is captured by the image capturing device, the data is stored in the original image memory 32 of FIG. FIG.
9, the image may be sequentially reduced in the processing of FIG. 20 and stored in the reduced image memory 33.

Further, steps T4 and T5 of the third image reduction processing are replaced with steps S4 and T5 of the second image reduction processing.
If the processing is performed in the same manner as in S12 and S13, the same effect as in the second image reduction processing can be obtained in reducing the image in the one-dimensional reduction direction. In this case,
The central pixel of G _X (t _x ) at the time of reduction in the X direction is shown in FIG.
In the method described above, the center of R _x (t _x ) in the X direction is obtained,
The pixel including the center may be set as the center pixel of G _X (t _x ). Similarly, the center pixel of G _Y (t _Y ) at the time of reduction in the Y direction is determined by R _Y ( The center in the Y direction of t _Y ) may be obtained, and the pixel including the center may be set as the center pixel of G _Y (t _Y ).

[0121]

As is apparent from the above description, according to the first aspect of the present invention, the calculation target pixel section of the original image is connected to each pixel in the calculation target pixel section of the original image. Is selected, and the density data of the pixel to be calculated for the reduced image is obtained by averaging the density data of each pixel, so that the connection is made within the calculation target pixel section of the original image. By excluding non-existing pixels, density data of pixels to be calculated in the reduced image can be obtained by using density data of a plurality of pixels representing the calculation target pixel section of the original image which are connected to each other. In addition, it is possible to prevent a decrease in image quality due to image reduction.

According to the second aspect of the present invention, by averaging the density data of the central pixel and the pixels whose distance and the density data are close to the central pixel in the pixel segment to be calculated of the original image. Since the density data of the pixel to be calculated in the reduced image is calculated, a central pixel representing a rough density distribution state of the pixel segment to be calculated in the original image and a pixel having a high connection with the central pixel are used. Thus, the density data of the pixels of the image after the reduction can be obtained, and the deterioration of the image quality due to the image reduction can be prevented. Further, since it is only necessary to check the connection state between the center pixel and the other pixels in the calculation target pixel section of the original image, the processing time required for obtaining the density data of one pixel of the reduced image can be reduced. it can.

According to the third aspect of the present invention, it is possible to simultaneously and suitably reduce the size of the original image in the two-dimensional direction.

According to the fourth aspect of the present invention, image reduction processing is performed for each pixel row of an original image in which pixels are arranged in a one-dimensional reduction direction, and processing for reducing the original image in the reduction direction is preferably performed. Can be.

According to the fifth and sixth aspects of the present invention, it is possible to cause a computer to execute the image reduction processing according to the first and second aspects of the present invention.

[Brief description of the drawings]

FIG. 1 is a block diagram showing an example of a hardware configuration for implementing an image reduction method according to the present invention.

FIG. 2 is a diagram showing a configuration of an original image memory.

FIG. 3 is a diagram illustrating a configuration of a reduced image memory.

FIG. 4 is a flowchart illustrating a procedure of a first image reduction process according to the present invention, in which image reduction in a two-dimensional direction of a two-dimensional digital original image is performed simultaneously.

FIG. 5 is a diagram showing a two-dimensional calculation target area and a two-dimensional calculation target pixel section;

FIG. 6 is a diagram showing a relationship between an original image and a reduced image.

FIG. 7 is a diagram illustrating a method for calculating a distance between two pixels.

FIG. 8 is a diagram illustrating a method of calculating a maximum inter-pixel distance in a calculation target pixel section of an original image.

FIG. 9 is a diagram for explaining a procedure for checking a connection state of each pixel in a calculation target pixel section of an original image.

FIG. 10 is a diagram for explaining a procedure for checking a mutual connection state of each pixel;

FIG. 11 is a diagram illustrating a connection state of each pixel in each calculation target pixel section of the original image of FIG.

FIG. 12 is a diagram showing a result of reducing the original image of FIG. 20A by a first image reduction process.

FIG. 13 is a diagram showing a case where the processing procedure is given priority in the X direction and a case where the processing procedure is given priority in the Y direction.

FIG. 14 is a flowchart illustrating a procedure of a second image reduction process according to the present invention, in which image reduction in a two-dimensional direction of a two-dimensional digital original image is simultaneously performed.

FIG. 15 is a diagram illustrating a method of calculating a center pixel of a calculation target pixel section of an original image.

FIG. 16 is a diagram illustrating a method of calculating a center pixel of a calculation target pixel section of the original image.

FIG. 17 is a diagram for explaining a procedure for examining the connection state between each pixel other than the center pixel in the calculation target pixel section of the original image and the center pixel.

FIG. 18 is a diagram showing a result of reducing the original image of FIG. 20A by a second image reduction process.

FIG. 19 shows a procedure of a third image reduction process according to the present invention, in which an image reduction process is performed for each pixel column of an original image in which pixels are arranged in a one-dimensional reduction direction to reduce the original image in the reduction direction. It is a flowchart.

FIG. 20 is a flowchart showing a procedure of a second image reduction process according to the present invention.

FIG. 21 is a diagram showing a configuration of a modification of the original image memory.

FIG. 22 is a diagram for explaining a conventional image reduction method.

FIG. 23 is a diagram illustrating a conventional image reduction method for each pixel column.

FIG. 24 is a diagram showing a procedure for reducing an image of a two-dimensional original image in a two-dimensional direction by a conventional method.

FIG. 25 is a diagram for explaining a problem of the conventional method.

[Explanation of symbols]

10: CPU 31: program memory 32: the original image memory 33: after the reduction image memory 45: Storage _{P (s X, s Y)} : density data Q of the pixels of the original image (t _X, t _Y): After reduction Density data G _XY (t _X , t _Y ), G _X (t _X ), G _Y (t _Y ) of the image pixel

Claims (6)

[Claims] 1. An image reduction method for reducing a digital original image to obtain a reduced image, comprising: (1-1) calculating an original image used for calculating density data of a pixel to be calculated for the reduced image; (1-2) determining the calculation target pixel section according to the reduction ratio of the image; and (1-2) determining the density data value between the pixels in the calculation target pixel section of the original image determined in the step (1-1). A step of selecting a plurality of pixels representing the calculation target pixel section of the original image, which are mutually connected, based on the proximity and the proximity of the distance between the pixels; (1-3) the (1-2) Obtaining the average value of the density data of each pixel selected in the step as density data of the pixel to be calculated for the reduced image, and obtaining the density data of each pixel of the reduced image in the step of An image characterized in that a reduced image obtained by reducing an original image is obtained. Small way. 2. An image reduction method for reducing a digital original image to obtain a reduced image, comprising: (2-1) calculating an original image used for calculating density data of a pixel to be calculated for the reduced image; A step of determining the calculation target pixel section in accordance with the image reduction ratio; and (2-2) a pixel other than the pixel at the center position (center pixel) in the calculation target pixel section of the original image determined in the step (2-1). (2-3) selecting a pixel whose density data value and distance are closer to the center pixel from the pixels of (2-3); and (2-3) each density data of the pixel selected in the step (2-2) and the center pixel Using the average value of as the density data of the pixel to be calculated of the reduced image, and obtaining the density data of each pixel of the reduced image in the step of calculating the reduced image obtained by reducing the original image. A method for reducing an image, comprising: 3. An image reduction method according to claim 1, wherein the two-dimensional image of the two-dimensional digital original image is reduced simultaneously. 4. An image reduction process according to claim 1 or 2, wherein an image reduction process is performed for each pixel row of the original image in which pixels are arranged in a one-dimensional reduction direction, and the original image is reduced in the reduction direction. An image reduction method, comprising: 5. A storage medium storing a program for causing a computer to execute a process of reducing a digital original image to obtain a reduced image, wherein: (1-1) a calculation target of the reduced image A step of determining a pixel section to be calculated for the original image used to calculate the density data of the pixel according to the reduction ratio of the image; and (1-2) a calculation target of the original image determined in the step (1-1). A step of selecting a plurality of pixels representing the calculation target pixel section of the original image that are connected to each other based on the proximity of the value of the density data between the pixels in the pixel section and the proximity of the distance between the pixels; And (1-3) a step of using the average value of the density data of each pixel selected in the step (1-2) as the density data of the pixel to be calculated in the reduced image. By calculating the density data of each pixel of the subsequent image, A storage medium recording a program for executing a process of obtaining a reduced image obtained by reducing the image to a computer. 6. A storage medium storing a program for causing a computer to execute a process of reducing a digital original image to obtain a reduced image, wherein (2-1) a calculation target of the reduced image is calculated. A step of determining a pixel section to be calculated of the original image used to calculate the density data of the pixel in accordance with the reduction ratio of the image; and (2-2) a calculation target of the original image determined in the step (2-1). A step of selecting, from pixels other than the pixel at the center position (center pixel) in the pixel section, a pixel having a value close to the value of density data and a distance from the center pixel, (2-3) Using the average value of the respective density data of the pixel selected in the step and the center pixel as the density data of the pixel to be calculated for the reduced image, and calculating the density data of each pixel of the reduced image in the step of Reduced image obtained by reducing the original image Storage medium storing a program for executing obtaining processing to the computer.