JPH089155A - Image signal binarization processing unit and its method - Google Patents

Abstract

PURPOSE:To obtain the image signal binarizing processing unit and its method in which an image with a desired density is formed for the entire density area including a shadow area of an image obtained by binarization the image when the image is binarized by the error diffusion method. CONSTITUTION:A multi-level image signal I(x, y) is corrected based on an error signal E(x-k, x-l) from an error memory 24 and an error diffusion coefficient W(k, l) from an error diffusion coefficient memory 28 and a corrected multi-level image signal I'(x, y) is compared with a threshold level signal TH at a comparator 14 to obtain a binary image signal P(x, y). When the binary image signal P(x, y) corresponds to a shadow area, a correction signal generating circuit 18 is used to correct the binary image signal P(x, y) so as to extend a noon-recording area and the error signal E(x-k, x-l) is corrected based on the corrected binary image signal P(x, y). Thus, the density of the image formed by the binary image signal P(x, y) in the shadow area is adjusted and an excellent image is obtained.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention, when converting a multi-valued image signal into a binary image signal by an error diffusion method, in a shadow area of an image formed from the binary image signal, the non-valued The present invention relates to an image signal binarization processing apparatus and method for enlarging a recording area.

[0002]

2. Description of the Related Art When a gradation image is reproduced by using a display device or a printer device capable of only binary display, a gradation image signal which is a multi-valued image signal is composed of "0" and "1" signals.
A process of converting into a value image signal is performed. In this case, there is an error diffusion method that can reproduce a good halftone image in which the occurrence of moire is suppressed by modulating the frequency (or density) of the image according to the multi-valued image signal.

In the error diffusion method, when a multi-valued image signal of an input pixel is compared with a threshold value signal to be binarized, an error generated by binarization is distributed and added to neighboring pixels of the input pixel, and this addition is performed. The binarized multi-valued image signal is sequentially binarized as a new multi-valued image signal of the input pixel.

That is, the multi-valued image signal of the input pixel is I
(x, y) (where x is the position in the main scanning direction and y is the position in the sub scanning direction) If the binary image signal is P (x, y), the binarization error signal E (x, y) Is calculated as E (x, y) = I (x, y) -P (x, y) (1). Therefore, the binarization error signal E (x, y) of the equation (1) is diffused to neighboring pixels as I '(x, y) = I (x, y) + ΔE (x, y) (2) And is replaced with the multivalued image signal I ′ (x, y). Then, by comparing the replaced multi-valued image signal I ′ (x, y) with a predetermined threshold signal, 2
A value image signal P (x, y) is obtained. In the equation (2),

[0005]

[Equation 1]

And W (k, l) is the binarization error signal E
An error diffusion coefficient for diffusing (x, y) at a predetermined rate.

[0007]

By the way, in an image formed on the basis of a binary image signal obtained by the error diffusion method, the pixel density is multivalued in the entire density area from the highlight area to the shadow area. By controlling according to the signal, a halftone density is realized.

Here, for example, when a gradation image is formed using a laser beam printer, since the intensity of the laser beam has a Gaussian distribution, the density of the recorded image formed based on the binary image signal is the shadow area. , The image density becomes higher than the desired image density. That is, as shown by intensity characteristics A and B in FIG. 9, in the highlight region where the positions of the two beam spots are formed apart from each other on the recording medium, the beam intensity of the image recorded on the recording medium is A pixel having a width d is formed with a threshold value of TH. On the other hand, as shown by intensity characteristics C and D, in the shadow region where the positions of the two beam spots are formed close to each other, the beam spots overlap each other,
The width d'of the formed pixel is the width d of the pixel in the highlight region.
Will be larger than. As a result, the pixel spacing becomes narrower,
The image density in the shadow area becomes higher than the desired density.

On the other hand, when a printed matter consisting of a multi-valued image is created, a negative film (film original plate) of a binary image is once created from a multi-valued image in which characters and images are mixed, and then a return process is carried out to carry out a positive film. In some cases, a (return film) is obtained, and then a printing plate is created from the positive film, and a printed matter is created through the printing plate. In this case, when the return film is formed from the film original plate, the dot% of the image hardly changes in the entire density area (see FIG. 10). On the other hand, make a plate from the return film,
Further, in the step of producing a printed matter, the halftone dot% of the highlight area of the return film tends to decrease and the halftone dot% of the shadow area tends to increase. When making a printing plate,
This is because it is usual to determine the exposure conditions of the printing plate so as to erase dust and traces of sticking of the original at the time of plate collection, and therefore halftone dots having a small area in the highlight region are likely to disappear.
Further, when a printed matter is created from a printing plate, the density increases particularly in the shadow area of the printed matter due to the influence of dot gain caused by ink crushing, ink bleeding on a recording medium, and the like. FIG. 11 shows a change state of the dot% when a printed matter is produced from the return film through the printing plate.

In summary of the above tendency, when a printed matter is produced by using a return process, for example, when a film original is produced by a laser beam for a shadow area of the printed matter, that is, for the highlight side of the film original. , A large density variation does not occur with respect to the image indicated by the dotted line (FIG. 12A), and when a printed matter is produced using the return film produced from the film original plate (FIG. 12B), the dot gain Although the density of the shadow area increases due to the influence (FIG. 12C), the increase amount and the increase amount of the density of the highlight area at the time of making the film original plate cancel each other, and as a result, the density variation almost occurs. There is no. On the other hand, in the highlight area of the printed matter, that is, in the shadow side of the film original plate, a large density fluctuation occurs when the film original plate is formed (FIG. 13A).
Next, when a printing plate is made using the return film made from the film original plate (FIG. 13B), the printing plate printing conditions are set for the purpose of erasing dust and traces of original sticking as described above. Therefore, small halftone dots on the film disappear on the printing plate (FIG. 13C). Therefore, halftone dots are not formed even on the printed matter (FIG. 13D). Therefore, the gradation information of the highlight area on the printed matter is lost.

The present invention solves the above-mentioned problems, and in the entire density area from the highlight area to the shadow area,
It is an object of the present invention to provide an image signal binarization processing apparatus and method capable of reproducing a good gradation image having a desired density without causing moire or the like.

[0012]

To achieve the above object, the present invention compares an image signal with a predetermined threshold signal,
Binarization means for generating a binary image signal, error signal calculation means for obtaining an error signal by using the image signal and the binary image signal, and the error signal based on a predetermined error diffusion coefficient. Spread the image around the signal,
An image signal correction means for correcting the image signal, and information of the binary image signal corresponding to the already binarized pixel in the vicinity of the pixel corresponding to the binary image signal, using the binary image signal. And a binary image signal correcting means for correcting.

The present invention also comprises a first step of comparing the image signal with a predetermined threshold signal to generate a binary image signal,
A second step of obtaining an error signal using the image signal and the binary image signal, and based on a predetermined error diffusion coefficient,
A third step of diffusing the error signal with respect to an image signal around the image signal to correct the image signal, and a pixel already binarized in the vicinity of the pixel corresponding to the binary image signal. And a fourth step of correcting the binary image signal using the information of the binary image signal corresponding to.

Further, according to the present invention, the first binarizing means for comparing the image signal with a predetermined threshold signal to generate a binary image signal and the binary image signal correspond to the binary image signal. Using the information of the multi-valued image signal corresponding to the already multi-valued pixel in the vicinity of the pixel, the multi-valued conversion means for converting into a multi-valued image signal, the image signal and the multi-valued image signal Error signal calculating means for obtaining an error signal by using, and image signal correcting means for correcting the image signal by diffusing the error signal with respect to an image signal around the image signal based on a predetermined error diffusion coefficient. Second binarizing means for converting the multi-valued image signal into a binary image signal.

Further, according to the present invention, the first step of comparing an image signal with a predetermined threshold signal to generate a binary image signal, and the binary image signal in the vicinity of a pixel corresponding to the binary image signal. And a second step of converting into a multi-valued image signal using the information of the multi-valued image signal corresponding to the already multi-valued pixel, and an error signal using the image signal and the multi-valued image signal. And a fourth step of correcting the image signal by diffusing the error signal with respect to an image signal around the image signal based on a predetermined error diffusion coefficient.
And a fifth step of converting the multi-valued image signal into a binary image signal.

[0016]

In the image signal binarization processing apparatus and method of the present invention, when the image signal is converted into a binary image signal by the error diffusion method, non-recording is performed in the shadow area of the image formed from the binary image signal. By correcting the binary image signal corresponding to the recording pixel in the vicinity of the binary image signal corresponding to the pixel to the binary image signal corresponding to the non-recording pixel, the area of the non-recording pixel is increased and at the time of recording. An image having a desired density is formed by suppressing an increase in the density of the shadow area.

Further, according to the image signal binarization processing apparatus and method of the present invention, when the image signal is converted into the binary image signal by the error diffusion method, it is already in the vicinity of the pixel corresponding to the binary image signal. After generating a multi-valued image signal by using the information of the multi-valued image signal corresponding to the multi-valued pixel, the multi-valued image signal is converted into a binary image signal to obtain an image having a desired density. Form.

[0018]

1 shows the configuration of an error diffusion processing circuit 10 which is an image signal binarization processing apparatus of this embodiment.

The error diffusion processing circuit 10 includes a multi-valued image memory 12 for storing the multi-valued image signal I (x, y), a corrected multi-valued image signal I '(x, y) and a predetermined threshold signal. A comparator 14 (binarization means) for comparing TH with TH to generate a binary image signal P (x, y), and a binary image memory 16 for storing the binary image signal P (x, y). Binary image signal P (x, y-1) and binary image signals P (x, y-2) and P (x-1, y-1) related to surrounding pixels
, P (x + 1, y-1) based on the binary image correction signal P _cor (x, y)
Error using the correction signal generation circuit 18 (binary image signal correction means) for generating the corrected multi-valued image signal I ′ (x, y) and the binary image signal P (x, y). adding the signals E ₀ (x, y) subtracter 20 (the error signal calculation means) for obtaining the said error signal E ₀ (x, y) the relative binary image correction signal P _cor (x, y) and Adder 2 which obtains the modified error signal E (x, y)
2, an error memory 24 for storing the modified error signal E (x, y), and an error diffusion coefficient W for the error signal E (xk, yl).
A cumulative adder 26 that cumulatively adds (k, l), an error diffusion coefficient memory 28 that stores the error diffusion coefficient W (k, l), and a diffusion in which the error diffusion coefficient W (k, l) is cumulatively added. Error signal ΔE
and an adder 30 (image signal correction means) for adding (x, y) to the multivalued image signal I (x, y) before correction. In addition,
It is assumed that x is the position in the main scanning direction of the image, y is the position in the sub scanning direction of the image, and (k, l) represents the position of pixels around (x, y).

Next, the operation of the error diffusion processing circuit 10 having the above configuration will be described.

The multi-valued image signal I (x, y) is temporarily stored in the multi-valued image memory 12 and then corrected by adding a diffusion error signal ΔE (x, y) described later in the adder 30. The multi-valued image signal I ′ (x, y) is supplied to the comparator 14. The comparator 14 compares the multi-valued image signal I ′ (x, y) with a predetermined threshold signal TH to generate a binary image signal P (x, y). The multi-valued image signal I ′ (x, y) and the binary image signal P (x,
The relationship with y) is defined by the following equation (4).

[0022] The binary image signal P (x, y) output from the comparator 14
Is supplied to the subtracter 20, and the multi-valued image signal I ′ (x, y)
An error signal E ₀ (x, y) is obtained as a difference signal between the following.

E ₀ (x, y) = I ′ (x, y) −P (x, y) (5) In the calculation of the equation (5), for example, the multivalued image signal I ′
When (x, y) is 8-bit data, the binary image signal P (x,
y) As described above, the calculation is performed by converting into 8-bit data.

On the other hand, the binary image signal P (x, y) is temporarily stored in the binary image memory 16. Next, in the correction signal generation circuit 18, the binary image signal P (x, y-1) and the binary image signals P (x, y-2), P (x-
1, y-1), P (x + 1, y-1) based on the binary image signal P (x, y)
A binary image correction signal P _cor (x, y) for is obtained. This binary image correction signal P _cor (x, y) is, for example, as shown in FIG. 2, the binary image signal P (x, y-1) is 0,
Binary image signals P (x, y-2), P (x-1, y) related to the surrounding pixels
−1) and P (x + 1, y−1) are 1 respectively, the binary image signal P (x, y) is forcibly set to 0. That is, by forcibly setting the binary image signal P (x, y) adjacent to the binary image signal P (x, y-1) corresponding to the shadow area in which the surrounding pixels are 1 to 0, non-recording is performed. The pixel range will be expanded as described below. In this case, the binary image correction signal P _cor (x, y) is added to the error signal E ₀ (x, y) in the adder 22 and stored in the error memory 24 as the correction error signal E (x, y). To be done. The modified error signal E (x, y)
From the relationship of the equation (5), E (x, y) = E ₀ (x, y) + P _cor (x, y) = I ′ (x, y) −P (x, y) + P _cor (x , y) (6), the binary image correction signal P _cor (x, y)
Is P _cor (x, y) = 1 (P (x, y-2) = P (x-1, y-1) = P (x + 1, y-1) = P (x, y) = 1, P (x, y-1) = 0) 0 (conditions other than the above) ... (7)

Next, the error signal E (xk, yl) stored in the error memory 24 is cumulatively added to the error diffusion coefficient W (k, l) stored in the error diffusion coefficient memory 28 in the cumulative adder 26. And the diffusion error signal ΔE (x,
y) is obtained.

[0026]

[Equation 2]

The error diffusion coefficient W (k, l) obtained as described above is stored in the error diffusion coefficient memory 28,
In the cumulative adder 26, the error signal E (xk, yl) from the error memory 24 is cumulatively added to obtain the diffusion error signal ΔE (x, y) shown in the equation (8). Diffusion error signal ΔE (x, y)
Is added to the multi-valued image signal I (x, y) in the adder 30 to obtain the corrected multi-valued image signal I ′ (x,
y) is obtained.

I ′ (x, y) = I (x, y) + ΔE (x, y) (9) The corrected multi-valued image signal I ′ (x, y) has a threshold value in the comparator 14. The binary image signal P (x, y) is compared with the signal TH.
Is output as

The binary image signal P obtained as described above
Based on (x, y), for example, when a film original plate composed of a negative film of a binary image is created, a binary image signal P (x,
Since the error y) is diffused to surrounding pixels based on the diffusion error signal ΔE (x, y), a binary image without texture is obtained. Further, when the error of the binary image signal P (x, y) is diffused to the surrounding pixels, as shown in FIG. 2, the pixels adjacent to the non-recorded pixels in the shadow area of the film original plate are forcibly set to the non-recorded pixels. By doing so, it is possible to enlarge the non-recording area, thereby canceling out the influence of the enlargement of the recording pixels by the laser beam or the like as shown in FIG. 9, and it is possible to generate a binary image having a desired density. Furthermore, a good image can be obtained even when a printed matter is produced from the film original plate thus produced.

FIG. 3 shows the configuration of another embodiment of the image signal binarization processing apparatus according to the present invention. In the error diffusion processing circuit 50 shown in this embodiment, the binary image signal P (x, y) output from the comparator 14 is output to the correction signal generation circuit 52 in the modified signal generation circuit 52.
According to the following conditions, the multilevel image signal L (x, y) of K level (K ≧ 3) is corrected. The correction signal generation circuit 5
2, the binary image signal P (x, y) relating to the pixel of interest and the multi-valued image signal L relating to the surrounding pixels of the binary image signal P (x, y).
From (x, y), the multi-valued image signal L (x, y) relating to the pixel of interest is obtained based on the conditions of FIGS. 4A to 4C and other conditions.

That is, for example, when K = 5, in the correction signal generation circuit 52, when the multi-valued image signal L (x, y) relating to the pixels around the target pixel indicated by * is shown in FIG. 4A. , In the case shown in FIG. 4B, In the case shown in FIG. 4C, And in all other cases, The conversion process is performed. It should be noted that this conversion process can be performed using a lookup table.

Next, the multi-valued image signal L (x, y) obtained as described above is processed by the signal level adjusting circuit 56.
The multi-valued image signal I ′ (x, y) is converted into a multi-valued image signal L ′ (x, y) having the same gradation. That is, the multivalued image signal I ′
When (x, y) is 8-bit data, the multi-valued image signal L '
(x, y) is Is converted into 8-bit data and supplied to the subtractor 20. The multi-valued image signal L ′ (x, y) can be set to a conversion value for each multi-valued image signal L (x, y) according to the dot gain, output characteristics, etc. In the case of the equation 14), it is set corresponding to FIGS. 5A to 5E.

In the subtractor 20, the difference between the multi-valued image signal I '(x, y) and the multi-valued image signal L' (x, y) is obtained as a modified error signal E '(x, y). The signal is stored in the error memory 24. Modified error signal E ′ stored in the error memory 24
(xk, yl) is cumulatively added with the desired error diffusion coefficient W ′ (k, l) stored in the error diffusion coefficient memory 28 in the cumulative adder 26 to obtain a diffusion error signal ΔE ′ (x, y). Adder 3
0 is supplied.

The diffusion error signal ΔE '(x, y) is added to the adder 3
At 0, the multi-valued image signal I (x, y) is added and the next (1
The corrected multi-valued image signal I ′ (x, y) shown in the equation (5) is obtained.

I ′ (x, y) = I (x, y) + ΔE ′ (x, y) (15) The corrected multi-valued image signal I ′ (x, y) is supplied to the comparator 14. The binary image signal P (x, y) is compared with the threshold signal TH.
After being output as, the converted signal is converted into a multi-valued image signal L (x, y) in the correction signal generation circuit 52.

On the other hand, the multi-valued image signal L (x, y) generated as described above is stored in the multi-valued image memory 54 and then, in the binarization circuit 58, the binary image signal P '( i, j) and stored in the binary image memory 16. In this case, in the binarization circuit 58, as shown in FIGS. 5A to 5E and the following equation (16), the multi-valued image signal L (x, y) is 4
Two binary image signals P ′ (i, j), P ′ (i + 1, j), P ′ (i, j + 1),
It is converted into P ′ (i + 1, j + 1).

P ′ (i, j) = P ′ (i + 1, j) = P ′ (i, j + 1) = P ′ (i + 1, j + 1) = 0 (L (x, y ) = 0) P '(i, j) = P' (i + 1, j) = 0, P '(i, j + 1) = P' (i + 1, j + 1) = 1 (L ( x, y) = 1) P '(i, j) = P' (i, j + 1) = 0, P '(i + 1, j) = P' (i + 1, j + 1) = 1 (L (x, y) = 2) P '(i, j) = 0, P' (i, j + 1) = P '(i + 1, j) = P' (i + 1, j + 1 ) = 1 (L (x, y) = 3) P '(i, j) = P' (i + 1, j) = P '(i, j + 1) = P' (i + 1, j + 1) = 1 (L (x, y) = 4) (16) Binary image signals P ′ (i, j), P ′ (i +
1, j), P '(i, j + 1), P' (i + 1, j + 1), a film original plate made of a negative film of a binary image is created, for example, as shown in FIG. 6A. Multi-valued image signal L (x,
Since the non-recording area M of y) is expanded to the non-recording area (M + m) as shown in FIG. 6B, the expansion of pixels at the time of recording by a laser beam or the like as shown in FIG. A binary image composed of densities can be generated.

For example, as shown in FIG. 7A, when the desired recording area of the original multi-valued image is defined by the dotted line a1, the binary image signal P'generated by the error diffusion processing circuit 50 is obtained.
The non-recorded area of (x, y) is enlarged to become a dotted line a2. Therefore, when a film original plate is created by using this modified binary image signal P ′ (x, y), the shadow area of the non-recorded area is affected by the expansion of pixels at the time of recording by the laser beam or the like. The boundary is a solid line b between the dotted line a1 and the dotted line a2. The original film is returned and processed as shown in FIG. 7B.
When a return film shown in Fig. 7 is obtained, and then a printing plate is created from the return film, the recording area is reduced as shown in Fig. 7C, and the recording range is slightly smaller than the dotted line a1 of the recording area of the original multi-valued image. Becomes Then, when a printed matter is created using the printing plate, as shown in FIG. 7D, the recording range is expanded due to the influence of the dot gain, and a recording region approximately equal to the recording region of the original multi-valued image is obtained. You can It should be noted that the shadow area of the multi-valued image is hardly affected by the density variation, as described in the related art shown in FIGS. 12A to 12C. As a result, it is possible to obtain a good 2
A value image can be obtained.

As shown in FIG. 8, for the recording area N of the multivalued image signal L (x, y) in the highlight area, (1
Since the expression (3) is applied, the binary image having the density corresponding to the multi-valued image signal I (x, y) is generated without being enlarged.

[0040]

As described above, in the image signal binarization processing apparatus and method of the present invention, when the image signal is binarized by the error diffusion method, the shadow area of the image formed from the binary image signal is obtained. In, the binary image signal corresponding to the recording pixel adjacent to the binary image signal corresponding to the non-recording pixel is corrected to the binary image signal corresponding to the non-recording pixel, thereby increasing the area of the non-recording pixel. Therefore, it is possible to offset the increase in the shadow area during recording and obtain an image with a desired density. It should be noted that such a process is not necessary for the highlight area because there is little fluctuation during recording. Therefore, it is possible to obtain an image having good density without texture or moire in the entire density region.

Further, when converting an image signal into a binary image signal by the error diffusion method, a multi-valued image signal corresponding to a pixel which is already multi-valued in the vicinity of the pixel corresponding to the binary image signal is converted. By generating a multi-valued image signal using the information and then converting the multi-valued image signal into a binary image signal, it is possible to form a good image having a desired density in the same manner as described above.

[Brief description of drawings]

FIG. 1 is a configuration block diagram of an error diffusion processing circuit to which an image signal binarization processing device according to the present invention is applied.

FIG. 2 is an explanatory diagram of a binary image signal corrected by a correction signal generation circuit shown in FIG.

FIG. 3 is a configuration block diagram of another embodiment of an error diffusion processing circuit to which the image signal binarization processing device according to the present invention is applied.

4A to 4C are explanatory views of a multi-valued image signal generated in the correction signal generation circuit shown in FIG. 3, respectively.

5A to 5E are explanatory diagrams of a binary image signal generated in the binarizing circuit shown in FIG.

6A and 6B are a multi-valued image signal in a shadow region generated in the correction signal generation circuit shown in FIG. 3 and a binary image generated in a binarization circuit based on the multi-valued image signal. It is explanatory drawing of a signal.

7A to 7D are respectively a binary image on the shadow side of the film original plate created based on the binary image signal generated in the error diffusion processing circuit shown in FIG. 1, and the binary image is inverted. FIG. 6 is an explanatory diagram of a return image, an image of a printing plate created from the return image, and an image of a printed matter created from the image of the printing plate.

8 is an explanatory diagram of a binary image signal generated in a binarization circuit based on a multivalued image signal in a highlight region generated in the correction signal generation circuit shown in FIG.

FIG. 9 is an explanatory diagram of a relationship between a recording position of a laser beam and a recording area.

FIG. 10 is a diagram for explaining the relationship between the net% of the film original plate and the net% of the return film obtained from the net%.

FIG. 11 is a diagram for explaining the relationship between the net% of the return film and the net% of the printed matter obtained from the return film through a printing plate.

12A to 12C are binary images on the highlight side of a film original obtained in the related art,
It is explanatory drawing of the binary image by the side of the shadow of the return film obtained from the said binary image, and the binary image by the side of the shadow of the printed matter obtained from the said return film.

13A to 13D are binary images on the shadow side of a film original obtained in the related art, a binary image on the highlight side of a return film obtained from the binary image, and the return, respectively. It is explanatory drawing of the binary image on the highlight side of the printing plate obtained from the film, and the binary image on the highlight side of the printed matter obtained from the said printing plate.

[Explanation of symbols]

10, 50 ... Error diffusion processing circuit 12, 54 ... Multi-valued image memory 14 ... Comparator 16 ... Binary image memory 18, 52 ... Correction signal generation circuit 24 ... Error memory 26 ... Cumulative adder 28 ... Error diffusion coefficient memory 56 ... Signal level adjusting circuit 58 ... Binarizing circuit

Continuation of front page (51) Int.Cl. ⁶ Identification code Office reference number FI Technical display area H04N 1/40 B

Claims (4)

[Claims] 1. A binarizing means for comparing an image signal with a predetermined threshold signal to generate a binary image signal, and an error signal calculating means for obtaining an error signal using the image signal and the binary image signal. And an image signal correction means for correcting the image signal by diffusing the error signal with respect to an image signal around the image signal based on a predetermined error diffusion coefficient, and a pixel corresponding to the binary image signal. Already in the neighborhood and already 2
An image signal binarization processing device comprising: a binary image signal correction unit that corrects the binary image signal using information of the binary image signal corresponding to the binarized pixel. 2. A first step of comparing an image signal with a predetermined threshold signal to generate a binary image signal, and a second step of obtaining an error signal using the image signal and the binary image signal. A third step of correcting the image signal by diffusing the error signal with respect to an image signal around the image signal on the basis of a predetermined error diffusion coefficient; Already 2
A fourth step of correcting the binary image signal by using information of the binary image signal corresponding to the binarized pixel, and the image signal binarizing method. 3. A first binarizing means for comparing an image signal with a predetermined threshold signal to generate a binary image signal; and the binary image signal in the vicinity of a pixel corresponding to the binary image signal. And using the information of the multi-valued image signal corresponding to the already multi-valued pixel, multi-valued conversion means for converting into a multi-valued image signal, an error using the image signal and the multi-valued image signal An error signal calculating means for obtaining a signal; an image signal correcting means for correcting the image signal by diffusing the error signal with respect to an image signal around the image signal based on a predetermined error diffusion coefficient; An image signal binarization processing device comprising: a second binarization unit that converts an image signal into a binary image signal. 4. A first step of comparing an image signal with a predetermined threshold signal to generate a binary image signal, the binary image signal being already in the vicinity of a pixel corresponding to the binary image signal. A second step of converting into a multi-valued image signal using information of the multi-valued image signal corresponding to the multi-valued pixel, and a third step of obtaining an error signal using the image signal and the multi-valued image signal A step of diffusing the error signal with respect to an image signal around the image signal based on a predetermined error diffusion coefficient, and correcting the image signal; and a step of converting the multi-valued image signal into a binary image signal. An image signal binarization processing method comprising: