JP2000242779A - Image processor and image processing method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To make preventible a noise isolated at a part whose density is flat from being regarded as an edge and being emphasized corrected. SOLUTION: An edge judging part 20 sets an image area including an attentional pixel in the neighborhood of the attentional pixel and judges whether a pixel group included in the image area can be divided or not into a set of pixel groups having large density values and a set of pixel groups having small density values. Next, it judges whether the attentional pixel is included or not in the pixel groups having large density values when the pixel groups can be divided into the set of the pixel groups having large pixel values and the set of the pixel groups having small density values. When the attentional pixel is judged to be included in the pixel groups having large density values, an edge emphasizingly processing part 30 performs edge emphasizing correction of the density value of the attentional pixel.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus and an image processing method for highlighting an edge drawing portion in a gradation image.

[0002]

2. Description of the Related Art Conventionally, in the technical field of processing an image signal, in order to improve the image quality by sharpening a portion corresponding to an outline in an image, a density value of a pixel in an edge drawing portion is corrected and emphasized. Display processing is being performed. For this image processing, a two-dimensional filter is used. The two-dimensional filter includes, for example, a 3D filter for correcting the density value of the pixel of interest.
It is composed of a parameter group in the row 3 column.

The product of the 3 × 3 parameters of the two-dimensional filter and the density values of the 3 × 3 pixels centered on the target pixel is calculated, and the sum of the results is the corrected density of the target pixel. Value. When the value of the parameter is appropriately selected, when the density value of the target pixel is larger than the density value of the peripheral pixel, the density value of the target pixel is corrected so as to be larger, and the density value of the target pixel is larger than the density value of the peripheral pixel. When it is smaller, the correction is performed so that the density value of the target pixel becomes smaller. When the density value of the target pixel is equal to the density value of the peripheral pixel, the density value is not corrected. Such a technique related to edge enhancement correction is introduced in, for example, “Digital Signal Processing of Images, written by Takahiko Fukibuki, page 113 of Nikkan Kogyo Shimbun”.

[0004]

However, the above-mentioned prior art has the following problems to be solved. The density value of the target pixel is equal to the density value of the peripheral pixel when the target pixel exists in a background having a flat density in the image. However, noise may be mixed in such a flat portion of the density. When the noise is used as a pixel of interest and the processing is performed by the two-dimensional filter, there is a problem that the density value of the noise is corrected and emphasized. Therefore, it is necessary to execute the edge enhancement correction after determining whether or not the target pixel is noise.

[0005]

The present invention employs the following structure to solve the above problems. <Structure 1> An image region including the target pixel is set near the target pixel, and a pixel group included in the image region is set as follows:
It is determined whether the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value. If the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value, An edge determination unit that determines whether a pixel is included in the pixel group having the large density value; and an edge determination unit that determines that the pixel of interest is included in the pixel group having the large density value. An image processing apparatus comprising an edge enhancement processing unit that performs edge enhancement correction on the density value of the image.

<Structure 2> In the image processing apparatus described in Structure 1, each pixel is sequentially read from an input image, and
An entry / exit state detection unit that calculates a density difference between the target pixel and a pixel adjacent to the target pixel and requests the edge determination unit to perform an edge determination process on the target pixel when the density difference is equal to or greater than a certain threshold value An image processing apparatus characterized in that:

<Structure 3> An image area including the pixel of interest is set near the pixel of interest, and the pixel group included in the image area is divided into a pixel group having a large density value and a pixel group having a small density value. It is determined whether or not the pixel group can be classified. If the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value, it is determined whether or not the pixel of interest is included in the pixel group having a large density value. An image processing method, comprising: performing edge enhancement correction on a density value of a target pixel when it is determined that the target pixel is included in the pixel group having a large density value.

<Structure 4> In the image processing method according to Structure 3, each pixel is sequentially read from the input image, and
An image processing method comprising: calculating a density difference between a target pixel and a pixel adjacent to the target pixel; and requesting edge determination processing for the target pixel when the density difference is equal to or greater than a predetermined threshold.

<Structure 5> An image area including the target pixel is set near the target pixel, and the pixel groups included in the image area are divided into a pixel group having a large density value and a pixel group having a small density value. It is determined whether or not the pixel group can be classified. If the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value, it is determined whether or not the pixel of interest is included in the pixel group having a large density value. A computer-readable recording medium which stores a computer program for executing a process of performing edge enhancement correction on a density value of a target pixel when determining that the target pixel is included in the pixel group having a large density value.

[0010]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Embodiments of the present invention will be described below using specific examples. <Example 1> FIG. 1 is a block diagram of an image processing apparatus according to Example 1. This apparatus performs an edge enhancement process on an input image stored in an input image memory 11 and
2 has the function of outputting to Therefore, the edge determination unit 2
0, an edge enhancement processing unit 30 and an operation table 31 are provided. The edge determination unit 20 includes a region setting unit 21,
Average density value calculation unit 22, density difference calculation unit 23, low density pixel count unit 24, threshold value calculation unit 25, and comparison determination unit 26
It consists of.

The area setting section 21 of the edge judging section 20 is a section for performing processing for reading each density value in a predetermined image area from the input image memory 11. The image area is an area set so that the target pixel is included in the vicinity of the target pixel.
For example, it is an area composed of 3 × 3 pixels centered on the pixel of interest. Based on the density value of each pixel included in this image area, it is determined whether or not to perform edge enhancement processing on the target pixel. When performing edge enhancement processing, the edge enhancement processing unit 30 performs processing using a two-dimensional filter. When the edge enhancement processing is unnecessary, the density value of the target pixel is directly output to the output image memory 12. The edge determination unit 20 performs this processing for all pixels included in the input image.

The average density value calculating section 22 is a section for accumulating the density values of all the pixels included in the set image area and obtaining the average value. The low-density pixel count section 24 includes:
This is a part that compares the average density value with the density value of each pixel and counts the number of pixels lower than the average density value. Note that pixels having a density value equal to the average density value are counted as 0.5 pixels and the number of pixels is counted. The density difference calculator 23 is a part that calculates the difference between the density value of the target pixel and the average density value.

The threshold value calculating section 25 calculates the
This is a part for calculating a threshold value for determining whether or not the target pixel is a pixel at the edge portion. The comparison determination unit 26 compares the threshold value output from the threshold value calculation unit 25 with the density difference output from the density difference calculation unit 23, and pays attention to the edge enhancement processing unit 30 when the density difference is larger than the threshold value. This is a part for performing processing for outputting the density value of the pixel, and otherwise outputting the density value of the pixel of interest to the output image memory 12.

FIG. 2 is a diagram for explaining an example of the density distribution in the image area. The operation principle of the present invention will be schematically described with reference to FIG. First, consider a case where the input image shows a relatively flat density distribution in the image area 1 as shown in FIG. The density values of each pixel are distributed almost uniformly around the average density value A. The horizontal axis in the figure is the density value of each pixel,
The vertical axis indicates the number of pixels having the same density value.
(B) shows a case where an edge exists in the image area 1. The display of the horizontal axis and the vertical axis is the same as in (a).

In both cases (a) and (b), the pixel group included in the image area 1 is divided into a pixel group having a higher density value than the average density value A and a pixel group having a lower density value. When the target pixel is included in a pixel group having a large density value, a difference between the density value of the target pixel and the average density value A is obtained. In the case of (a), the difference is small. In the case of (b), the difference is relatively large. Therefore, in the case of (b), it is determined that the target pixel is on the edge. In the case of (a), the edge enhancement correction is not performed.
This is because, in the case of (a), the pixel of interest is likely to be noise.

The calculation table 31 shown in FIG. 1 is used for calculation processing when the edge enhancement processing unit 30 performs edge enhancement correction on a target pixel. This is data of a conventionally well-known two-dimensional filter. The specific configuration will be described later with reference to FIG. Output image memory 12
Stores an image of the corresponding portion that has been subjected to edge enhancement correction. The data stored in the output image memory 12 is thereafter output to another device (not shown).

FIG. 3 is a flowchart showing the operation of the image processing apparatus according to the first embodiment. First, in step S1,
The area setting unit 21 shown in FIG.
The address signal (pixel position P (i, j)) for sequentially setting each pixel stored in the pixel as a target pixel is input. The parameters i and j of the pixel position P (i, j) are sequentially incremented in steps S7 and S9. In step S2, an edge determination process is performed. Here, the processing of the edge determination unit 20 shown in FIG. 1 is executed. Then, the determination whether the pixel of interest is an edge component is made by the comparison determination unit 26 shown in FIG. The details will be described later with reference to FIG.

If it is determined that the component is an edge component, the process proceeds to step S4, where the edge emphasis processing unit 30 shown in FIG.
Performs edge enhancement correction. In step S5, the result is stored in the output image memory 12. Steps S6 and S7 are processes for sequentially shifting the target pixel in the line direction of the input image. Steps S8 and S9 are processes for sequentially switching the line including the target pixel to the next line.

FIG. 4 shows a flowchart of the edge determination process. First, in step S11, an image area is set. This image area is, for example, an area configured by a pixel group of 3 × 3 pixels. In step S12, an average density value of the pixel group is calculated. And step S
At 13, the density difference between the density value of the pixel of interest and the average density value is determined.

Next, in step S14, the number of pixels CNT having a low density value is counted. That is, the number of pixels having a density value lower than the average density value is counted. Then, in step S15, a threshold Th is calculated. The threshold Th is obtained by the following equation. Th = (CNT / N) × Δd Here, Δd is an optimum value obtained by an experiment. The reason for setting the threshold in this way is as follows.

First, in the case where the pixel of interest is noise,
When only the density value of the target pixel is higher than the density values of the peripheral pixels, the CNT becomes larger. CNT is the number of pixels whose density value is smaller than the average density value. N is the total number of pixels included in the image area. Therefore, Th is a sufficiently large value in this case. Therefore, the difference between the average density value and the density value of the target pixel does not exceed Th. Therefore, the pixel of interest is not emphasized.

If the pixel of interest is noise and the density value of the pixel of interest is smaller than the density values of the surrounding pixels,
Since CNT takes a sufficiently small value, the threshold Th becomes small. However, the density difference obtained by subtracting the average density value from the density value of the target pixel is a negative value. Therefore, also in this case, the density difference becomes equal to or smaller than the threshold, and the pixel of interest is not emphasized.

On the other hand, when the target pixel exists at the edge and the density of the target pixel is higher than the average density value, the density difference obtained by subtracting the average density value from the target pixel becomes larger than the threshold value Th. Therefore, it becomes a target of edge enhancement correction. If the target pixel is at the edge and the target pixel is included in a pixel group having a lower density value than the average density value, subtracting the average density value from the density value of the target pixel results in a negative value. In this case, since the density difference is smaller than the threshold Th, it is not targeted for edge enhancement. The reason why the edge enhancement correction is not performed when the target pixel is included in a pixel group having a density value lower than the average density value is that the edge enhancement correction is performed only when the target pixel is included in a pixel group having a density value higher than the average density value. Is sufficient because the edge enhancement correction is more effective when the density value is increased.

According to the above-described principle, for example, in the case of a black-and-white image, a pixel at a boundary portion between a black image and a white image and corresponding to an edge of the black image has a slightly larger density value. Is corrected so that appropriate edge enhancement can be performed. Similarly, the color image is corrected so that the pixel corresponding to the edge of the image having a large density value has a slightly larger density value.

Referring back to FIG. 4, in step S16,
The density difference is compared with the threshold, and if the density difference is larger than the threshold, the process proceeds to step S17, where it is determined that the pixel of interest is an edge component. Otherwise, it is determined that the target pixel is not an edge component. In this way, when it is determined that the target pixel is an edge component, edge enhancement correction is performed.

FIG. 5 is an explanatory diagram of an operation example of the first embodiment. (A) of the figure shows an example of the content of the image area 1a, in which five pixels with a density value of 120 and four pixels with a density value of 30 exist. Here, first, when the average density value in step S12 of FIG. 4 is calculated, 120 × 5 and 30 × 4
And a value obtained by dividing by 9 pixels. This value is 80. The number of pixels having a density value smaller than 80 is four in this case. Therefore, the threshold Th is (4/9) × 60, and the threshold Th is 27. At this time, Δd is set to, for example, 60. Here, the density value of the target pixel is 1
20 and the average density value is 80, so the density difference is 40. When this density difference is compared with the threshold Th, the density difference is larger. Therefore, edge enhancement correction is performed on the target pixel.

In the image area 1b shown in (b), the pixel of interest at the center is an example of noise. Also in this case, when the same calculation processing as in (a) is performed, the average density value is a value obtained by adding 10 × 8 and 30 × 1 and dividing this by 9. Therefore, the average density value is 12. The number of pixels whose density value is smaller than the average density value is eight. Therefore, the threshold value Th is (8/9) × 6
0, that is, 53. Since the density value of the target pixel is 30 and the average density value is 12, the density difference is 18. This is smaller than the threshold Th. Therefore, no edge enhancement correction is performed. In this way, the edge emphasis correction of the pixel corresponding to the noise, which is the object of the present invention, is eliminated.

FIG. 6 shows an example of the horizontal and vertical emphasis two-dimensional filter. (A) is the general form, for example, FIG.
Parameters h and 1 + 8h are set so as to correspond to each pixel of the image area 1a shown in FIG. h is a parameter for edge enhancement correction, and an appropriate value is selected according to the situation.

For example, if h is set to 0.2, as shown in FIG.
At 6, the portion corresponding to the peripheral pixels is -0.2. Multiply the density value of the pixel of interest by the numerical value 2.6 at the center of the figure,
When the peripheral pixels are multiplied by −0.2 and the results are cumulatively added, the result D (19) is obtained by the equation shown in FIG.
2) is obtained. The result D is set as the corrected density value of the target pixel. The handling of such a two-dimensional filter is the same as in the prior art. Performing this processing in the edge enhancement processing unit 30 shown in FIG. 1 enables necessary edge enhancement. The processing described above is for graphic images,
The same can be realized not only for a bitmap image or a monochrome image but also for a color image.

<Effect of Specific Example 1> As described above, each pixel in the image area including the target pixel is divided into a pixel group having a high density value and a pixel group having a low density value. Since it is determined whether or not the pixel is included in a large pixel group and the density value of only the edge-constituting pixels is corrected, it is possible to prevent an operation of erroneously enhancing a noise or an image of a portion other than an edge. As a result, a high-quality output image can be obtained.

<Specific Example 2> In the above-described example, edge determination is sequentially performed for all pixels in the input image, and edge enhancement correction is performed as necessary. However, if the above-described arithmetic processing is performed on all pixels, the amount of arithmetic processing becomes enormous and an arithmetic processing load increases in the case of an image having a large resolution. Therefore, in this specific example, it is determined in advance whether the pixel of interest is a pixel for which edge determination is to be performed, and the processing of the specific example 1 is performed only on a necessary pixel.

FIG. 7 is a block diagram of an image processing apparatus according to the second embodiment. This device includes an entry / exit state detection unit 40 that reads out and processes a target pixel from the input image memory 11. The output of the entry / exit state detection unit 40 is input to the edge determination unit 20 described using the first specific example. Other configurations of the operation table 31, the edge enhancement processing unit 30, and the output image memory 12 are the same as those in the first embodiment.

The entering / leaving state detecting section 40 includes a target pixel reading section 41, a density difference detecting section 42, a state determining section 43, and a state flag 44. Attention pixel readout unit 41
Has a function of sequentially reading out each pixel stored in the input image memory 11 and outputting the density value of the pixel of interest and the pixel immediately before the pixel of interest to the density difference calculation unit 42. The density difference calculation unit 42 is a part that calculates the density value of the target pixel and the density difference of the pixel immediately before the target pixel, that is, the pixel on the left side of the target pixel.

The state judging section 43 judges whether the density difference is equal to or larger than a certain threshold value. Otherwise, the pixel of interest is not subjected to edge determination processing, and the density value is output to the output image memory 12.
Transfer to At a predetermined timing during these operations, the state determination unit 43 sets a state flag 44 described later, and the operation of the entry / exit state detection unit 40 is performed in response thereto.

FIG. 8 is a diagram for explaining an example of approach / exit determination.
If there is an input image as shown in FIG. 8A, the density values are examined in order from the left pixel, and the density difference between two adjacent pixels including the target pixel is obtained. For example, if the target pixel is a black pixel and the left pixel is a white pixel, it is determined that the pixel of interest has entered the image drawn in black from the white background image side. In this case, the target pixel is determined to be a pixel to be edge-determined, and the pixel value is output to the edge determination unit. When the pixel of interest is a white pixel and the pixel on the left is a black pixel, it is determined that the image has drawn out of the image drawn in black toward the white background image. Again, in this case,
The pixel of interest is determined to be a pixel to be edge-determined, and the pixel value is output to the edge determination unit.

When the target pixel is on the background image side, the flag value is set to "0". Then, when the target pixel enters the drawing area from the background image side, the flag value is set to “0”.
From "1" to "1". Therefore, for example, when the target pixel moves from the position (1) to the position (2) in the figure, the flag value is changed from “0” to “1”. When the pixel of interest moves from the position (7) to the position (8) in the figure, the flag value is changed from “1” to “0”. The flag value of the status flag is handled in this way.

FIG. 8 (b) shows an example of a criterion for determination using a flag value, in which the position of the immediately preceding pixel of interest is on the outside, that is, on the background area side, and the density of the current pixel of interest is If the value is small, the target pixel is still on the background area side and is not subjected to edge determination. If the previous pixel of interest is located outside, that is, on the side of the background area, and the density value of the current pixel of interest is large, it is determined that the pixel of interest has entered the drawing area from the background image side. Therefore, the target pixel is set as a target of the edge determination processing. Note that whether the density value is large or small is determined by comparing with a predetermined threshold value.

If the position of the immediately preceding pixel of interest is inside, that is, in the drawing area, and if the current density value of the pixel of interest is small, it is determined that the pixel has retreated from the drawing area to the background image side. Therefore, the target pixel is set as a target of the edge determination processing.
If the position of the previous pixel of interest is inside, that is, in the drawing area, and the density value of the current pixel of interest is large, it is determined that the pixel of interest is still in the drawing area, and the pixel of interest is set to the edge. Not subject to judgment processing.

FIG. 9 is a flowchart showing the operation of the image processing apparatus according to the second embodiment. First, in step S21, the pixel position P (i, j) of the target pixel is input to the target pixel reading unit 41 illustrated in FIG. As a result, the corresponding pixel in the input image memory is read as the target pixel. Then, the density value of the pixel on the left side of the pixel is also read. In step S22, a determination process of the approach state is performed. This will be described later in detail with reference to FIG.

In the next step S23, the process branches according to the result of the determination as to whether the target pixel is in the entering state or the leaving state. If it is the entry state or the exit state, step S2
Proceed to 4. Then, the edge determination processing described using the first specific example is performed, and in step S25, it is determined whether the pixel of interest is an edge component. If it is an edge component, the process proceeds to step S26, where edge enhancement processing is performed.

Then, the process proceeds to step S27,
The output image is stored. Step S28 and Step S2
9 is a process for sequentially shifting the target pixel in the line direction of the input image. Steps S8 and S9 are processes for sequentially switching the line including the target pixel to the next line.

FIG. 10 shows a flowchart of the approach state determination processing. First, in step S41, the density value d (i, j) of the target pixel and the density value d (i-1, j) of the pixel immediately before it, that is, the left pixel, are read. And
In step S42, it is determined whether the flag is "0". If the flag is “0”, the target pixel is as shown in FIG.
And the target pixel is inside unless the flag is “0”.

In step S43, the difference between the density value of the pixel of interest and the pixel on the left side is calculated. Step S4
At 4, it is determined whether or not the difference between the density values is larger than a predetermined threshold. If the value is larger than the predetermined threshold value, the entry state has already been described, and the flag is changed from “0” to “1”.
Then, in step S46, it is determined that the vehicle is approaching. That is, as a result of this determination, the process proceeds to step S24 in FIG.

On the other hand, if it is determined in step S42 that the inside is inside, the process proceeds to step S47, and similarly, a difference in density value is calculated, and in step S48, comparison with a threshold value is performed. In this case, subtraction is performed in the reverse order of step S44 in order to determine whether or not the concentration difference is equal to or more than the predetermined value because the exit is from the inside to the outside.

In step S49, the flag is changed from "1" to "0" in the case of the leaving state according to the result of this determination. Then, in step S50, it is determined that the vehicle is in the leaving state,
The process proceeds to step S24 in FIG. Step S44,
If the difference between the density values is not larger than the threshold value in step S48, since the edge enhancement correction is not necessary, FIG.
The control proceeds to step S27. Other processes are the same as those in the first embodiment.

In the above description, the change of the pixel value of the target pixel is examined in the direction along the line to determine the approach state and the exit state, and a pixel to be subjected to edge determination is selected. However, as shown in FIG. 8A, if a similar determination is made in a direction perpendicular to the line, it is possible to select a pixel to be subjected to edge determination when viewed in this direction. Also, based on the result of the above-described pixel selection, data specifying a pixel to be subjected to edge determination in an input image is generated and temporarily stored in a buffer memory, and thereafter, edge determination processing is started. It may be.

The present invention as described above can be realized by a program for controlling a computer for image processing. The functional blocks in each block diagram can be configured by modules for executing programs. All of these can be stored in a storage medium such as a flexible disk or a hard disk, and installed and executed in an information processing apparatus.

<Effect of Specific Example 2> In this example, it is determined whether the pixel of interest is a pixel at the entry position, a pixel at the exit position, or any other pixel. Is controlled not to be the target pixel of the edge determination unit, so that the edge enhancement processing can be performed efficiently and at high speed. Such a device as described above can be widely used, for example, in a printer, for example, in pre-processing for maintaining the resolution of an edge portion, prior to binarization processing for reproducing a gradation image in a pseudo manner.

[Brief description of the drawings]

FIG. 1 is a block diagram of an image processing apparatus according to a specific example 1.

FIG. 2 is an explanatory diagram of an example of a density distribution in an image area.

FIG. 3 is an operation flowchart of the image processing apparatus according to the first embodiment.

FIG. 4 is a flowchart of an edge determination process.

FIG. 5 is an explanatory diagram of an operation example of a specific example 1.

FIG. 6 is an explanatory diagram of an example of a horizontal / vertical emphasis two-dimensional filter.

FIG. 7 is a block diagram of an image processing apparatus according to a specific example 2.

FIG. 8 is an explanatory diagram of an example of entry / exit determination.

FIG. 9 is an operation flowchart of the image processing apparatus according to the second embodiment.

FIG. 10 is a flowchart of an approach state determination process.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 11 Input image memory 12 Output image memory 20 Edge determination part 21 Area setting part 22 Average density value calculation part 23 Density difference calculation part 24 Low density pixel count part 25 Threshold calculation part 26 Comparison judgment part 30 Edge enhancement processing part 31 Calculation table

Claims (5)

[Claims] 1. An image region including a pixel of interest in the vicinity of the pixel of interest is set, and a group of pixels included in the image region can be divided into a pixel group having a high density value and a pixel group having a low density value. If the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value, it is determined whether the pixel of interest is included in the pixel group having a large density value. An edge determination unit; and an edge enhancement processing unit that performs edge enhancement correction on the density value of the pixel of interest when the edge determination unit determines that the pixel of interest is included in a pixel group having a large density value. Characteristic image processing device. 2. The image processing apparatus according to claim 1, wherein each pixel is sequentially read from the input image, and a density difference between a target pixel and a pixel adjacent to the target pixel is calculated, and the density difference is fixed. An image processing apparatus comprising: an entry / exit state detection unit that requests an edge determination unit to perform an edge determination process on a pixel of interest when the threshold value is equal to or greater than a threshold value. 3. An image area including the target pixel is set in the vicinity of the target pixel, and the pixel group included in the image area can be divided into a pixel group having a high density value and a pixel group having a low density value. If the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value, it is determined whether or not the pixel of interest is included in the pixel group having a large density value. An image processing method comprising: performing edge enhancement correction on a density value of a target pixel when it is determined that the target pixel is included in the pixel group having a large density value. 4. The image processing method according to claim 3, wherein each pixel is sequentially read from the input image, a density difference between the target pixel and a pixel adjacent to the target pixel is calculated, and the density difference is fixed. An image processing method characterized by requesting an edge determination process for a target pixel when the difference is equal to or larger than a threshold value. 5. An image area including the pixel of interest in the vicinity of the pixel of interest is set, and a group of pixels included in the image area can be divided into a pixel group having a high density value and a pixel group having a low density value. If the pixel group can be divided into a pixel group having a large density value and a pixel group having a small density value, it is determined whether or not the pixel of interest is included in the pixel group having a large density value. A computer-readable recording medium storing a computer program for executing, when it is determined that the pixel of interest is included in the pixel group having a large density value, a process of performing edge enhancement correction on the density value of the pixel of interest.