JPH0744700A - Picture processing method and picture editing method - Google Patents

Abstract

PURPOSE:To perform entire smoothing of a picture to be outputted by taking the picture data of the original picture as compression original picture data and processing the compression picture data. CONSTITUTION:When an original is scanned by a scanner, it is read in a line unit according to the resolution of the scanner and becomes the picture data of the binarized original picture. The picture data of the original picture are taken as the data in a line unit coupling the coordinate X of an attribute change point whose bit attribute changes from white to block or from black to white from among black and white bit images and the auxiliary attribute Z and forms compression picture data. The formed compression original picture data are stored in a picture memory. In this case, the picture data of the original picture are compressed to the compression original picture data in a line unit and the more the efficiency is improved the more the resolution in reading the original is good.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and an image editing method for a copying machine, a computer and the like, and more particularly, when outputting image information of an original document input by an image input device, an image to be output is output. The present invention relates to an image processing method and an image editing method suitable for reducing jaggies in a contour portion.

[0002]

2. Description of the Related Art In recent years, image information of a document such as characters and figures is read by an image input device such as an image scanner (hereinafter referred to as a scanner), and the image information is taken into a known image memory as image data of an original image. The image data of the original image is reproduced as it is, or after being subjected to image editing such as enlargement, it is reproduced by a known output device such as a printer.

In such image processing, image information of an original image is meshed by an image input device such as a scanner and converted into an electric signal, and one dot of the original image and one bit of the image memory are in a one-to-one correspondence. The corresponding bitmap data (image data of the original image) is stored in the image memory. Then, incidental attributes such as colors of the original image correspond by increasing the amount of image memory corresponding to each dot of the original image.

When performing image editing such as enlarging an original image, all coordinate values of the bitmap data stored in the image memory are calculated by an image editing command, and coordinate values of all bitmap data are calculated. By changing.

[0005]

In the conventional image processing method described above, an error is inevitable when the image information of the original image is read by the scanner and binarized, and as shown in FIG. 18 (a). Not the ideal original image data, but the original image data with steps as shown in FIG. 18B, and jaggies occur in the contour portion of the output image,
There is a problem that the image quality deteriorates. In particular, unevenness was generated in the straight line portion drawn in the direction orthogonal to the scanning direction of the scanner.

Further, when the image data of such an original image is subjected to image editing, for example, enlargement processing, the step of the original image data is simply enlarged as shown in FIG.
There is a problem in that the jaggies of the contour portion of the output image such as characters are more prominent and the image quality is further deteriorated.

Therefore, in order to deal with such a problem, an image processing method has been proposed in which the original image data is smoothed (outline correction) by a known mask processing such as 3 × 3, 5 × 5. There is. FIG. 20 illustrates a 3 × 3 mask process.

However, in the image processing method by the mask processing, the image data of the original image can only be locally smoothed, and the image quality of the entire output image cannot be improved. With the demand for improved image quality, better image processing methods and image editing methods are desired.

The present invention has been made in view of these points, and overcomes the above-mentioned problems in the conventional ones.
An object of the present invention is to provide an image processing method and an image editing method capable of preventing a jaggedness of the contour portion of an image to be output and obtaining a high quality output image.

[0010]

In order to achieve the above-mentioned object, the image processing method of the present invention according to claim 1 is characterized in that image data of an original image is converted into a coordinate value of a bit attribute change point and the attribute change. The compressed original image data in units of lines paired with the incidental attribute at the point is used, and the continuous three lines of the compressed original image data are expanded as the corrected compressed data by expanding only the coordinate value of the attribute change point. When the attribute change points having the same attribute of each line are located within a predetermined range in the coordinate direction, the coordinate value of the attribute change point of the intermediate line is set to the coordinate value of the attribute change point of the first line and the attribute change point of the tail line. It is characterized in that the contour correction of the image data of the original image is performed by replacing the average coordinate value with the coordinate value of.

According to the image processing method of the present invention as set forth in claim 2, the image data of the original image is composed of a line unit in which the coordinate value of the bit attribute change point and the incidental attribute at the attribute change point are paired. Compressed original image data, the continuous three lines of the compressed original image data are expanded to the corrected compressed data by expanding only the coordinate values of the attribute change points, and the intermediate line from the attribute change points of the tail line of the corrected compressed data The attribute change point that has the same attribute as that of the attribute change point and the absolute value of the difference from the coordinate value of the attribute change point of the intermediate line is equal to or less than a predetermined value is detected. An attribute change point that has the same attribute as the attribute change point of the tail line from among the points and whose absolute value of the difference from the coordinate value of the attribute change point of the tail line is less than or equal to a predetermined value is detected, and the detected first line Attribute change point of When the absolute value of the difference between the standard value and the coordinate value of the attribute change point of the tail line is less than or equal to a predetermined value, the coordinate value obtained by adding the average of the difference to the coordinate value of the attribute change point of the intermediate line is the attribute of the intermediate line. It is characterized in that the contour value of the image data of the original image is corrected by using the coordinate value of the change point.

Further, in the image editing method of the present invention according to claim 3, when the enlargement ratio with respect to the original image is a predetermined value or more,
After performing the image processing according to claim 1 or 2,
The coordinate values of two lines adjacent to each other in the compressed original image data are multiplied so as to be equal to a predetermined expansion rate to obtain expanded compressed data, and an attribute change point for linear interpolation is detected from the expanded compressed data, and an interpolation line is detected. It is characterized in that the image data of the original image is enlarged by performing the attribute change point of (1) by linear interpolation according to the enlargement ratio.

[0013]

According to the image processing method of the present invention described in claims 1 and 2, the image data of the original image is used as the compressed original image data, and the compressed original image data is processed to obtain the image to be output. Global smoothing can be performed.

According to the image editing method of the present invention as defined in claim 3, the image data of the original image is subjected to overall smoothing, and then the smoothed compressed original image data is processed and outputted. The enlarged image can be smoothed.

[0015]

Embodiments of the present invention will now be described with reference to the drawings.

First, compressed original image data applied to the image processing method according to the present invention will be described with reference to FIG.

It is assumed that there is a manuscript in which desired characters are written in black on white paper. If you scan this document with a scanner,
Image data of the original image is read in line units according to the resolution of the scanner, for example, 400 dpi, and converted into a binarized bit image in line units as shown in FIG. 1A.

The image data (bit image) of the original image shown in FIG. 1 (a) is converted into an attribute change point at which the bit attribute changes from white to black or black to white in the black and white bit image. FIG. 1 (b) shows the data in units of a line, in which the coordinate value X of (hereinafter, referred to as a change point, also referred to as a change point in the figure) and the incidental attribute Z at the change point are paired. Thus, the compressed original image data is formed.

That is, the image data of the original image of the bit image shown in FIG.
Since the dot having the coordinate value 0) is white, a set of data in which the coordinate value X of the X coordinate of (0, white) and the incidental attribute Z are paired,
That is, assuming that the coordinate value is X and the incidental attribute is Z, the data of the change point 1 consisting of (0, white) (X1, Z1) is first created. Next, the coordinate value X in the traveling direction of the line is 4
Since the color has changed to black at (X = 4), data of the change point 2 of (X2, Z2) composed of (4, black) is created. Similarly, the data of the change point 3 of (X3, Z3), the data of the change point 4 of (X4, Z4), and (X
5, Z5), the data of change point 5 is sequentially created,
Compressed original image data of a line unit of (Xn, Zn) is formed with the coordinate value X of the bit change point and the incidental attribute Z at the change point as a pair.

The compressed original image data formed as described above is stored in a known image memory (not shown).

In this way, the image data of the original image is converted into the coordinate value X of the bit change point and the incidental attribute Z at the change point.
The compression of line-by-line compressed original image data in which and are paired (Xn, Zn) is more efficient as the resolution at the time of reading the original is superior. For example, the number of dots forming the image data of the original image is proportional to the square of the resolution of the scanner. On the other hand, in the compressed original image data after compression, the number of lines is proportional to the resolution of the scanner, but the coordinate value X of the change point of the bit in one line and the additional attribute Z at the change point are paired ( (Xn, Zn) does not change the number of pairs. Therefore, if the resolution is squared, the number of dots is 4
However, the number of compressed original image data is only twice as many as the number of lines.

FIG. 2 shows an example of the compressed original image data formed as described above, and FIG. 3 is a schematic diagram showing the changing points of the compressed original image data.

Next, an embodiment of the image processing method according to the present invention will be described with reference to the flow chart shown in FIG.

The image processing method of this embodiment is performed by processing the compressed original image data stored in the image memory (not shown).

As shown in FIG. 4, when the image processing method (outline correction method) of the present embodiment is started, the compressed original image data stored in the image memory (not shown) at the beginning of the line (line The line number and each change point number are initialized so that they can be sequentially processed from 0), and the process proceeds to the next step ST11. That is, L, i, j,
Let k ← 0.

Here, L is the line number, i is the change point number of the line L, j is the change point number of the line L + 1, and k is the change point number of the line L + 2.

Next, in step ST11, compressed original image data of three consecutive lines, L, L + 1, L + 2, is taken out from an image memory (not shown), and the next step S11 is performed.
Proceed to T12.

Next, in step ST12, the coordinate value X of the change point of the three lines taken out is set to 2 in the X coordinate direction.
ⁿ (n: natural number) times and expands to make modified compressed data,
Then, the process proceeds to next step ST13.

The enlarged value of 2 ⁿ (n: natural number) times is for facilitating the internal processing and preventing the reduction of the processing speed, and the reduction of the processing speed is prevented by another method. In this case, any value can be used.

Next, in step ST13, an incidental attribute (color attribute) Z of the change point k at the beginning of the tail line (L + 2) of the corrected compressed data and a change point j of the intermediate line (L + 1).
Has the same attribute as the incidental attribute (color attribute) Z, and the difference ΔX between the coordinate values kx and jx of both change points k and j.
The absolute value of 1 (| kx-jx |) is a predetermined value ΔX (fixed value)
The presence or absence of the following change points k and j (change points that require contour correction) is determined. If YES, the next step ST14
Proceed to.

That is, "color attribute of changing point [(L + 2), k] = color attribute of changing point [(L + 1), j]" and "|
The change points k and j satisfying the coordinate value (kx) of the change point [(L + 2), k] -the coordinate value (jx) | ≦ ΔX ”of the change point [(L + 1), j] are detected.

If the determination in step ST13 is NO, the process proceeds to step ST20 and the intermediate line (L
(J ← j + 1), where the next change point j + 1 of the first change point j in (+1) is j (j ← j + 1), the process proceeds to the next step ST21, and the number of change points in line L + 1 ≧ j (whether or not all change points j have been processed) If NO (processed for all change points j), the process proceeds to step ST40 and Y
In the case of ES (all the change points j have not been processed), the process returns to step ST13, and the same process is repeated until NO is determined in step ST21. And
In step ST40, the next change point k + 1 of the first change point k of the tail line L + 2 is set to k (k ← k + 1), and the process proceeds to the next step ST41, where the number of change points of the line L + 2 ≧ k (for all change points k If NO (processed for all change points k), proceed to step 16. If YES (not processed for all change points k), proceed to step 16. ST13
Returning to step ST41, the same processing is repeated until NO is determined in step ST41.

That is, in steps ST20 and ST21, the change point j of the line L + 1 is changed in order from the beginning, and in steps ST40 and ST41, the change point k of the line L + 2 is changed in order from the beginning. All points j and k are processed.

Next, in step ST14, the additional attribute (color attribute) Z of the change point k of the tail line (L + 2) of the corrected compressed data and the additional attribute (color attribute) Z of the change point i of the first line (L) are set. Have the same attribute, and the change point k, in which the absolute value (| kx-ix |) of the difference ΔX2 between the coordinate values kx, ix of the two change points k, i is less than or equal to a predetermined value ΔX.
Determine if there is an i (change point that requires contour correction), and YES
In the case of, the process proceeds to the next step ST15.

That is, as in step ST13, "color attribute of changing point [(L + 2), k] = color attribute of changing point [(L), i]" and "| changing point [(L +
2) Change points k and i satisfying the coordinate value (kx) of k] −the coordinate value (ix) | ≦ ΔX ”of the change point [(L), i] are detected.

If the determination in step ST14 is NO (none), the process proceeds to step ST30, where i is the change point i + 1 next to the change point i at the beginning of the start line L (i ← i
+1) Proceeding to the next step ST31, the number of change points of the line L ≧ i (whether or not all change points i have been processed)
And NO (processed for all change points i)
In the case of, proceed to the next step ST40, and YES
In the case of (all the change points i have not been processed), the process returns to step ST14 and N is returned in step ST31.
The same processing is repeated until the determination of O is made.

That is, in steps ST30 and ST31, the change point i of the line L is changed in order from the beginning, and steps ST40 and ST
In 41, the change point k of the line L + 2 is changed in order from the beginning to process all the change points i and k.

Next, in step ST15, based on the respective change points i, j, k detected in steps ST13 and ST14, the intermediate line (L + 1)
The coordinate value (jx) of the change point j is replaced with a new coordinate value (jx ') obtained by adding the average of the differences ΔX2 to the coordinate value kx of the change point i of the first line (L), and the process proceeds to the next step ST16. .

That is, "new coordinate value (jx ') of change point [(L + 1), j] = coordinate value (ix) of change point [(L), i] + {change point [(L + 2), k] Coordinate value of (k
x) -change point [(L), i] coordinate value (ix)} / 2 "
And

Next, in step ST16, it is determined whether or not there is image editing (enlargement editing) described later. If NO (no image editing), the process proceeds to the next step ST17b, and L, L + 1, L + 2 is set to 2 ^After returning to the original size by dividing by ⁿ (n: natural number), it is stored in an image memory (not shown) and the process proceeds to the next step ST18. In addition, when returning to the original size, if a decimal point occurs instead of an integer value, the decimal point is truncated.

If the determination in step ST16 is YES (image editing), the process proceeds to the next step ST17a, in which L, L + 1 and L + 2 are stored in an image memory (not shown) without being restored to the original size. To step ST18.

Next, in step ST18, L + 2
It is determined whether or not the line number of the actual compressed original image data of L + 3 following is smaller than the final line number of the compressed original image data stored in the image memory. If YES (small), the next step ST19 At L +
When 1 is set to L (L ← L + 1), the process returns to step ST11, and the same process is repeated until NO is determined in step 18, and if NO (large), the process ends.

Next, the above-mentioned image processing will be specifically described with reference to FIGS.

First, for example, line 7, line 8 and line 9 are extracted from the compressed original image data shown in FIG. 2 as compressed original image data of three consecutive lines, L, L + 1, L + 2. The extracted compressed original image data is shown in FIG. Here, the change point of line 7 is A, the change point of line 8 is B, and the change point of line 9 is C.

Next, the coordinate values of the compressed original image data shown in FIG. 5 are multiplied by 2 ⁿ (n: natural number) in the coordinate direction, where n =
It is doubled as 1 to form modified compressed data. This corrected compressed data is shown in FIG. Here, the change point of the corrected compressed data on line 7 is A ', the change point of the corrected compressed data on line 8 is B', and the change point of the corrected compressed data on line 9 is C '.

Next, a change point requiring contour correction is searched for from the change point of the corrected compressed data shown in FIG. 6 as a predetermined value ΔX = 2. That is, a change point that has the same color attribute as the change point of the line 9 and a difference in coordinate value of 2 or less is searched for on both the line 7 and the line 8 at the same time.

There are three changing points which require the contour modification as described below. 1) Change points A1 ', B1', C1 '2) Change points A2', B2 ', C2' 3) Change points A5 ', B3', C5 'Next, the intermediate line (line 8) of the modified compressed data The coordinate value of the changing point B ′ that requires contour correction is replaced with a new coordinate value as described below. 1) Change point B1 ′ = A1 ′ + (C1′−A1 ′) / 2 = 0 + (0−0) / 2 = 0 Therefore, the new coordinate value of the change point B1 ′ remains 0. 2) Change point B2 ′ = A2 ′ + (C2′−A2 ′) / 2 = 4 + (4-4) / 2 = 4 Therefore, the coordinate value of the change point B2 ′ is replaced with 6 from the new coordinate value 4. 3) Change point B3 ′ = A5 ′ + (C5′−A5 ′) / 2 = 44 + (44−44) / 2 = 44 Therefore, the coordinate value of the change point B3 ′ is changed from 46 to the new coordinate value 44.
Replace with.

FIG. 7 shows the corrected compressed data in which the contour is corrected by this replacement.

Next, when performing image editing, the corrected compressed data subjected to the contour correction is subjected to image processing (contour correction).
The compressed original image data is stored in the image memory (not shown) as it is.

If the image is not edited, the process shown in FIG.
The coordinate value of the replaced corrected compressed data shown in (4) is divided by 2 to return to the original size, and the compressed original image data is subjected to image processing (outline correction). FIG. 8 shows the compressed original image data that has been subjected to this image processing (outline correction).

Next, when the image processing on the compressed original image data of line 7, line 8 and line 9 is completed, the image processing on the compressed original image data of line 8, line 9 and line 10 is performed in the same manner as described above. Give. In addition, the compressed original image data of the line 8 when the image processing of the line 8, the line 9, and the line 10 is performed uses the data whose coordinate values are replaced by the image processing.

Thereafter, three lines are sequentially taken out and subjected to the above-mentioned image processing until the number of the tail line extracted from the image memory becomes the same as the final line number of the compressed original image data stored in the image memory. The compressed original image data shown in FIG. 2 can be the compressed original image data with the contour correction shown in FIG. 9, and the schematic diagram shown in FIG. 3 becomes a schematic diagram shown in FIG. The contour is corrected smoothly, jaggies in the contour of the output image are reliably prevented, and a high-quality output image can be obtained.

Next, an embodiment of the image editing method (smoothing processing) according to the present invention will be described with reference to the flowchart shown in FIG.

The image editing method of this embodiment is performed by processing the compressed original image data which has been subjected to the image processing (outline correction) stored in the image memory (not shown) in step ST17b of the above-mentioned image processing method.

As shown in FIG. 11, when the image editing method (enlargement editing) of this embodiment is started, the above-mentioned image processing is performed in step ST50, and then step ST is executed.
Proceed to 51.

Next, in step ST51, it is determined whether or not the enlargement ratio N for enlarging the image is 2 or more (N ≧ 2). If YES (enlargement ratio is 2 or more, N ≧ 2), Proceed to step ST52.

Then, in step ST52, the compressed original image data which has been subjected to the image processing of two lines, L and L + 1, which are adjacent to each other, is taken out from the image memory (not shown), and the process proceeds to the next step ST53.

Next, in step ST53, the coordinate value X of the extracted change point of the two lines L and L + 1 is enlarged in the X coordinate direction by a magnification N / ²ⁿ to obtain enlarged / compressed data, and the process proceeds to the next step ST54. .

Next, in step ST54, a change point for linear interpolation is detected, and the process proceeds to next step ST55.

That is, the change point of the front line L and the change point of the rear line L + 1 of the expanded / compressed data have the same attribute, and an overlapping change point is detected.

Next, in step ST55, the change point of the interpolation line corresponding to the enlargement ratio N with respect to the original image is linearly interpolated with the change point detected in step ST54 to obtain the interpolation line corresponding to the enlargement ratio N. Enlarged and compressed data is created, and the process proceeds to the next step ST56.

Next, in step ST56, L + 1
Is set to L (L ← L + 1) and the process proceeds to the next step ST57.

Next, in step ST57, L + 1
Of the compressed original image data is smaller than the final line number of the compressed original image data stored in the image memory. If YES (small), the process returns to step ST52 and NO in step 57. The same process is repeated until the determination is made. If NO (large), the process ends.

If the determination in step ST51 is NO (the enlargement ratio N is less than 2), the process proceeds to step ST61.

Then, in step ST61, the compressed original image data subjected to the image processing of the line L is taken out from the image memory (not shown), and the process proceeds to step ST62.

Next, in step ST62, the coordinate value X of the change point of the line L taken out is multiplied by N in the X coordinate direction.
The data is expanded with / 2 ⁿ to obtain expanded compressed data, and the process proceeds to the next step ST63.

Next, in step ST63, the change point of the line L is linearly interpolated as the change point of the interpolation line corresponding to the enlargement ratio N with respect to the original image to obtain the enlargement / compression data of the interpolation line corresponding to the enlargement ratio N. Create and proceed to the next step ST64.

Next, in step ST64, L + 1
Is set to L (L ← L + 1) and the process proceeds to the next step ST65.

Next, in step ST65, it is determined whether or not the line number of the compressed original image data of the line L is smaller than the final line number of the compressed original image data stored in the image memory. If YES (small) In step ST61, the same process is repeated until NO is determined in step 65. If NO (large), the process ends.

Next, the image editing (enlargement) described above will be specifically described with reference to FIGS. 12 to 16 by exemplifying the case where the enlargement ratio N = 3 of the original image.

First, two lines of line L and line L + 1 from the compressed original image data stored in an image memory (not shown) and subjected to the contour correction process (hereinafter, line L is line 1 and line L + 2 is line 1 for convenience of explanation). 2)
Is taken out and the coordinate values of line 1 and line 2 are multiplied by 3/2 ⁿ in correspondence with the enlargement ratio N to obtain enlarged compressed data. An example of this expanded / compressed data is shown in FIG. 12, and a schematic diagram showing the change points thereof is shown in FIG. 13, and the following description will be made with reference to FIGS. 12 and 13. Here, the change points of the expanded / compressed data of the line 1 are A, B, C ... And the change points of the expanded / compressed data of the line 2 are a, b, c.

Next, a change point for linear interpolation is searched for (detected). That is, the change points A, B, C of line 1 ...
And the changing points a, b, c ... Of line 2 have the same attribute, and the changing points that overlap each other are detected.

The change point for this linear interpolation is the change point A-a.
, Change point B-b, change point D-b, change point D-d
7 points between the change points E-e, between the change points F-f, and between the change points G-g.

Next, the coordinate value of the change point of the interpolation line is calculated by linearly interpolating according to the enlargement ratio N. Here, since the enlargement ratio N is set to 3, linear interpolation is performed to create two interpolation lines (interpolation line 1 and interpolation line 2). 1) Between change points A-a (white) A coordinate value + (a coordinate value-
A coordinate value) / enlargement ratio Coordinate value of interpolation line 1 = 0 + (0-0) × 1/3 = 0 Coordinate value of interpolation line = 0 = 0 + (0-0) × 2/3 = 0 2) Change point B Between -b (black) B coordinate value + (b coordinate value-
B coordinate value) / magnification ratio Coordinate value of interpolation line 1 = 3 + (6-3) × 1/3 = 4 Coordinate value of interpolation line 2 = 3 + (6-3) × 2/3 = 5 3) Change point D Between -b (black) D coordinate value + (b coordinate value-
D coordinate value) / magnification ratio Coordinate value of interpolation line 1 = 12 + (6-12) × 1/3 =
10 Coordinate value of interpolation line 2 = 12 + (6-12) × 2/3 =
84) Change point D-d (black) D coordinate value + (d coordinate value-
D coordinate value) / magnification ratio Coordinate value of interpolation line 1 = 12 + (18-12) × 1/3
= 14 Coordinate value of interpolation line 2 = 12 + (18-12) × 2/3
= 165) Between change points E-e (white) E coordinate value + (e coordinate value-
E coordinate value) / magnification ratio Coordinate value of interpolation line 1 = 21 + (24-21) × 1/3
= 22 Coordinate value of interpolation line 2 = 21 + (24-21) × 2/3
= 236) Between change points F-f (black) F coordinate value + (f coordinate value-
F coordinate value) / magnification ratio Coordinate value of interpolation line 1 = 30 + (27-30) × 1/3
= 29 Coordinate value of interpolation line 2 = 30 + (27-30) × 2/3
= 287) Between change points G-g (white) G coordinate value + (g coordinate value-
G coordinate value) / magnification ratio Coordinate value of interpolation line 1 = 36 + (33−36) × 1/3
= 35 Coordinate value of interpolation line 2 = 36 + (33-36) × 2/3
= 34 FIG. 14 shows the expanded / compressed data including this interpolation line, and FIG. 15 schematically shows the changing points.

By performing image editing (enlargement) as described above, the schematic diagram of the enlarged and compressed data shown in FIG.
It is possible to obtain a high-quality output image that has been subjected to smoothing processing as shown in FIG. 15 in which the contour jaggies are very small as shown in FIG.

Incidentally. In the image editing (enlargement) of the present embodiment, the smoothing process is performed when the enlargement ratio is 3. However, the smoothing process is performed in consideration of the conspicuousness of the jaggies of the contour of the output image and the processing time. It suffices to determine the rate N, for example N = 2, and it is not limited to the enlargement rate of this embodiment.

Further, as described above, the coordinate value of the compressed original image data is multiplied by 2 ^{n in the} X coordinate direction before the contour correction is performed, so that the compressed original image data is simply enlarged as shown in FIG. In this case (the above-mentioned image editing method, steps ST61 to ST65 in FIG. 11), it is possible to surely improve the image quality of the contour portion, particularly the contour portion of the curved portion.

In this embodiment, when the image of the original image is edited (enlarged), the coordinate value X of each line of the compressed original image data is multiplied by 2 ^{n in the} X coordinate direction (step ST
12) After performing the contour correction process, the process proceeds to the smoothing process without once returning to the original size (step ST17a), where N is the enlargement ratio of the original image and is multiplied by N / 2 ⁿ (step ST53). , Step ST62) The procedure of creating enlarged / compressed data by multiplying the coordinate value X by N times in the X coordinate direction is used, but at the time of contour correction processing, the size is temporarily returned to the original size (step ST17b), and then progresses to smoothing processing. However, it is also possible to use a procedure of multiplying the enlargement ratio N of the original image here to create enlarged and compressed data in which the coordinate value X is multiplied by N in the X coordinate direction.

Further, the present invention is not limited to the above-mentioned embodiment, but can be modified as necessary.

[0080]

As described above, according to the image processing method and the image editing method of the present invention, it is possible to prevent the jaggedness of the contour portion of the output image and to obtain a high quality output image. Produce the effect.

[Brief description of drawings]

FIG. 1 is a diagram illustrating compressed original image data applied to an image processing method according to the present invention, in which (a) is image data of an original image and (b) is compressed original image data of (a).

FIG. 2 is a diagram showing an example of compressed original image data applied to an image processing method according to the present invention.

FIG. 3 is a schematic diagram showing change points of the compressed original image data shown in FIG.

FIG. 4 is a flowchart showing an embodiment of an image processing method according to the present invention.

FIG. 5 is a diagram showing compressed original image data of lines 7, 8 and 9;

FIG. 6 is a diagram showing the corrected compressed data of FIG.

FIG. 7 is a diagram showing corrected compressed data subjected to contour correction.

FIG. 8 is a diagram showing compressed original image data subjected to image processing (outline correction).

FIG. 9 is a view similar to FIG. 2 showing the entire compressed original image data with contour correction.

10 is a view similar to FIG. 3 showing the entire change points of the compressed original image data shown in FIG. 9;

FIG. 11 is a flowchart showing an embodiment of an image editing method (smoothing processing) according to the present invention.

FIG. 12 is a diagram showing an example of expanded and compressed data.

13 is a schematic diagram showing a change point of the expanded / compressed data shown in FIG.

FIG. 14 is a diagram showing expanded / compressed data including an interpolation line.

15 is a schematic diagram showing a change point of the expanded / compressed data shown in FIG.

FIG. 16 is a schematic diagram showing a change point of simple expansion / compression data.

FIG. 17 is an explanatory diagram illustrating the effect of contour correction.

FIG. 18 is an explanatory diagram illustrating conventional original image data, where (a) is ideal original image data and (b) is conventional original image data.

FIG. 19 is an explanatory diagram illustrating conventional image editing (enlargement).

FIG. 20 is an explanatory diagram illustrating mask processing as conventional image processing (contour correction).

[Explanation of symbols]

 N magnification rate X coordinate value Z incidental attribute

Continuation of front page (51) Int.Cl. ⁶ Identification number Office reference number FI Technical display location H04N 1/409 4226-5C H04N 1/40 101 C (72) Inventor Yukio Sawano 2 Nishiazabu, Minato-ku, Tokyo No. 26-30 Fuji Shashin Film Co., Ltd. (72) Inventor Koichi Sugiyama 1-7 Yukiya Otsuka-cho, Ota-ku, Tokyo Alps Electric Co., Ltd. (72) Inventor Shuichi Aratsu 1 Yukaya-Otsuka-cho, Ota-ku, Tokyo No. 7 Alps Electric Co., Ltd. (72) Inventor, Kyuichi Fujisawa No. 7 Yukiya Otsuka-cho, Ota-ku, Tokyo Alps Electric Co., Ltd.

Claims (3)

[Claims] 1. Image data of an original image is compressed original image data in units of lines in which a coordinate value of a bit attribute change point and an incidental attribute at the attribute change point are paired, and the compressed original image data is continuous. If three lines are expanded as coordinate values of their attribute change points to be corrected compressed data, and attribute change points having the same attribute of each line of the corrected compressed data are located within a predetermined range in the coordinate direction, an intermediate line The contour correction of the image data of the original image is performed by replacing the coordinate value of the attribute change point of the above with the average coordinate value of the coordinate value of the attribute change point of the first line and the coordinate value of the attribute change point of the tail line. Image processing method. 2. Image data of an original image is compressed original image data in units of lines in which a coordinate value of a bit attribute change point and an incidental attribute at the attribute change point are paired, and the compressed original image data is continuous. The three lines are expanded to have only the coordinate values of the attribute change points as modified compressed data, and have the same attributes as those of the modified line of the tail line of the modified compressed data, overlapping with the attribute changing points of the intermediate line, and having the same attribute, An attribute change point whose absolute value of the difference from the coordinate value of the attribute change point of the intermediate line is equal to or less than a predetermined value is detected, and then the attribute change point of the trailing line has the same attribute as the attribute change point of the first line. ,
Also, the attribute change point whose absolute value of the difference from the coordinate value of the attribute change point of the tail line is less than or equal to a predetermined value is detected, and the detected coordinate value of the attribute change point of the first line and the coordinate of the attribute change point of the tail line are detected. When the absolute value of the difference with the value is less than or equal to a predetermined value, the coordinate value obtained by adding the average of the differences to the coordinate value of the attribute change point of the intermediate line is used as the coordinate value of the attribute change point of the intermediate line. An image processing method, characterized in that the contour of the image data is corrected. 3. When the enlargement ratio with respect to the original image is a predetermined value or more, after performing the image processing according to claim 1 or 2, the coordinate values of two lines adjacent to each other of the compressed original image data Is multiplied by equal to a predetermined enlargement ratio to obtain enlarged / compressed data, the attribute change point for linear interpolation is detected from the enlarged / compressed data, and the attribute change point of the interpolation line is performed by linear interpolation according to the enlargement ratio. The image editing method is characterized in that the image data of the original image is enlarged by.