JPH04326184A - Data interpolation system - Google Patents

Abstract

PURPOSE:To realize a smooth hatched line by reducing the faintness of the hatched line, and to make sharp the angle part of a straight line, at the time of interpolating binarized two-dimensional picture data, and operating a 2 to the nth power picture element density conversion. CONSTITUTION:At the time of operating the picture element density conversion in a subscanning direction, the value of a picture element D to be interpolated is decided according to the pattern of 6 picture elements (e), (f), (g), (p), (q), and (r) existing adjacent to the surrounding of this picture element D, and that of 16 picture elements (a) to (d), (h) to (k), (l) to (o), and (s) to (v) existing on a main scanning direction line on which those 6 picture elements exist, which are close to the picture element D.

Description

[Detailed description of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a data interpolation method, and more particularly to a data interpolation method for performing power-of-two pixel density conversion on binarized two-dimensional image data in facsimile and the like.

0002

[Prior Art] When converting a first image into a second image according to the conventional data interpolation method, first, two images in the sub-scanning direction are converted.
The double pixel density conversion processing procedure will be explained using FIG. 8.

In the figure, points a to h indicate eight pixels on the first image, and the coordinates of each point are assumed to be as shown in the figure on the first image. For example, point a has coordinates (i-
2, j), and its pixel value is represented by a, in this case,
The value a indicates "0" or "1". In addition, in the figure,
The pixel value and coordinates of point a are expressed as a(i-2,j), and the same applies to other pixels.

[0004] Point B, which is the pixel value on the second image subjected to pixel density conversion, and interpolated pixel point D are B (i, j), D (i,
j+0.5). For point B, the pixel value and coordinates of point c on the first image become the values on the second image, and B
=c...(1) It is expressed as follows.

Point D is a value determined by the pixel patterns a to h, and is calculated by the logical operation of the following equation (2).

[0006] D=c×! {b×(!d)×(!e)×(!f)×
(!g)} ×! {(!a)×(!b)×d
×(!g)×(!h)} +! {(!b)×
d×e×f×g}+! {a×b×(!d)×g×h}


...(2) In the above formula, × means logical product, + means logical sum,! α indicates the inversion of α, respectively.

[0007] Formulas (1) and (2) are used to perform pixel density conversion twice in the sub-scanning direction, and when performing pixel density conversion 2n times (n is a positive integer), (1), ( The same process is repeated n times on the second image obtained by the correction process using equation 2).

Next, the case of performing double pixel density conversion in the main scanning direction will be described with reference to FIG. Points c, d, g
, h are the same pixels on the first image as in FIG.

Point B, which is a pixel value on the second image, and interpolated pixel point D are expressed as B(i,j) and D(i+0.5,j). For point B, the coordinates and pixel values on the first image become the values on the second image as they are, and B=c (3).

Point D is a value determined by the pixel pattern of points c, d, g, and h, and is calculated by the logical operation D=c×g+c×h+c×d+g×d (4).

[0011] Pixel density conversion is performed twice in the main scanning direction using equations (3) and (4), and when performing 2n times pixel density conversion, interpolation processing using equations (3) and (4) is performed. The same process is repeated n times on the obtained second image.

Furthermore, when performing pixel density conversion in both the main scanning and sub-scanning directions, (3) ，
By performing interpolation processing in the main scanning direction using equation (4), pixel density conversion of an arbitrary power of 2 is performed.

In such a conventional data interpolation method, (2
) formula determines the interpolated pixel value in the sub-scanning direction,
According to equation (2), even if the pixel value of point c is black (logical 1), the surrounding pixel values are b=1, d=e=f=g=
0, d=1, a=b=g=h=0, white (logical 0) will be interpolated.

Therefore, when performing pixel density conversion in the sub-scanning direction, there is a drawback that thin black diagonal lines tend to be blurred in the second image after interpolation.

Furthermore, since the interpolation pixel D is determined by the surrounding eight pixels, the interpolation pixel D is
), and should be interpolated with white, or is it the edge of a diagonal line, as shown in Figure 10 (B), which should be interpolated in order to make the diagonal line smooth. Since it cannot be determined whether black should be interpolated and white tends to be interpolated, the second image after interpolation has the disadvantage that diagonal lines are not smooth.

In FIG. 10, white circles indicate logic 0 pixels, and black circles indicate logic 1 pixels.

[0017]

OBJECTS OF THE INVENTION An object of the present invention is to provide a data interpolation method during pixel density conversion in which the shaded areas are maintained smoothly.

[0018]

[Structure of the Invention] The data interpolation method according to the present invention interpolates binarized two-dimensional first image data and performs pixel density conversion of a power of 2 to obtain binarized two-dimensional second image data. A data interpolation method for obtaining image data, wherein during interpolation in the main scanning direction, the pixel to be interpolated is determined according to a pixel pattern of 6 pixels on the first image that exists adjacent to the pixel to be interpolated. The method is characterized in that the value of is determined.

Another data interpolation method according to the present invention interpolates the binarized two-dimensional first image data and performs a power-of-two pixel density conversion to obtain the binarized two-dimensional second image data. It is a data interpolation method for obtaining image data, and when performing interpolation in the sub-scanning direction, in addition to the six pixels that exist close to the periphery of the pixel to be interpolated, there are also six pixels that exist on the line in the main scanning direction where these six pixels exist. The present invention is characterized in that the value of the pixel to be interpolated is determined according to 16 pixel patterns close to the pixel to be interpolated.

[0020]

Embodiments Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

FIG. 1 is a diagram showing a case in which double pixel density conversion in the sub-scanning direction is performed according to an embodiment of the present invention. 1st
The respective coordinates of 22 pixels a to v (existing on two adjacent lines in the main scanning direction) on the image are determined as shown.

Point B, which is a pixel on the second image, and interpolated pixel point D are expressed as B(i,j) and D(i,j+0.5). For point B, the coordinates and pixel values on the first image become the values of the second image as they are, and are expressed as B=f (11).

Next, regarding the interpolation pixel D, the following processing is performed. First, as shown in FIG. 2, for the 22 pixels a to v in FIG. 1, a neighboring group 1 (
The group is divided into a group of 6 pixels existing near the periphery of pixel D) and groups 2 and 3 containing the remaining pixels.

Next, D1 is calculated by performing the following logical operation of equation (22) on all pixels of groups 1 to 3.

D1 = f×p×(!e)+f×r×(!g)+e
×f×g +f×g+(!e)×f×(!g
)×(!p)×(!q)×(!r) +d×
e×(!g)×(!p)×r×s×(!t)×(!u)
+(!b)×(!×c)×d×e×(!g
)×(!p)×r×s +(!e)×g×h
×(!m)×(!n)×o×p×(!r)
+(!e)×g×h×(!i)×(!j)×o×p×(
! r)…(22)

At the same time, for proximal group 1, first, by performing calculations using the following equations (23) to (26), it is possible to determine that if it is considered to be part of the diagonal line, it becomes black (logical 1). be compensated for.

Furthermore, the function value shown in equation (27) is d
2 = 1, by performing logical operations (28) to (32) corresponding to equations (23) to (26), respectively, a width of 4 is obtained on the first image as shown in FIG. This prevents the corners of the orthogonal lines to the pixels from becoming rounded.

The interpolation pixel D is D=D1 +D2 (21), D1 is the above equation (22), and D2 is (2
8) to (32).

d21=e×p×q...(23) d22=e
×f×p…(24) d23=g×q×r…(25) d24=f×g×r…(26) d2 =d21+d22+d23+d24…(27)

[
[0030] Here, when d2 = 0, D2 = d2
...(28) When d2 = 1, when d21 = 1, equation (29), d
If d22=1, use equation (30); if d23=1, use equation (3
If d24=0, calculate equation (32).

D2=! {(!a)×b×c×d×m×n×o}
×! {(!b)×c×d×n×o}×
! {(!c)×d×o}×d…(29)

D2=! {b×c×d×(!j)×m×n×o}
×! {c×d×(!m)×n×o}×
! {d×(!n)×o}×o…(30)

D2=! {h×i×j×(!i)×s×t×u}
×! {h×i× (!j)×s×t}×
! {h×(!i)×s}×h…(31)

D2=! {h×i×j×s×t×u×(!v)}
×! {h×i×s×t×(!u)}×
! {h×s×(!t)}×s…(32)

[0035](
11) and (21) are used to perform double pixel density conversion in the sub-scanning direction, and when performing 2n times pixel density conversion, the The same process is repeated n times for the two images.

The operational flow of the above interpolation process in the sub-scanning direction is shown in FIGS. 5 and 6.

Next, the case of performing double pixel density conversion in the main scanning direction will be described with reference to FIG. Points f, g,
q, r, w, and x are pixels on the first image, and the coordinates of each point are as shown in the figure.

The pixel value B on the second image and the interpolated pixel point D are represented by B(i,j) and D(i+0.5,j). For point B, the coordinates and pixel values on the first image become the values on the second image as they are, and it is expressed as B=f (40).

Point D is determined by the pixel pattern of points f, g, q, r, w, and x, and is determined by the following equation (41).

D=f×g+w×f×q+w×g+f×r+q×g
+x×f+f×(!w)×(!x)×(!
g)×(!q)×(!r)…(41)

[0041] Pixel density conversion is performed twice in the main scanning direction using equations (40) and (41), and when performing 2n times pixel density conversion, interpolation processing using equations (31) and (41) is performed. The same process is repeated n times on the obtained second image. The above operating procedure is shown in the flowchart of FIG.

When performing pixel density conversion in both the main scanning and sub-scanning directions, (40) and (4
By performing interpolation processing in the main scanning direction according to equation 1), pixel density conversion of an arbitrary power of 2 is performed.

For example, a first image having a density of 8 dots/mm in the main scanning direction and 3.851 in/mm in the sub-scanning direction, which is the international standard for facsimile, is processed at 16 dots/mm in the main scanning direction and 7.8 dots/mm in the sub-scanning direction. When converting the pixel density to 71ine/mm, first change the sub-scanning direction to (11ine/mm).
), converted to 7.71ine/mm by formula (21),
The target pixel density can be obtained by converting the main scanning direction of the obtained image to 16 dots/mm using equations (40) and (41).

[0044]

According to the present invention, when determining the value of a pixel to be interpolated, the range of adjacent pixels to be referenced is expanded and the interpolated pixel value is determined according to the aspect of the reference adjacent pixel pattern. This has the effect that the diagonal lines are smooth and the corners of the orthogonal lines are also sharp.

[Brief explanation of the drawing]

FIG. 1 is a schematic diagram for explaining pixel density conversion processing in the sub-scanning direction according to an embodiment of the present invention.

FIG. 2 is a schematic diagram for explaining pixel density conversion processing in the sub-scanning direction according to the embodiment of the present invention.

FIG. 3 is a schematic diagram for explaining the principle of an embodiment of the present invention.

FIG. 4 is a schematic diagram for explaining pixel density conversion processing in the main scanning direction according to the embodiment of the present invention.

FIG. 5 is a flowchart showing a pixel density conversion processing operation in the sub-scanning direction according to an embodiment of the present invention.

FIG. 6 is a flowchart showing a pixel density conversion processing operation in the sub-scanning direction according to an embodiment of the present invention.

FIG. 7 is a flowchart showing a pixel density conversion processing operation in the main scanning direction according to an embodiment of the present invention.

FIG. 8 is a schematic diagram for explaining pixel density conversion processing in the sub-scanning direction according to a conventional method.

FIG. 9 is a schematic diagram for explaining pixel density conversion processing in the main scanning direction according to a conventional method.

FIG. 10 is a schematic diagram for explaining the drawbacks of the conventional method.

Claims (2)

[Claims] Claim 1: A data interpolation method for interpolating binarized two-dimensional first image data and performing pixel density conversion of a power of 2 to obtain binarized two-dimensional second image data. Therefore, during interpolation in the main scanning direction, the value of the pixel to be interpolated is determined according to a pixel pattern of 6 pixels on the first image that exists adjacent to the pixel to be interpolated. A data interpolation method characterized by: 2. A data interpolation method for interpolating binarized two-dimensional first image data and performing pixel density conversion by a power of 2 to obtain binarized two-dimensional second image data. Therefore, during interpolation in the sub-scanning direction, in addition to the 6 pixels that exist close to the periphery of the pixel to be interpolated, there are 16 pixels that exist on the main scanning direction line where these 6 pixels exist and are close to the pixel to be interpolated. A data interpolation method characterized in that the value of the pixel to be interpolated is determined according to each pixel pattern.