JP3077414B2 - Image processing method - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method,
More specifically, the present invention relates to an image processing method for expressing a gradation of an original image by a binarized pixel distribution using an average error minimum method.

[0002]

2. Description of the Related Art Conventionally, as an image processing method used for halftone expression using binary values of ON and OFF, there are a conditional determination method that takes into consideration the density and display results of peripheral pixels as a method of determining a threshold value, An independent decision method that does not consider them is known.

[0003] Among the former methods, the method with the best image quality at present is the average error minimization method. This method is described in M. R.
A paper published by Schroeder (Bell Laboratories, USA) in IEEE Spectrum in March 1969,
Image by computer (Images from co
local spatial averages of the concentrations referred to in the
of brightness).
F. Computer Graphics and Image Processing (Com) in May 1976 by Jarvis
puter graphics and image pr
In the papers published in the article, the outline of the technology for continuous tone display on the two-tone representation is an improved method in the form of a minimum average error method.

In this method, as shown in FIG. 3, attention is paid to an error E (k, l) of a pixel in which the presence or absence of a dot has been determined around the target pixel 20 for which the presence or absence of a dot is to be determined.

The error is multiplied by a weight matrix W as shown in FIG. 4 to obtain an average A (m, n). This equation is: A (m, n) = (1 / {W (k, l)) Σ ( W (k,
1) · E (k, l) ) .

Here, the density data of the target pixel 20 is represented by I
If (m, n), the dot determination data P (m, n) of the target pixel 20 is P (m, n) = A (m, n) + I (m, n). ) Is determined to be greater than or less than half of the maximum density level,
Is determined.

The error E of the pixel of interest 20 at this time is
(M, n) is as follows.

When there is a dot, P (m, n)> = 0.5 E (m, n) = P (m, n) -1 When there is no dot, P (m, n) <0.5 E (M, n) = P (m, n) The basic idea of the average error minimization method is to execute this operation for all pixels and form an image.

[0009]

However, when the above-described average error minimizing method is used, in a region where the density is rapidly changed, the error is not immediately reflected and dot missing occurs, resulting in a gap. was there.

SUMMARY OF THE INVENTION The present invention has been made to solve the above-described problem, and has as its object to provide an image processing method capable of suitably expressing an image even in an area where the density is rapidly changed. I do.

[0011]

In order to achieve this object, an image processing method according to the present invention provides a method for calculating the density of a pixel of interest in an original image .
With binarized is compared with a predetermined threshold data, using a minimum average error method to reflect the quantization error caused by the binarization in the binarization of other pixels of the pixel of interest, before Symbol two Before performing the binarization, the density data of the target pixel of the original image is calculated using the density data of the pixels surrounding the pixel.
And converts the density of the pixel of interest of the original image into the threshold value.
Data is used .

[0012]

According to the image processing method of the present invention having the above configuration, in the binarization processing using the average error minimum method ,
Before binarization, the density data of the pixel of interest in the original image is calculated by using the density data of the pixels surrounding the pixel and converted to obtain the binary value of the pixel of interest. The threshold value for the original image
, The gap due to missing dots that occurs in the area of the original image where the abrupt change occurs is prevented.

[0013]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram showing the configuration of an image processing apparatus to which the image processing method of the present invention is applied.

This image processing apparatus mainly comprises an image scanner 1 for reading an original image in multiple gradations, and an electronic control unit 3 for processing a video signal from the image scanner 1 and outputting it to a printer 2. . The electronic control unit 3 is configured as a so-called arithmetic and logic operation circuit including a well-known CPU 4, a ROM 5, a RAM 6, a video RAM 7, etc., via a bus 8, an image signal input port 9, a CRTC 11 for controlling a display 10, It is interconnected with an external storage device 12, an output port 13 for driving the printer 2, and the like.

The image input port 9 is connected to the image scanner 1. The image signal output from the image scanner 1 is converted into a digital signal in real time and stored in the video RAM 7. Therefore, the CPU 4
By accessing a predetermined area of the AM 7, data of an original image including gradation information can be read.

The printer 2 is of a thermal transfer type capable of outputting an image as a set of black and white pixels as a bit image. When a multi-color image is handled, a multi-color image scanner and a multi-color printer may be used.

Next, the image processing executed by the image processing apparatus will be described with reference to the flowchart shown in FIG.

When the control routine shown in FIG. 2 is started,
First, a process of capturing an image from the image scanner 1 via the image signal input port 9 is performed (step S10).
0, hereinafter simply referred to as S100, and the same applies to other steps). When an image signal from the image scanner 1 is input, the image signal input port 9 converts the gradation information into a numerical value between 0 and 1 and sequentially outputs the video RA.
Expand to M7. Therefore, in a predetermined area of the video RAM 7, image data I (m,
n) is stored. In this conversion process, various pre-processes according to the image quality of the target image can be performed, and gamma correction and color correction can be performed on the printer 2 or the like that enhances and compresses the contrast or finally outputs the image. It is. The numerical value after the conversion is hereinafter referred to as pixel density data.

Subsequently, scanning of the image data is started from the origin of the image, and variables m and n are initialized to values 0 ( S105,
S110). Hereinafter, by repeatedly executing the S1 2 0 to S220, performs a process of distributing the corresponding to the density of each pixel of the original image dots (black pixels). In the following description, it is assumed that the position of a pixel of interest in the scanning process is (m, n), and the density of this pixel is I (m, n).
Note that variables m and n indicating the pixel position (m, n) are represented by m =
... NMAX, n = 0, 1,..., NMAX, and the size of the original image to be processed
AX) × vertical (nMAX).

Next, the quantization error E (k, l) of the twelve pixels shown in FIG. 3 and the weight matrix W (k,
1), the process of calculating the cumulative average error A (m, n) by the above-described equation is performed (S120). In addition, these 12 pixels in the preceding area have already been subjected to the processing relating to the dot distribution, and how to obtain the quantization error E (k, l) is in accordance with the processing in the pixel of interest 20. It will be described later.

Next, a process for obtaining conversion data P (m, n) of the target pixel 20 from the density data of the pixel 21 immediately above the target pixel 20 and the immediately preceding pixel 22 shown in FIG. That is,
From the density data I (m, n-1) of the immediately above pixel 21 and the density data I (m-1, n) of the immediately preceding pixel 22, the following equation is obtained: P (m, n) = I (m, n) × 3-I (M-1, n)-
The conversion data P (m, n) is calculated from I (m, n-1) (S130).

Subsequently, the cumulative average error A thus obtained is
By adding (m, n) and the conversion data P (m, n), the dot determination data Q (m, n) of the target pixel 20 is obtained.
Is calculated (S140).

In this way, the dot determination data Q (m, n) of the pixel of interest and the density data I (m, n) of the pixel of interest 20
n) are compared with each other (S150), and the dot determination data Q (m, n) is the density data I (m, n) of the target pixel 20.
If not less than n), output image data B (m, n) is set to a value of 1 (S160); otherwise, output image data B (m, n) is set to a value of 0. (S17
0). That is, the dot determination data of the target pixel 20 in consideration of the quantization errors of the 12 pixels around the target pixel 20 and the densities of the pixels immediately above and immediately before the target pixel 20 are the density data I (m, n) of the target pixel 20. If this is the case, dots (black pixels) are arranged in the output image. The set output image data B (m, n) is stored in a predetermined area in the RAM 12.

After determining whether or not to arrange the dots on the target pixel 20 in this manner, the output image data B (m, n) is subtracted from the dot determination data Q (m, n), and the quantization error E ( (m, n) is performed (S180). Since the output image data B (m, n) takes a value of 0 or 1, a quantization error is obtained by calculating the difference between the two.

Next, in order to update the position of the target pixel 20, m indicating the horizontal position is incremented by 1 (S190). With respect to the variable m thus updated, it is determined whether or not the horizontal position is smaller than the minimum value 0 and smaller than the maximum value mMAX (S200). If into this range and it continues performing the same process, and repeats the processing described above returns to S1 2 0 (S1 2 0 to S200).

When the scanning of the pixel of interest 20 reaches the end by repeating the image processing, the variable m becomes the maximum value mMAX. In this case, the variable n indicating the vertical position of the target pixel 20 is incremented by 1 (S210), and it is determined whether or not this variable n is equal to or less than the maximum value nMAX in the vertical direction (S22).
0), if it is equal to or less than the maximum value nMAX, it is determined that the same processing is performed from the end of the next line, and the process returns to S110 to repeat the above processing (S110 to S220). When the image processing on the target pixel 20 is completed up to the end of the original image in this way, the scanning is terminated (S230), and the RAM is stopped.
6, the output image data B (m, n) is read and output to the display 10, the printer 2, or the external storage device 12 (S240), and this routine ends.

The image processing method in the image processing apparatus configured as described above is based on the minimum average error method with respect to the original image.
By comparing (m, n) with the density data I (m, n), the dots of the output image data B (m, n) are determined. By doing so, it is possible to prevent the occurrence of a gap due to missing dots in an area where the density changes rapidly.

The present invention is not limited to the embodiment described in detail above, and can be modified without departing from the scope of the invention. For example, in the present embodiment, the conversion data P (m,
When n) is obtained, the density data of the pixel immediately above and immediately before the pixel of interest 20 is used. However, the present invention is not limited to this, and the density data of the pixels immediately before and after the pixel immediately above the pixel of interest 20 may be considered. Good.

[0030]

As apparent from the above description,
According to the image processing method of the present invention, it is possible to prevent the occurrence of gaps due to missing dots, which are usually seen in the output of the average error minimization method and appear in a region where the density changes rapidly.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus using an image processing method according to the present invention.

FIG. 2 is a flowchart illustrating a flow of a process according to the embodiment.

FIG. 3 is an explanatory diagram showing a positional relationship between a target pixel and a quantization error used for binarization in a binarization process of an image processing method.

FIG. 4 is an explanatory diagram showing a weight matrix in the binarization processing of the image processing method.

FIG. 5 is an explanatory diagram showing a pixel immediately above and a pixel immediately before in a binarization process of an image processing method.

[Explanation of symbols]

 1 image scanner 3 electronic control unit

Continuation of front page (56) References JP-A-3-109871 (JP, A) JP-A-4-61474 (JP, A) JP-A-63-234772 (JP, A) JP-A-63-288568 (JP) JP-A-63-209370 (JP, A) JP-A-3-112270 (JP, A) JP-A-3-112269 (JP, A) (58) Fields investigated (Int. Cl. ⁷ , DB Name) H04N 1/40-1/409 H04N 1/46 H04N 1/60

Claims (1)

(57) [Claims] 1. A method of binarizing density data of a target pixel of an original image with a predetermined threshold value and binarizing a quantization error caused by the binarization with another pixel of the target pixel. using the minimum average error method to reflect, in an image processing method for representing an image by distribution of pixels binarized, before performing pre Symbol binarization, the concentration of the target pixel of said original image
Using the data of the density of the pixels around the pixel.
Calculated by converting Te, using the data of the density of the target pixel of the original image to the threshold value
Image processing method, characterized in that that.