JP2000324340A - Picture data correcting device and its method and medium for recording picture data correction program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To simplify and quicken processing by calculating the distribution of the difference of the gradation values of each pixel and an adjacent pixels, and judging the characteristics of the distribution configuration data pixels. SOLUTION: Picture data obtained by multi-level expressing pictures with dot matrix-shaped pixels are obtained from a medium for recording a picture data correction program in a picture data obtaining process A1. The picture data are inputted from the picture data obtaining process A1, and the data of each pixel constituting the picture data are analyzed so that the characteristics, that is, whether or not the pixels are edge pixels or moire pixels or intermediate pixels can be judged in a pixel characteristic judging process A2. In this case, the distribution of the difference of the gradation values of each pixel with adjacent pixels is calculated so that the characteristics of the distribution configuration data pixels can be judged. Then, prescribed defining processing is executed to the pixels judged to form the edge, and prescribed smoothing processing is executed to the pixels judged to form the moire pixels for the picture data inputted from the picture data obtaining process A1 in a picture data correcting process A3.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image data modifying apparatus, an image data modifying method, and a medium storing an image data modifying program for determining the characteristics of pixels and executing image data modifying processing corresponding to the characteristics of each pixel. About.

[0002]

2. Description of the Related Art In order to improve the quality of an image captured by a scanner or a digital camera, image data modification processing is performed on image data of the image. Specifically, the image data is taken into a computer, a photo retouching application is activated on the computer, and a desired color component or contrast is emphasized. Alternatively, in order to reduce the influence of a predetermined color component, it is possible to perform various types of modification processing such as removing the color component.

Here, when the image to be subjected to the image data modification processing is a document image mainly composed of a character portion or a photographic image mainly composed of a photograph portion, the image corresponding to the main image is used. What is necessary is just to perform image data modification processing, and it can be realized with a simple processing configuration. on the other hand,
As is the case today, it is possible to easily create presentation documents in which documents and color graphs are integrated as well as album images in which text portions and photo portions are arranged in the same way, with DTP becoming the mainstream. In many cases, an image is composed of a so-called mixed image in which a portion and a photograph portion are mixed.

[0004] Regarding the character portion in the image data of such a mixed image, the boundary between the character and the background tends to be an intermediate color, the character is blurred, and the legibility often deteriorates. Further, periodic noise of high-frequency components is generated in a photograph portion, and in some cases, this noise is a cause of image quality deterioration that can be visually recognized. Therefore, when the image data modification process is performed on the mixed image, the shading of the boundary between the character and the background is emphasized in order to remove the blur of the character portion. Thereby, the legibility of characters can be improved. At this time, a predetermined sharpening process for emphasizing shading is performed on each pixel at the boundary portion.

On the other hand, in the photographic portion, since the above-mentioned noise is composed of high-frequency components, a predetermined smoothing process for reducing the high-frequency components is performed on each pixel on which the noise is present. Here, generally, a boundary region of a character portion is expressed as an edge pixel, and periodic noise of a high-frequency component generated in a photograph portion is expressed as a moiré pixel. The outline of the image data modifying process for the above-described mixed image will be described. First, image data of an image captured by a scanner or a digital camera is obtained as image data in which pixels in a dot matrix form are expressed in multiple gradations. Then, the pixels constituting the image data are sequentially scanned to calculate a gradation difference from surrounding pixels of a predetermined area based on the judgment pixel, and a case where there are many pixels having a large gradation difference is regarded as an edge pixel. Extract. In consideration of the position of the extracted edge pixel,
An edge pixel area to be sharpened is classified and determined.

Next, the pixels constituting the image data are sequentially scanned again, and the gradation difference from the surrounding pixels of the predetermined area is calculated based on the judgment pixel, and there are many pixels having a small gradation difference. The case is extracted as a moiré pixel. In consideration of the position of the extracted moiré pixels, the moiré pixel region to be subjected to the smoothing process is classified and determined. When the edge pixel region and the moiré pixel region are determined as described above, a sharpening process and a smoothing process are performed. In this case, the sharpening process and the smoothing process are sequentially executed.

The sharpening process extracts an edge pixel area,
The sharpening process is performed on this region, and the processed edge pixel region is held. The smoothing process extracts a moiré pixel region, performs a smoothing process on this region, and holds the processed moiré pixel region. That is, the sharpening processing area and the smoothing processing area that are distinguished in pixel units are individually extracted, and the processing is individually performed. Then, the image data of each area that has been processed and held is aligned and integrated to generate image data after the image data modification processing.

[0008]

In the above-described image data modification processing, the judgment of the edge pixel and the judgment of the moiré pixel are executed by separate processing, and the edge pixel area and the moiré pixel area divided by this processing are determined. Further, the image data modifying process is executed by a separate process. Therefore, there is a problem that the processing configuration of the process of determining the edge pixels and the moiré pixels and the process of modifying the image data of the pixels are complicated. As described above, since the processing configuration must be complicated, the processing speed is increased, and the user feels inconvenience.

SUMMARY OF THE INVENTION The present invention has been made in view of the above problems, and has been made in view of the fact that the processing for judging the characteristics of pixels such as edge pixels and moiré pixels is efficiently executed, and the corresponding image data modification processing is easily executed. It is an object of the present invention to provide a medium, an image data modifying apparatus, and an image data modifying method which record an image data modifying program capable of simplifying and simplifying the processing and increasing the processing speed.

[0010]

In order to achieve the above object, the invention according to claim 1 determines the characteristics of each pixel in image data in which an image is represented by multi-gradation using pixels in a dot matrix, and determines each pixel. An image data retouching device that performs retouching according to the characteristics thereof, wherein the image data obtaining means for obtaining the image data, and each pixel of the image data obtained by the image data obtaining means as a target pixel. ,
A pixel characteristic determining means for determining a distribution of a difference in tone value from a neighboring pixel in a predetermined range around the pixel characteristic and comparing the distribution with a predetermined model distribution to determine the characteristic of the target pixel; Image data modifying means for executing predetermined image processing corresponding to the characteristics of the pixels determined by the means.

According to the first aspect of the present invention, the image data obtaining means obtains image data in which an image is expressed by multi-gradation using pixels in a dot matrix. Then, the characteristic of each pixel in the image data is determined by the pixel characteristic determining means. At this time, each pixel is set as a target pixel, and a distribution of a difference in a gradation value from surrounding pixels in a predetermined range is obtained. After the distribution is obtained, the characteristics of the target pixel are determined by comparing the distribution with a predetermined model distribution. Then, predetermined image processing is executed by the image data modifying means in accordance with the determined characteristic of the pixel.

That is, instead of changing the determination process for each characteristic, the distribution of the difference in tone value between neighboring pixels is obtained, and the characteristics of the pixel are determined based on the distribution. Here, the pixel characteristic determining means obtains a distribution of a difference from the gradation value of the target pixel in a predetermined range centered on the target pixel, and compares this distribution with a model distribution from a statistical viewpoint. As a specific example, the invention according to claim 2 is the image data modifying apparatus according to claim 1, wherein the pixel characteristic determination unit determines the distribution of the range with a small difference and the distribution of the range with a large difference. Is used for determination.

In the invention according to claim 2 configured as described above, the frequency distribution of the difference between the tone values is obtained, but not the frequency distribution for each tone value but the distribution in the range where the difference is small and the difference is large. Find the distribution of the range. If the characteristic of the pixel to be determined is the presence or absence of an edge, the edge is a distribution at a place where the difference in tone value is large, so that a large number of distributions are necessarily found in a range where the difference is large. Also, if moiré occurs, pixels with a small change in gradation value in a minute range should have occurred. Needless to say, a similar tendency may be observed even if the edge or moiré is not used, but this is merely one criterion, and the determination accuracy may be increased in combination with another determination method. Therefore, such a distribution also corresponds to one model-like distribution.

In this sense, as another example of the pixel characteristic determining means, the invention according to claim 3 is the image data modifying apparatus according to claim 2, wherein the pixel characteristic determining means determines whether the distribution is positive or negative. The configuration is such that the bias is used for determination. In the invention according to claim 3 configured as described above, whether or not the difference distribution is biased toward the positive or negative region is used for the determination. For example, since an edge is a region where pixels having a large difference in tone value are continuous, there are generally a side having a large tone value and a side having a small tone value. If the target pixel is on the side of a pixel having a large gradation value, the distribution of the difference tends to be biased toward a distribution close to zero and a positive side. If the target pixel is on the side of the pixel having the smaller gradation value, the distribution of the difference tends to be biased toward a distribution close to zero and a negative side. Therefore, the positive / negative bias can be considered as one model-like distribution and used for determination.

According to a fourth aspect of the invention, as an example of a configuration specifically representing the above determination, in the image data modifying apparatus according to the third aspect, the pixel characteristic determination means may include a distribution in a range where the difference is large. And if the distribution has a positive or negative bias, it is determined to be an edge pixel. That is, it is determined as an edge pixel by combining the distribution of the range with a large difference and the positive / negative bias. According to a fifth aspect of the present invention, in the image data modifying apparatus according to the fourth aspect, the image data modifying means executes a sharpening image process when the target pixel is determined to be an edge pixel. There is a configuration to do.

If it is determined that the pixel is an edge pixel, a sharpening image process is executed using the result of determination as it is, thereby preventing the edge from becoming dull. According to a sixth aspect of the present invention, in the image data modifying apparatus according to the fifth aspect, the sharpening is formed in a matrix having a predetermined number of pixels centered on the target pixel, and each pixel of the matrix is formed. It is configured to be executed by a sharpening filter in which a predetermined coefficient that emphasizes the same target pixel is set at a position.

The pixels in a predetermined range centered on the target pixel are subjected to the determination processing. Similarly, if a sharpening filter that processes the pixels in the predetermined range is used, it is possible to determine the characteristics of the pixels and perform image processing. And the sharpening process can be executed efficiently. As another example of a configuration specifically representing the above-described determination, the invention according to claim 7 is the image data retouching device according to claim 3, wherein the pixel characteristic determination unit includes When there are many distributions in a range where the difference is small and there is a positive or negative bias in the distribution, it is determined to be a moiré pixel.

That is, a combination of the distribution in the small difference range and the positive / negative bias is determined as a moiré pixel. According to an eighth aspect of the present invention, in the image data modifying apparatus according to the seventh aspect, the image data modifying means executes smoothing image processing when the target pixel is determined to be a moiré pixel. There is a configuration to do. If the pixel is determined to be a moiré pixel, smoothing image processing is executed using the determination result as it is to eliminate moiré.

According to a ninth aspect of the present invention, in the image data retouching apparatus according to the eighth aspect, the smoothing is formed in a matrix having a predetermined number of pixels centered on a target pixel. Is executed by a smoothing filter in which a predetermined coefficient for substantially averaging the target pixel is set at each pixel position. For moiré pixels, a judgment process and a smoothing filter are applied by using pixels in a predetermined range around the target pixel, and efficient smoothing is performed while improving the familiarity between the pixel characteristic judgment and the image processing. Can perform processing.

According to a tenth aspect of the present invention, in the image data retouching device according to any one of the first to ninth aspects, the image data retouching means sets a retouching value for a luminance value of the image data. Then, the image data is modified by adding the same modification value to the gradation value of each element color. In the invention according to claim 10 configured as described above, when each pixel is composed of an element color, a luminance correction value for the calculated luminance of each pixel is generated, and the gradation of the element color of each pixel is generated. The image data is modified by adding the same luminance modification value to the value. That is, the modification processing is performed based on the luminance calculated from each element color, and the modification data based on the luminance is reflected on each element color.

By the way, the distribution of the difference between the gradation values may be obtained by using the concept of the vector value. For example, for a target pixel to be determined first, a gradation difference between the target pixel and surrounding pixels in a predetermined range is calculated as a vector value, and then the total of the surrounding pixels having a large vector value is calculated from the distribution of the vector values. And the sum of surrounding pixels having a small vector value. Then, a target pixel having a relatively large number of surrounding pixels having a large vector value is determined as an edge pixel, and a target pixel having a relatively large number of surrounding pixels having a small vector value is determined as a moiré pixel. Here, the pixel characteristic determination means executes the above-described determination processing by sequentially scanning all the pixels.

Whether each pixel corresponds to an edge pixel,
When the determination as to whether the pixel corresponds to a moiré pixel is completed, the image data modifying means performs a predetermined sharpening process on the pixel determined to form an edge pixel, and performs image sharpening processing on the pixel determined to form a moiré pixel. Then, a predetermined smoothing process is executed. Similarly, the image data modifying unit executes the image data modifying process by sequentially scanning all the pixels, similarly to the pixel characteristic determining unit. In this way, it is determined for each pixel whether the pixel is an edge pixel or a moiré pixel. If the pixel is an edge pixel, a sharpening process is performed. If the pixel is a moiré pixel, a smoothing process is performed.

In this way, the judgment of the edge pixels and the moiré pixels and the image data modification are collectively executed. On the other hand, the predetermined surrounding pixels are formed into a pixel set that forms a 3 * 3 matrix centered on the target pixel in consideration of a range that can affect the pixel to be determined or a range that can affect the target pixel. Or a set of pixels forming a 5 * 5 matrix, and the number of the matrices can be changed as appropriate. Of course, as described above, the present invention is not limited to the pixel set in the range directly affecting, and the range may be appropriately widened or narrowed.

Further, the mode of judging the magnitude of the vector value by the pixel characteristic judging means may be based on a predetermined threshold value or may be based on the average value of the vector values. The value used as the reference may be a standard deviation when a vector value distribution is created, or may be a mode value. Further, it may be a median value and can be changed as appropriate. Of course, the determination may be made separately for an area where the vector value is determined to be large, an area where the vector value is determined to be small, and another area.

In the pixel characteristic determining means, the relative number may be determined simply by comparing the number of pixels of each of the pixels whose vector values are classified into large or small, or the predetermined number of pixels may be distinguished by large or small. A pixel whose accumulated value exceeds a predetermined threshold value may be used as a target for determining the relative amount. The sharpening process in the image data modifying means may further enhance the color components of the pixels determined to be edge pixels and sharpen them from surrounding pixels, or may take into account the color components of surrounding pixels and enhance them.
Sharpening may be performed from the surrounding pixels. In the latter case, the surrounding pixels and the target pixel are multiplied by a predetermined coefficient and added.
A convolution operation is used. In such a case, the above-described predetermined matrix of surrounding pixels is used.

Similarly, in the smoothing process in the image data modifying means, the color components of the pixels determined to be moiré pixels may be slightly increased or decreased to smooth them, or may be smoothed in consideration of the color components of surrounding pixels. That is, it may be averaged by the gradation of the surrounding pixels. In the latter case, a convolution operation is used in which surrounding pixels and target pixels are multiplied by a predetermined coefficient and added. In such a case, the above-described predetermined matrix of surrounding pixels is used. The image data obtaining means only needs to be able to obtain image data in which an image is expressed in multiple gradations by dot matrix pixels. Therefore, the input source of the image may be a scanner or a digital camera, and can be appropriately changed as long as image data expressed in multiple gradations by dot matrix pixels can be obtained.

Further, the image may be a monochrome image or a color image. In the case of a color image, it is also necessary to determine a coordinate system in a color space or a gradation range. There is no particular limitation. Depending on the distribution of vector values based on the gradation difference between the target pixel and surrounding pixels, it is considered that there are pixels that cannot be determined as edge pixels or moire pixels. Such a pixel is a case where there is only a slight gradation difference from the surrounding pixels,
When such pixels are treated as edge pixels or moiré pixels, accurate image data modification processing may not be performed in some cases.
From such a viewpoint, a configuration may be adopted in which a pixel having a relatively large number of pixels having a vector value smaller than the vector value determined as a moiré pixel is determined as an intermediate pixel that does not correspond to an edge pixel and a moiré pixel. In the case of such a configuration, the pixel characteristic determination unit determines that a pixel having a relatively large number of pixels having a vector value smaller than the vector value determined as a moiré pixel is an intermediate pixel that does not correspond to an edge pixel and a moiré pixel. Accordingly, the pixel characteristic determining means calculates a vector value, sets a value for determining an edge pixel, a value for determining a moiré pixel, and a value for determining an intermediate pixel with respect to the vector value. A case where the value is smaller than a value to be determined as a pixel is treated as an intermediate pixel.

As a specific example of the element for calculating the vector value from the gradation difference, the pixel characteristic determination means calculates the luminance of each pixel and calculates the gradation difference of the same luminance as a vector value. Can be. In the case of such a configuration, the pixel characteristic determining unit calculates the luminance from the color component data constituting each pixel of the image data acquired by the image data acquiring unit based on a predetermined arithmetic expression. Then, a gradation difference is calculated as a vector value based on the luminance, and the determination of an edge pixel, a moiré pixel, or an intermediate pixel is performed.

As another specific example of the element for calculating the vector value from the gradation difference by the pixel characteristic judging means, each pixel is color-separated into each element color, and the gradation difference between the same color-separated element colors is calculated. It may be configured to calculate as a vector value. In the case of such a configuration, the pixel characteristic determining unit performs color separation of each pixel into each element color, and calculates a gradation difference of each element color separated by the same color as a vector value. here,
Each element color is a color component that constitutes a pixel.
It refers to three-color data of (red) G (green) and B (blue). When determining the characteristics of a pixel from a vector value for each element color, an element forming an edge pixel with one element color may be determined as an edge pixel, or an edge pixel may be formed using two element colors. May be determined as edge pixels, or only those that form edge pixels for three element colors, that is, all element colors, may be determined as edge pixels. Therefore, this determination method can be appropriately changed.

As an example of handling in the image data modifying means for a pixel determined to be an intermediate pixel by the pixel characteristic determining means, image data modification of sharpening processing or smoothing processing is not performed on the intermediate pixel. It may be configured. In the case of such a configuration, the image data modifying means includes:
The image data modification of the sharpening process or the smoothing process is not performed on the pixel determined as the intermediate pixel by the pixel characteristic determining unit. That is, the level of the corresponding pixel of the image data acquired by the image data acquiring means is held.

Here, the image data often includes various types of information, but the data to be used does not need to be fixed. As an example, when modifying the image data of each pixel, the image data attribute instructing means for acquiring an instruction of the attribute of the image data to be processed is executed, and based on the image data of the attribute acquired by the image data attribute instructing means. A configuration may be adopted in which the pixel characteristic determination unit and the image data modification unit are executed.

Conventionally, the attributes of image data to be modified have been fixed. That is, if the attribute is based on the luminance signal, the image data modification process is performed on the luminance signal of the image data. On the other hand, if the attribute is based on the RGB signal,
Image data modification processing has been performed on the RGB signals of the image data. In such a case, when the user desires a high-quality output result, the image data modifying process based on the luminance signal is compared with the image data modifying process based on the RGB signal. Output results are inferior. Further, when the user desires the image data retouching process in a short time, the image data retouching process is executed based on the RGB signal, and when the image data retouching process is executed based on the luminance signal, The execution time is longer in comparison. In other words, there is a problem that a situation occurs in which the condition desired by the user cannot be satisfied because of being fixed.

In the case of such a configuration, the instruction of the attribute of the image data handled by the image data attribute instructing means is obtained,
The pixel characteristic determining unit and the image data modifying unit are executed based on the image data of the attribute acquired by the image data attribute instructing unit. That is, in performing the image data modifying process, the attribute of the image data used in the process is not executed by a predetermined fixed attribute, but the attribute designated by the image data attribute designating means is selected, and based on this selection, To perform pixel characteristic determination means and image data modification processing.

As described above, the attribute of the image data to be subjected to the image data modification processing in accordance with the predetermined instruction is determined, the usability is improved, and the user can obtain an output result under desired conditions. Here, the image data attribute instructing means only needs to be able to indicate an attribute for handling the image data, may indicate an attribute selected by the user, or may analyze the image data to be suitable for the configuration of the image data. Attribute may be indicated. Further, the attribute may be specified according to the state of the resource of the device to be applied. Of course, the present invention is not limited to these, and can be changed as appropriate as long as the image data modifying means can indicate an attribute to be handled in the image data modifying process.

Such an attribute may be any attribute as long as it can be introduced from the pixels representing the multi-gradation constituting the image data, and may be binary data or R (red) G
The data may be (green) B (blue) data or luminance data calculated from the RGB data. Of course,
The present invention is not limited to these, and can be changed as appropriate as long as the state of the image data can be expressed. As a specific example of the attribute to be instructed, when the image data attribute instructing unit desires the image data modifying process at a high speed, instructs the luminance signal as the attribute and desires the high quality image data modifying process Alternatively, a configuration may be adopted in which an element color signal for forming an image is specified as an attribute.

In such a configuration, the image data attribute instructing means, when instructing the attribute of the image data handled in the image data modifying process, instructs the luminance signal as the attribute if the process is to be realized at high speed. I do. When it is desired to realize high quality image data of the image data generated after the image data modification processing, an element color signal for forming an image, for example, an RGB signal is specified as an attribute. When the image data is composed of R (red), G (green), and B (blue) data, the luminance signal can be calculated based on the RGB data. The number of pixels constituting the image data is 1
In the case of 00 pixels, only the luminance of each pixel is calculated according to the luminance signal, so that there are image data of 100 luminance gradations. On the other hand, according to the RGB data, since each pixel has three colors, there are image data with 300 gradations. Therefore, since the number of data to be handled in the image data modification processing differs, a high-speed image data modification processing requires a luminance signal. On the other hand, when a high-quality output is to be realized, an element color signal for forming an image, such as an RGB signal, is specified.

This is for the following reason. A general luminance signal is not a mixture of the RGB signals at an equal ratio, and the RGB signals are approximately 30%, approximately 60%, and approximately 10%, respectively.
%. Thus, for example,
When the B data contains many moiré components, the method of modifying the luminance signal and reflecting the modification on the RGB signal cannot sufficiently reduce the moiré component of the B data. At this time, B
In order to sufficiently reduce the moiré component of the data, it is necessary to perform a modification process on each of the RGB data.
Therefore, when realizing a high quality output, an RGB signal is instructed.

The image data modifying processing performed by the image data modifying means may be any processing that modifies the image data and adjusts the image quality of the reproduced image. Therefore,
Sharpening and unsharpening of an image can be appropriately adopted. In such a case, a predetermined filter is often applied to each pixel in the image data modification process, and when it is desired to sharpen a predetermined pixel, a predetermined sharpening filter is applied to the pixel to enhance the gradation. If it is desired to make a predetermined pixel unsharp, a predetermined smoothing filter is applied, and the gradation is averaged.

As described above, the method of judging the characteristics of each pixel constituting the image data and executing the modification according to the characteristics for each pixel is not necessarily limited to a substantial device. It is easy to understand that also works. For this reason, the invention according to claim 11 determines the characteristics of each pixel in the image data in which the image is expressed by multi-gradation using pixels in a dot matrix, and executes an image correction for each pixel according to the characteristics. A data modification method, comprising: an image data obtaining step of obtaining the image data; and each pixel of the image data obtained in the image data obtaining step as a target pixel, and a gradation with a neighboring pixel in a predetermined range around the target pixel. A pixel characteristic determination step of determining the distribution of the value difference, comparing the distribution with a predetermined model distribution and determining the characteristic of the target pixel, and corresponding to the characteristic of the pixel determined in the pixel characteristic determination step. An image data modifying step for executing a predetermined image processing is provided.

That is, there is no difference that the method is not necessarily limited to a tangible medium or the like and is effective as a method. It goes without saying that, in the image data retouching method, the aspects of the invention as described in claims 2 to 10 are exactly the same. By the way, such an image data retouching device may exist alone, or may be used in a state incorporated in a certain device.
The idea of the invention is not limited to this, but includes various aspects. Therefore, it can be changed as appropriate, such as software or hardware.

When the software of the image data modifying apparatus is used as an example of realizing the idea of the present invention, the software naturally exists on a recording medium on which such software is recorded, and it must be said that the software is used. As an example, the invention according to claim 21 determines a characteristic of each pixel in image data in which an image is expressed by multi-gradation using pixels in a dot matrix form, and performs a modification according to the characteristic for each pixel. A medium in which an image data modification program is recorded, wherein an image data acquisition function for acquiring the image data, and each pixel of the image data acquired by the image data acquisition function as a target pixel, and a predetermined range around the target pixel. A pixel characteristic determining function for determining a distribution of a difference between a pixel and a gradation value, comparing the distribution with a predetermined model distribution, and determining a characteristic of a target pixel; and a pixel determined by the pixel characteristic determining function. Each of the functions of the image data modifying function for executing a predetermined image processing corresponding to the above characteristic is implemented. Claim 2
It goes without saying that the aspect of the invention as set forth in claim 10 applies to the medium in which the present image data modifying program is recorded.

Of course, such a recording medium may be a magnetic recording medium or a magneto-optical recording medium, and any recording medium to be developed in the future can be considered in the same manner. Also, the duplication stages of the primary duplicated product, the secondary duplicated product, and the like are equivalent without any question. Further, even when a part is implemented by software and a part is implemented by hardware, the concept of the present invention is not completely different, and a part is stored on a recording medium and appropriately It may be in a form that can be read.

When the present invention is implemented by software, it may be configured to use hardware or an operating system, or may be implemented separately from these. For example, even if it is a process of inputting image data to perform an interpolation process, if a method for realizing the process can call a predetermined function in the operating system and perform processing, the hardware can be used without calling such a function. It is also possible to input from. Then, it can be understood that the present invention can be implemented only by the program in the process of being recorded on a medium and distributed, even if the program is actually realized with the intervention of an operating system. The computer executes the program, but the computer is not limited to a normal computer, and various modes are possible as long as the computer is installed with one or more CPUs and processes the program. For example, it goes without saying that an intelligent printer or copy can be said to be a computer.

When the present invention is implemented by software, the present invention can be realized not only as a medium on which a program is recorded, but also as the program itself. included.

[0045]

As described above, according to the present invention, the distribution of the difference between the gradation values of the neighboring pixels is obtained, and the characteristics of the pixels are determined according to the distribution mode. There is no need to provide an image data modifying apparatus capable of facilitating determination, enhancing coordination with image processing, and increasing processing speed.

According to the second aspect of the present invention, it is possible to use a relatively simple tabulation of a distribution in a range with a small difference and a distribution in a range with a large difference, and to simplify the configuration. Furthermore, according to the third aspect of the present invention, it is possible to use a relatively simple counting of positive or negative bias of the distribution for the determination and to simplify the configuration. Claim 4
According to the present invention, the edge can be easily determined by combining the distribution of the range with a large difference and the positive / negative bias.

Further, according to the invention of claim 5,
Image processing suitable for edge pixels can be performed by sharpening the edge pixels. Further, according to the invention of claim 6, since the sharpening filter is used to implement the sharpening processing for a predetermined range of pixels around the target pixel as in the case of the determination, the determination and the image processing are compared. It can be handled well. Furthermore, according to the invention of claim 7, it is possible to easily determine the moire by combining the distribution of the small difference range and the positive / negative bias.

Further, according to the invention of claim 8,
Image processing suitable for moiré pixels can be performed by smoothing the moiré pixels. Further, according to the ninth aspect of the present invention, the determination and the image processing are compared with each other in order to implement the smoothing processing with the smoothing filter for the pixels in the predetermined range around the target pixel as in the case of the determination. It can be handled well. Furthermore, according to the tenth aspect of the present invention, the determination process of the edge pixels and the moiré pixels and the image data modification process for each of these pixels are collectively executed, thereby simplifying the configuration of the image data modification process. It is possible to provide an image data retouching method that can be simplified and can speed up processing.

Further, according to the invention of claims 11 to 20, it is possible to provide an image data correction method capable of achieving the same effect, and to provide the invention of claims 21 to 30. According to this, it is possible to provide a medium in which the image data correction program is recorded.

[0050]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 shows a claim correspondence diagram of an image data modifying method according to an embodiment of the present invention. In the figure, the medium on which the image data modifying program is recorded acquires image data in which an image is expressed in multiple gradations by dot matrix pixels in an image data acquiring step A1. Then, the pixel characteristic determining step A2 receives the image data from the image data obtaining step A1, analyzes the data of each pixel constituting the image data, and analyzes the characteristics, that is, whether the pixel is an edge pixel, a moiré pixel or an intermediate pixel. It is determined whether the pixel is a pixel. Specifically, first, for a target pixel to be determined, a gradation difference between the pixel and a surrounding pixel in a predetermined range is calculated as a vector value, and then, the vector value is large from the distribution of the vector value. The total number of pixels is compared with the total number of pixels having a small vector value. Then, a pixel having a relatively large number of pixels having a large vector value is determined as an edge pixel, and a pixel having a relatively large number of pixels having a small vector value is determined as a moiré pixel. Also. A pixel having a relatively small vector value and a relatively large number of pixels that cannot be determined as a moiré pixel is determined as an intermediate pixel. Pixel characteristic determination step A2
Performs this determination processing by sequentially scanning all pixels. When the determination as to whether each pixel corresponds to an edge pixel, a moiré pixel, or an intermediate pixel is completed, the image data modifying step A3 performs edge pixel processing on the image data input from the image data obtaining step A1. A predetermined sharpening process is performed on the pixels determined to form the moire pixels, and a predetermined smoothing process is performed on the pixels determined to form the moiré pixels. No processing is performed on pixels determined to form intermediate pixels. In the image data modifying step A3, similarly to the pixel characteristic determining step A2, image data modifying processing is performed by sequentially scanning all pixels.

In performing the image data modifying process, the image data attribute designating step A4 designates an attribute to be handled in the image data modifying process, for example, a luminance signal or an RGB signal. This instruction may be performed by the user's selection, or may be performed by the configuration of the image data. Therefore, when a luminance signal is designated as an attribute, the image data modifying process A3 executes the image data modifying process based on the luminance data of each pixel. When an RGB signal is designated as an attribute, the image data modifying process A3 performs the image data modifying process. This is performed using RGB data.

Next, FIG. 2 is a perspective view showing an external appearance of a color copying apparatus which is applied to constitute an image data retouching apparatus which embodies the present image data retouching method. Book color copying machine 1
Numeral 0 is composed of a color scanner 20, a copy server 30, and a color printer 40. When an image is scanned by the color scanner 20 based on the control of the copy server 30, the image data read by the scan is The copy server 30 performs image processing to generate print data, and the color printer 40 performs printing based on the print data.

FIG. 3 shows a schematic configuration of the color scanner 20, which employs a flatbed type. In the figure, an illumination lamp 22 and a line sensor 23 are slidably supported below a transparent plate 21 on which an object to be scanned is placed, and a driving belt 24a and a pulley 24b for driving these lamps. Drive motor 2
4c are connected to the control circuit 25. When reading an image, when the illumination lamp 22 is turned on based on a control signal from the control circuit 25, the object to be scanned is illuminated via the transparent plate 21. Therefore, the reflected light from the scan target illuminates the transparent plate 21. The light is radiated to the line sensor 23 via the light source.

Here, the line sensor 23 is provided with RGB filters and CCD elements corresponding to the three primary colors of light, one row for each color, usually three rows, and these three rows of CCD elements extend in the horizontal direction of the scanning object. The color arrangement for one row is read and output as image data. On the other hand, the control circuit 25 drives the drive motor 24c to
The illumination lamp 22 and the line sensor 24 are integrally moved in the vertical direction of the scan target, and image data is acquired and output from the line sensor 23 each time the illumination lamp 22 and the line sensor 24 are moved by a minute distance. Accordingly, externally, the object to be scanned is sub-scanned in the vertical direction while main scanning in the horizontal direction, and two-dimensional image data is generated.

FIGS. 4 and 5 show the copy server 30 in a schematic block diagram. The copy server 30 is roughly equivalent to a computer, and a RAM 33, a ROM 34 and an operation panel 35 are connected to a bus 32 of the CPU 31.
And the hard disk 36 and the I / F 37 are connected. Here, the color scanner 20 and the color printer 40 are connected via the I / F 37. Further, a basic calculation program and a conversion table are written in the ROM 34, and the CPU 31 executes the calculation program while using the RAM 33 as a work area, and refers to the conversion table as needed. In the present embodiment, the I / F 37 is not specified, but the I / F 37 is used for the color scanner 20 and the color printer 40.
Can be connected to the copy server 30 and may be connected by an LPT port or may be connected by a USB port or SCSI.

The hard disk 36 includes a scanner driver 38a for driving the color scanner 20 and a printer driver 38b for driving the color printer 40.
The scanner driver 38a can input and output image data from the color scanner 20 and the printer driver 38b can input and output image data to the color printer 40, respectively.
Then, the hard disk 36 is used as a buffer for temporarily storing the image data, reads the image data input by the scanner driver 38a, determines the characteristics of each pixel constituting the image data, and determines a predetermined characteristic according to the determination. Image data modification processing, and the image data subjected to this image data modification processing is
8b, and stores an image data modifying program 39 for causing the color printer 40 to execute printing.

In addition, the operation panel 35 includes a scan start button 35a, input of the number of prints, setting of items for modifying the image, and whether the scan target is a color image in which a photograph or the like is arranged. Or a liquid crystal display 35c for confirming operation information, as well as various operation buttons such as a numeric keypad 35b for setting whether the image is a monochrome image such as a document.
, The operation status of the operation panel 35 can be monitored.

FIG. 6 schematically shows the structure of the color printer 40, which employs an ink jet system in which color ink is ejected onto a recording paper in the form of a dot matrix to perform printing. More specifically, a print head 41 including three print head units 41a,
Head controller 42 for controlling the print head and a print head girder moving motor 4 for moving the print head 41 in the girder direction
3, a paper feed motor 44 for feeding print paper in the row direction, a print head controller 42, a print head digit moving motor 43, and a printer controller 45 which serves as an interface between the paper feed motor 44 and external devices. .

The color printer 40 uses four color inks as print inks, and each print head unit 41a has two independent rows of print nozzles. The color ink to be supplied can be changed for each row of print nozzles. In this case, black ink (K) is supplied to both rows of the print head unit 41a on the left side in the figure, and the print head unit 41a on the right side in the figure.
With respect to, the magenta ink (M) is supplied to the left column, the yellow ink (Y) is supplied to the right column, and the cyan ink (C) is supplied to the left column for the print head unit 41a in the middle of the drawing. The right column is unused.

Although four color inks are used in the present embodiment, three print head units 41 are used.
It is also possible to use six color inks by maximizing the use of the two rows of print nozzles in a. In this case, dark and light inks are used for cyan and magenta, and a total of six colors can be used using yellow and black. In the present embodiment, the present image data modifying apparatus is applied as the integrated color copying apparatus 10 formed integrally with the copy server 30 as a core, but the color scanner 51 as shown in FIG. It goes without saying that the same can be realized by a personal computer 53 having a color printer 52 even if a color copying system is adopted.

FIG. 8 is a flowchart schematically showing the contents of the image data modification processing according to the present invention, out of the color copying processing executed by the copy server 30 described above. In FIG. 1, when the operator of the color copying apparatus 10 places an object to be scanned on the flatbed 21 of the color scanner 20, the operator pushes down a scan start button 35a on the operation panel 35. Thus, the color scanner 20 starts scanning based on the above-described operation. First, a scan process is performed on the entire image of the flatbed 21 including the image of the scan target in order to generate image data including pixels of a predetermined resolution (step S100). Next, in performing the image data modification process on the generated image data, an image data attribute selection process of selecting an attribute of the image data to be applied to the process is performed (step S150). Then, each pixel of the image data generated by the scanning process is set as a target pixel, and a gradation difference calculation process of calculating a gradation difference between each target pixel and surrounding pixels is performed based on the selected attribute. (Step S200) A pixel characteristic determination process is performed to determine whether the pixel is an edge pixel, a moiré pixel, or an intermediate pixel based on the gradation difference (step S300). Next, if the characteristic of each pixel is an edge pixel, a sharpening process is performed; if it is a moiré pixel, a smoothing process is performed; if it is an intermediate pixel, an image data modification process that retains the original pixel data Is executed (step S400). Such image data modification processing is also executed based on the selected attribute. When the image data modification process is completed, an image data conversion process for generating print data to be output to the color printer 40 is executed (step S500). Then, the print data resulting from the conversion of the image data is transferred to the color printer 40 and printed out by the color printer 40. As described above, since the attribute of the image data to be subjected to the image data modification processing is selectable, for example, when the image data modification processing is to be performed at high speed, the luminance signal may be selected as the attribute, and the image data modification processing may be performed. When it is desired to obtain a high quality image by the retouching process, an RGB signal may be selected as an attribute, and a desired image data retouching process environment can be obtained.

Next, the respective processes of steps S100 to S500 will be described in more detail with reference to the flowcharts of FIGS. The flowchart in FIG. 9 shows the processing content of the scan processing in step S100. As described above, when the operator of the color copying apparatus places a document on the flatbed 21 as a scan target and depresses the scanner start button 35a, the I / O is started.
An image reading command is sent to the color scanner 20 via the interface 37 to start scanning (step S10).
5). Then, the scan resolution set by the operator using the numeric keypad 35b or the resolution previously set in the color copying apparatus 10 is read (step S1).
10). Here, the control circuit 25 of the color scanner 20 turns on the illumination lamp 22, outputs a drive command to the drive motor 24c, and starts scanning of the image by sliding the illumination lamp 22 and the line sensor 23 (see FIG. 1). Step S115). Then, the control circuit 25 acquires the image data read by the line sensor 23 every time the control circuit 25 moves by a predetermined distance, generates image data having a resolution specified in advance (step S120), and transmits the image data to the copy server 30. . The copy server 30 receives this image data via the I / F 37 and spools it on the hard disk 36. Here, if it is determined that all the scanning has been completed for the divided pixels (step S125), the spooled image data is stored in the hard disk 36 (step S130). Therefore,
A scan process of executing a scan with a predetermined resolution on a scan target and acquiring and storing image data constitutes an image data acquisition step A1 according to the present invention.

As described above, the color scanner 20 generates the image data of the image of the object to be scanned. This image data is subjected to various types of image data modification processing for the purpose of improving image quality and the like. When performing such image data modification processing, it is necessary to handle image data according to predetermined attributes. FIG. 10 shows a step S for selecting this attribute.
It is a flowchart which shows the processing content of 150 image data attribute selection processing. In the figure, an attribute set by the user on the operation panel 35 of the copy server 30 is obtained (step S155). If the attribute is luminance (step S160), when image data is to be handled thereafter, a setting is made to execute a predetermined process on the luminance data (step S165). On the other hand, if the acquired attribute is R
If the image data is GB, RG
A setting is made to execute a predetermined process on the B data (step S170).

FIG. 11 is a flowchart showing the contents of the gradation difference calculation processing in step S200. In the figure, the image data of the image of the scan target generated by the scan process is read (step S205). Then, it is determined whether or not the attribute selected in the above-described image data attribute selection processing is luminance data (step S206). In the case of the luminance data, each pixel constituting the image data is scanned, and the luminance of the target pixel is calculated while setting the scanned pixel as a target pixel for determining the characteristics of the pixel (step S210). The luminance Y is expressed by the following equation (1), where each element color R (red) G
It is calculated by substituting the gradation of (green) G (blue) data.

Y = 0.30R + 0.59G + 0.11B (1) Next, the luminance of the surrounding pixels formed by a 5 * 5 matrix centered on the target pixel is calculated based on Expression (1). (Step S215). On the other hand, if the selected attribute is RGB
In the case of data, each RGB data of the target pixel is extracted (step S216), and each RGB data of surrounding pixels is extracted (step S217). If the attribute is luminance data, the luminance difference of the target pixel is subtracted from the luminance gradation of the surrounding pixels to calculate a gradation difference. On the other hand, the attribute is RG
In the case of the B data, the gradation of the target pixel is subtracted from the gradation of the surrounding pixels for each of the RGB data to calculate a gradation difference (step S220). When the calculation of the gradation difference from each surrounding pixel is completed, a distribution based on the frequency of the pixels included in each gradation difference is created (step S225), and a predetermined edge pixel, moiré pixel, intermediate pixel and The total is calculated for each of the determined categories (step S230).

By executing a pixel characteristic determination process described later, it is determined whether the target pixel is an edge pixel, a moiré pixel, or an intermediate pixel (step S23).
5). It is determined whether or not all the pixels of the image data read in step S205 have been subjected to the pixel characteristic determination processing as the target pixels by the pixel characteristic determination processing (step S240). If the characteristics have been determined for all pixels,
If the gradation difference calculation processing is completed and the characteristics have not been determined for all the pixels, the target pixel is moved, and the processing from step S210 is repeated.

Here, the above-described gradation difference calculation processing will be specifically described with reference to FIG. FIG.
* 5 indicates original image data of matrix. The subsection indicates a pixel unit, and if each pixel is indicated by (x, y) coordinates, a pixel (0, 0) shaded at the center constitutes a target pixel, and the target pixel (0, 0) 0) and pixels (-
(2, -2) to pixel (2, 2) constitute surrounding pixels. Further, the numerical value shown for each pixel indicates a gradation. And
The tone difference between the target pixel and the surrounding pixels is calculated by the following equation (2).

B (n1, n2) = a (n1, n2) −a (N1, N2) (2) n1 = N1-2, N1-1, N1, N1 + 1, N1 + 2 n2 = N2-2, N2- 1, N2, N2 + 1, N2 + 2 Here, a (N1, N2) indicates the gradation of the target pixel, and in the present embodiment, a (N1, N2) = 64. Further, a (n1, n2) indicates the original gradation of the surrounding pixels, and b (n1, n2) indicates the gradation difference between the surrounding pixels and the target pixel. The results calculated in this way are shown in a 5 * 5 matrix in FIG. Then, while creating the distribution of each gradation difference, a distribution that is totaled for each section shown in FIG. 12C is generated.

In this embodiment, this section is referred to as section 1
[−255, −50), section 2 [−50, −10), section 3 [−10, 10), section 4 [10, 50), section 5 [5
0, 255], and the frequencies of the tone differences are totaled for these sections 1 to 5. In such a case, the total number of each is C
If 1 to C5, C1 = 0, C2 = 1, C3 = 11,
It can be seen that C4 = 13 and C5 = 0. In the present embodiment, the section of the distribution is set to the section 1 [−255, −5
0), section 2 [-50, -10), section 3 [-10, 1
0), section 4 [10, 50), and section 5 [50, 255]. Of course, the setting method of this section is not particularly limited and can be changed as appropriate.

If the attribute is luminance data, the processing of steps S225 to S235 is performed on only luminance data for each pixel. On the other hand, when the attribute is RGB data, the process is performed for each RGB data of each pixel.
Next, the pixel characteristic determination processing performed in step S235 described above will be described. FIG. 13 is a flowchart showing the contents of the pixel characteristic determination processing.
In the figure, first, C
1 to C5 are acquired (step S305). Then, it is determined whether or not C1 to C5 satisfy the edge pixel determination condition represented by the following equation (3) (step S310). C1>C2> Te, C4 = C5 = 0 or... (3) C5>C4> Te, C1 = C2 = 0 Here, Te indicates a predetermined threshold value determined in advance, and The embodiment is implemented with Te = 5. Of course, it is not limited to Te = 5, but can be changed as appropriate.

If the expression (3) is satisfied, the target pixel is determined to be an edge pixel (step S315), and a pixel characteristic flag indicating the characteristic of this pixel is set as an edge flag (step S320). When the attribute is luminance data, the edge flag has only one pixel characteristic flag for each pixel. Therefore, as shown in FIG. 14A, a predetermined bit data indicating a characteristic provided for each target pixel is used. A configuration in which the bit position is turned on / off is adopted, and when the attribute is RGB data, the bit data indicating the characteristics provided for each RGB data for each target pixel is turned on / off as shown in FIG. Adopt configuration.

As another example, as shown in FIG. 15A, a characteristic flag table indicating the same configuration as the pixel range forming the image data is generated, and data indicating the edge flag is stored at the corresponding pixel position. You may write it.
Of course, FIG. 15A shows a case where the attribute is luminance data, and in the case of RGB data, a characteristic flag table is generated for each RGB as shown in FIG. 15B. If the target pixel does not satisfy the edge pixel determination condition in step S310, it is determined whether or not the moire pixel determination condition represented by the following equation (4) is satisfied (step S32).
5). C2>C1> Tm, C4 = C5 = 0 or... (4) C4>C5> Tm, C1 = C2 = 0 where Tm indicates a predetermined threshold value which is determined in advance. The embodiment is implemented with Tm = 3. Of course, it is not limited to Tm = 3, but can be changed as appropriate.

If equation (4) is satisfied, the target pixel is determined to be a moiré pixel (step S330), and a pixel characteristic flag indicating the characteristic of this pixel is set as a moiré flag (step S335). As described above, the moiré flag is shown in FIGS. 14 (a) and (b) or FIGS. 15 (a) and (b).
A predetermined bit position of the bit data indicating the gradation data of the target pixel may be turned on or off as shown in FIG. 3, or a characteristic flag table indicating the same configuration as the pixel range forming the image data may be generated. The data indicating the moire flag may be written at the pixel position where the moiré flag is set.

On the other hand, in the determination of step S325,
Pixels that do not satisfy the moiré pixel determination condition are determined as intermediate pixels (step S340). Then, a pixel characteristic flag indicating the characteristic of the pixel is set as an intermediate flag (step S345). As for the intermediate flag, as described above, the predetermined bit position of the bit data indicating the gradation data of the target pixel is turned on or off as shown in FIGS. 14 (a) and 15 (b). Or
A characteristic flag table indicating the same configuration as the pixel range forming the image data may be generated, and data indicating the intermediate flag may be written at the corresponding pixel position.

If the selected attribute is RGB data, steps S305 to S345 are performed for each of RGB.
It is necessary to determine whether or not the process is executed (steps S350, S355). Here, an example of the configuration and distribution of the edge pixels, the moiré pixels, and the intermediate pixels is shown in FIGS. FIGS. 16 to 18 show a case where the attribute is luminance data. When the attribute is RGB data, a distribution is generated for each RGB.

FIG. 16 shows a case where the target pixel forms an edge pixel. FIG. 16A shows original image data of a 5 * 5 matrix, and a small section indicates a pixel unit. The pixel (0, 0) shaded constitutes the target pixel, and the pixel (-2,-) including the target pixel (0, 0) is included.
2) to pixel (2, 2) constitute surrounding pixels. The numerical value shown in each subsection indicates the gradation of each pixel. And
The tone difference between the target pixel and the surrounding pixels is calculated by equation (2). The calculation result is shown in a 5 * 5 matrix in FIG. Then, while creating the distribution of each gradation difference, a distribution totalized for each section shown in FIG. 16C is generated. In such a case, assuming that the total numbers are C1 to C5, C1 =
It can be seen that 0, C2 = 0, C3 = 1, C4 = 7, and C5 = 17. Therefore, the target pixel is determined to be an edge pixel because the condition of the above-described equation (3) is satisfied.

FIG. 17 shows a case where the target pixel forms a moiré pixel. FIG. 17A shows original image data of a 5 * 5 matrix, and a small section indicates a pixel unit. The pixel (0, 0) shaded constitutes the target pixel, and the pixel (-2,-) including the target pixel (0, 0) is included.
2) to pixel (2, 2) constitute surrounding pixels. The numerical value shown in each subsection indicates the gradation of each pixel. And
The tone difference between the target pixel and the surrounding pixels is calculated by equation (2). The calculation result is shown in a 5 * 5 matrix in FIG. Then, while creating the distribution of each gradation difference, a distribution totalized for each section shown in FIG. 17C is generated. In such a case, assuming that the total numbers are C1 to C5, C1 =
It can be seen that 0, C2 = 0, C3 = 5, C4 = 12, and C5 = 8. Therefore, the target pixel is determined to be a moiré pixel because the condition of Expression (4) is satisfied.

FIG. 18 shows a case where the target pixel forms an intermediate pixel. FIG. 18A shows original image data of a 5 * 5 matrix, and a small section indicates a pixel unit. The pixel (0, 0) shaded forms a target pixel, and the pixel (−2, 0) including the target pixel (0, 0) is included.
-2) to pixel (2, 2) form surrounding pixels. The numerical value shown in each subsection indicates the gradation of each pixel. Then, the tone difference between the target pixel and the surrounding pixels is calculated by Expression (2). The calculation result is shown in a 5 * 5 matrix of FIG. Then, while creating the distribution of each gradation difference, FIG.
Is generated for each section shown in FIG. In such a case, assuming that the total numbers are C1 to C5, C1 =
It can be seen that 0, C2 = 1, C3 = 21, C4 = 2, C5 = 1. Therefore, the above equations (3) and (4)
Since none of the conditions is satisfied, the pixel is determined to be an intermediate pixel.

Therefore, the image data attribute selecting process constitutes the image data attribute specifying step A4 by selecting and specifying the data attribute when performing the image data modifying process on the image data of the scan object generated in the scanning process. . Further, for each pixel constituting the acquired image data, it is determined whether the target pixel is an edge pixel, a moiré pixel, or an intermediate pixel from the distribution based on the gray level difference with the surrounding pixels, thereby performing the gray level difference calculation processing and The pixel determination processing constitutes a pixel characteristic determination step A2.

Next, the processing contents of the image data modification processing in step S400 will be described with reference to the flowchart of FIG.
In the figure, first, image data generated by the above-described scan processing and stored with the characteristic flag of each pixel in the pixel characteristic determination processing is read (step S40).
5). Then, a characteristic flag is checked for each pixel constituting the image data. First, it is determined whether or not the characteristic flag is an edge flag (step S410). If the characteristic flag is an edge flag, the sharpening filter shown in FIG. 20 is applied to the pixel (step S415). This sharpening filter is formed by a 3 * 3 matrix, and sets a large coefficient to a target pixel of a small section shaded with diagonal lines, and negatively assigns negative pixels to the upper, lower, left and right peripheral pixels in order to emphasize the gradation of the target pixel. A coefficient is set, and zero is set as a coefficient for surrounding pixels that are not in direct contact. The application of the sharpening filter can be expressed by the following equation (6). Here, the gradation of the original pixel is set to a (N1, N2), and the output pixel after applying the sharp filter is set to c (N1, N2).

[0081]

(Equation 1) However, h (k1, k2) is given by the following equations (7) and (8) from FIG. h (-1,, 1) = 0, h (-1,0) =-1, h (-1,1,) = 0, h (0, -1) =-1, h (0,0) = 5, h (0,1) =-1, h (1, -1) = 0, h (1,0) =-1, h (1,1) = 0 ... (7) h (-1 ,,-) 1) + h (-1,0) + h (-1,1) + h (0, -1) + h (0,0) + h (0,1) + h (1, -1) + h (1,0) + h ( 1,1) = 1 (8) In the present embodiment, a configuration is adopted in which a sharpening filter of a 3 * 3 matrix is applied to enhance the edge pixels. Of course, the sharpening filter is 3 *. The matrix is not limited to three matrices, but may be a 5 * 5 matrix as long as it satisfies Expression (8), that is, the condition that the sum of the coefficients of all the subdivisions becomes 1 is sufficient. . Then, the pixels to which the sharpening filter has been applied are stored as modified pixels (step S420).

If it is determined in step S410 that the characteristic flag is not an edge flag, it is determined whether the characteristic flag is a moire flag (step S425). If it is the moiré flag, the smoothing filter shown in FIG. 21 is applied to the pixel (step S430). This smoothing filter is formed by a 3 * 3 matrix, and has the same coefficient as the target pixel and the surrounding pixels in order to average the gradation of the target pixel and the surrounding pixels with the hatched small section. Set. The application of the smoothing filter can be represented by the following equation (9). Here, the gradation of the original pixel is set to a (N1, N2), and the output pixel after applying the smoothing filter is set to c (N1, N2).

[0083]

(Equation 2) Here, g (k1, k2) is obtained from the following equation (10) from FIG.
And (11). g (−1, −1) = 1/9, g (−1, 0) = 1/9, g (−1, 1) = 1/9, g (0, −1) = 1/9, g (0,0) = 1/9, g (0,1) = 1/9, g (1, -1) = 1/9, g (1,0) = 1/9, g (1,1) = 1/9 (10) g (-1, -1) + g (-1,0) + g (-1,1) + g (0, -1) + g (0,0) + g (0,1) + g (1, -1) + g (1,0) + g (1,1) = 1 (11) In the present embodiment, a 3 * 3 matrix smoothing filter is applied, and the moire pixels are averaged. Although the configuration is adopted, it goes without saying that the smoothing filter is not limited to the 3 * 3 matrix, and if the condition of Expression (11), that is, the condition that the sum of the coefficients of all subsections becomes 1, is satisfied, 5 * 5 A matrix may be used, or a coefficient may be appropriately weighted. For example, a low coefficient is set for peripheral pixels farther than the target pixel, and a large coefficient is set for peripheral pixels close to the target pixel. Of course,
The sum of the coefficients is set to 1. Then, the pixels to which the smoothing filter has been applied are stored as modified pixels (step S420).

On the other hand, if the characteristic flag is not a moiré flag in step S425, the pixel is determined to be an intermediate pixel, and the sharpening filter and the smoothing filter are not applied (step S435). That is, the gradation of the original pixel is held at the gradation of the output pixel. Then, this intermediate pixel is also stored as a modified pixel (step S420). Here, in executing the image data modifying process, if the selected attribute is RGB, it is necessary to execute the image data modifying process for each of RGB (Steps S440 and S44).
5). The determination of edge pixels, moiré pixels, and intermediate pixels as described above is performed for all pixels (step S45).
0), image data is generated by applying a sharpening filter and a smoothing filter to each pixel constituting the original image data (step S455).

Here, when performing image data modification processing applying each filter based on luminance data of each pixel, the gradation of the RGB data after the image data modification processing is set to R ′.
G'B ', and the gradation of the RGB data before modification is RGB. Further, assuming that the luminance after applying the sharpening filter and the smoothing filter to the luminance Y is Y ′, R′B′G ′
Can be calculated by the following equation (12). ΔY = Y′−Y R ′ = R + ΔY G ′ = G + ΔY (12) B ′ = B + ΔY On the other hand, when each filter is applied based on the RGB data of each pixel, each filter is applied directly to the RGB data. Therefore, R′G′B ′ that has been subjected to each filter becomes image data after modification as it is.

As described above, the image data acquired by the scanner processing is modified by applying a predetermined filter based on the determination of the pixel characteristic determination processing, so that the image data modification processing is performed in the image data modification step A3. Is configured. The image data generated by performing the image data modification process is subjected to a color conversion process and the like, sent to the color printer 40, and printed. Here, the processing contents of the image data conversion processing performed before the modified image data is sent to the color printer 40 are shown in the flowchart of FIG.

In the figure, first, image data modification processing is executed, and image data in which each pixel is composed of output gradation is input (step S505), and color conversion is performed (step S510). RGB2 image data is common
Assuming that there are 56 tones, the printer 50 needs two-level CMYK color image data for printing, so that color conversion and gradation conversion are required. Therefore, at step 510, R
The color image data of 256 gradations of GB is converted into the color image data of 256 gradations of CMYK. At this time, a color conversion process may be performed using a LUT based on a standard method. Next, the CMYK 256 gradations are half-toned into CMYK 2 gradations (step S515), and the half-toned print data is transmitted from the personal computer 10 to the printer 5 by parallel communication.
0 (step S520).

The color printer 40 inputs the print data and executes printing on a print medium. By the way, the positioning of the above-mentioned various programs is described in accordance with the flow of processing. However, since a plurality of devices execute at the same time, they are actually realized in various modes. Further, each program may be executed independently, or may be a part of another program. Furthermore, it is also possible to replace software processing with hardware processing, and in this sense, the term module refers to means common to both software and hardware.

As described above, the image data is acquired from the image input device such as the color scanner 20, the gradation difference between each pixel constituting the image data and the surrounding pixels is calculated, and the distribution of the gradation difference is calculated. Is created, and it is possible to determine whether each pixel is an edge pixel, a moiré pixel, or an intermediate pixel by collective processing based on the distribution. Then, according to the judgment, a sharpening filter is applied to an edge pixel, a smoothing filter is applied to a moiré pixel, and an image data modifying process is performed for an intermediate pixel to retain a tone of an original image. It becomes possible to carry out in a series of procedures. Therefore, it is possible to simplify the processing configuration of the image data modification processing executed from determination to modification, and to increase the processing speed. That is, the user of the color copying apparatus 10 can acquire a printed material of an appropriately modified image at a higher speed.

If the attribute is luminance data, after calculating the luminance from the RGB data of each pixel, each processing is performed on this luminance, so that the processing configuration can be simplified and the image data modification processing can be performed. Becomes faster. Further, when the attribute is RGB data, each process is performed on each RGB data of each pixel, so that the processing configuration becomes large and the processing speed of the image data modifying process becomes low. On the other hand, since the RGB data is reflected in the modification processing, the image quality of the image data obtained by the image data modification processing is made high. Therefore, the user selects luminance data in the image data attribute selection processing in step S150 when performing image data modification processing at high speed, and selects RGB data when obtaining high quality image output. , It is possible to realize desired image data modification processing.

[Brief description of the drawings]

FIG. 1 is a diagram corresponding to claims of an image data modifying method according to an embodiment of the present invention.

FIG. 2 is a schematic external view of a color copying apparatus applied for realizing the image data modifying method.

FIG. 3 is a schematic diagram illustrating a configuration of a scanner of the color copying apparatus.

FIG. 4 is a schematic block diagram showing a configuration of a copy server of the color copying apparatus.

FIG. 5 is a schematic block diagram showing a configuration of the copy server.

FIG. 6 is a schematic diagram showing a configuration of a color printer of the present color copying apparatus.

FIG. 7 is a schematic external view of a computer system showing a modification of the present color copying apparatus.

FIG. 8 is a flowchart showing an outline of a color copying process executed by the copy server;

FIG. 9 is a flowchart showing the contents of a scan process executed by the copy server.

FIG. 10 is a flowchart showing processing contents of image data attribute selection processing executed by the copy server.

FIG. 11 is a flowchart showing the contents of a tone difference calculation process executed by the copy server.

FIG. 12 is a diagram illustrating a process of creating a distribution from a tone difference in the tone difference calculation process.

FIG. 13 is a flowchart showing the details of a pixel characteristic determination process executed by the copy server.

FIG. 14 is a diagram illustrating an example of storing pixel characteristics.

FIG. 15 is a diagram illustrating another example of storing pixel characteristics.

FIG. 16 is a diagram illustrating a specific example of an edge pixel.

FIG. 17 is a diagram illustrating a specific example of a moiré pixel.

FIG. 18 is a diagram illustrating a specific example of an intermediate pixel.

FIG. 19 is a flowchart showing processing contents of image data modification processing executed by the copy server.

FIG. 20 is a diagram illustrating an example of a sharpening filter.

FIG. 21 is a diagram illustrating an example of a smoothing filter.

FIG. 22 is a flowchart showing processing contents of image data conversion processing executed by the copy server.

[Explanation of symbols]

 S100: Scan processing S150: Image data attribute selection processing S200: Tone difference calculation processing S300: Pixel characteristic determination processing S400: Image data modification processing S500: Image data conversion processing

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Claims (30)

[Claims] And determining a characteristic of each pixel in image data in which an image is expressed by multi-gradation using pixels in a dot matrix.
An image data retouching device that performs retouching for each pixel in accordance with its characteristics, wherein the image data retrieving means retrieves the image data, and targets each pixel of the image data acquired by the image data retrieving means. A pixel characteristic determining means for determining a distribution of a difference in tone value between the pixel and a neighboring pixel in a predetermined range around the pixel and comparing the distribution with a predetermined model distribution to determine the characteristic of the target pixel; An image data retouching device, comprising: image data retouching means for executing predetermined image processing corresponding to pixel characteristics determined by the pixel property determining means. 2. The image data modifying apparatus according to claim 1, wherein said pixel characteristic determining means uses a distribution in a range with a small difference and a distribution in a range with a large difference with each other. Image data retouching device. 3. The image data retouching device according to claim 2, wherein said pixel characteristic judging means uses a positive or negative bias of said distribution for judgment. 4. The image data retouching device according to claim 3, wherein said pixel characteristic determining means determines that an edge pixel is present when the distribution in the range where the difference is large is large and the distribution has a positive or negative bias. An image data retouching device characterized by determining. 5. The image data retouching device according to claim 4, wherein said image data retouching means executes sharpening image processing when said target pixel is determined to be an edge pixel. Image data retouching device. 6. The image data modifying apparatus according to claim 5, wherein the sharpening is formed in a matrix having a predetermined number of pixels centered on a target pixel, and the sharpening is performed at each pixel position of the matrix. An image data retouching device, which is executed by a sharpening filter in which a predetermined coefficient for enhancing a pixel is set. 7. The image data modifying apparatus according to claim 3, wherein said pixel characteristic determining means has a large distribution in a range where said difference is small, and a positive or negative bias is generated in said distribution. An image data retouching device, wherein a moiré pixel is determined when the image data is displayed. 8. The image data retouching device according to claim 7, wherein the image data retouching means executes smoothing image processing when the target pixel is determined to be a moiré pixel. Image data retouching device. 9. The image data modifying apparatus according to claim 8, wherein the smoothing is performed in a matrix having a predetermined number of pixels centered on a target pixel, and the target is located at each pixel position of the matrix. An image data modifying apparatus, wherein the image data modifying apparatus is executed by a smoothing filter in which a predetermined coefficient for substantially averaging pixels is set. 10. The image data retouching device according to claim 1, wherein said image data retouching means obtains a retouching value for a luminance value of said image data, and obtains a retouching value for each element color. An image data retouching device for retouching image data by adding the retouching value to a tone value. 11. An image data retouching method for judging characteristics of each pixel in image data in which an image is expressed by multi-gradation using pixels in a dot matrix, and performing retouching for each pixel in accordance with the characteristics. An image data obtaining step of obtaining the image data, and each pixel of the image data obtained in the image data obtaining step is set as a target pixel, and a distribution of a gradation value difference from a neighboring pixel in a predetermined range around the target pixel is calculated. A pixel characteristic determining step of determining the characteristics of the target pixel by comparing the distribution with a predetermined model distribution, and executing a predetermined image processing corresponding to the characteristics of the pixels determined in the pixel characteristic determining step An image data retouching step. 12. The image data retouching method according to claim 11, wherein in the pixel characteristic determining step, the distribution of the range with a small difference and the distribution of the range with a large difference are used for the determination. Image data modification method. 13. The image data modifying method according to claim 12, wherein in the pixel characteristic determining step, a positive or negative bias of the distribution is used for the determination. 14. The image data modifying method according to claim 13, wherein, in the pixel characteristic determination step, when the distribution in a range where the difference is large is large and the distribution has a positive or negative bias, the pixel is determined as an edge pixel. An image data retouching method characterized by determining. 15. The image data modifying method according to claim 14, wherein in the image data modifying step, a sharpening image process is executed when the target pixel is determined to be an edge pixel. Image data modification method. 16. The image data modifying method according to claim 15, wherein the sharpening is formed in a matrix having a predetermined number of pixels centered on the target pixel, and the sharpening is performed at each pixel position of the matrix. A method for modifying image data, which is performed by a sharpening filter in which a predetermined coefficient for enhancing a pixel is set. 17. The image data modifying method according to claim 13, wherein in the pixel characteristic determining step, a distribution in a range where the difference is small is large,
An image data retouching method characterized in that when the distribution has a positive or negative bias, it is determined to be an edge pixel. 18. The image data modifying method according to claim 17, wherein in the image data modifying step, smoothing image processing is executed when it is determined that the target pixel is a moiré pixel. Image data modification method. 19. The image data retouching method according to claim 18, wherein the smoothing is performed on a matrix having a predetermined number of pixels centered on a target pixel, and the target is located at each pixel position of the matrix. A method for modifying image data, which is performed by a smoothing filter in which a predetermined coefficient for substantially averaging pixels is set. 20. The image data retouching method according to claim 11, wherein in the image data retouching step, a retouching value for a luminance value of the image data is obtained, and a gradation value of each element color is obtained. An image data retouching method characterized by retouching image data by adding the retouch value to a tonal value. 21. An image data modifying program for judging characteristics of each pixel in image data in which an image is expressed by multi-gradation using pixels in a dot matrix and executing modification according to the characteristic for each pixel is recorded. A medium, an image data acquisition function for acquiring the image data, and each pixel of the image data acquired by the image data acquisition function as a target pixel, and a gradation value of a neighboring pixel in a predetermined range around the target pixel. A pixel characteristic determining function for determining the distribution of the difference, comparing the distribution with a predetermined model distribution, and determining a characteristic of the target pixel; and a predetermined characteristic corresponding to the characteristic of the pixel determined by the pixel characteristic determining function. A medium storing an image data modifying program for executing an image data modifying function for performing image processing. 22. A medium on which the image data modifying program according to claim 21 is recorded, wherein the pixel characteristic determining function uses the distribution of the range with a small difference and the distribution of the range with a large difference. A medium having recorded thereon an image data modifying program. 23. A medium on which the image data modifying program according to claim 22 is recorded, wherein said pixel characteristic determining function uses a positive or negative bias of said distribution for determination. The recorded media. 24. A medium on which the image data modifying program according to claim 23 is recorded, wherein the pixel characteristic determination function has a large distribution in a range where the difference is large, and the distribution has a positive or negative bias. A recording medium storing an image data modifying program, wherein the image data modifying program is determined to be an edge pixel. 25. A medium on which the image data modifying program according to claim 24 is recorded, wherein the image data modifying function executes sharpening image processing when it is determined that the target pixel is an edge pixel. A medium having recorded thereon an image data modification program. 26. A medium on which the image data modifying program according to claim 25 is recorded, wherein the sharpening is performed by:
It is formed by a sharpening filter which is formed in a matrix having a predetermined number of pixels centered on the target pixel and in which a predetermined coefficient for emphasizing the target pixel is set at each pixel position of the matrix. A medium on which an image data modification program is recorded. 27. In the medium on which the image data modifying program according to claim 23 or 24 is recorded, the pixel characteristic determination function has a large distribution in a range where the difference is small, and the distribution has a positive or negative sign. A medium on which an image data modifying program is determined to be a moiré pixel when a deviation occurs. 28. A medium on which the image data modifying program according to claim 27 is recorded, wherein the image data modifying function executes a smoothing image process when it is determined that the target pixel is a moiré pixel. A medium having recorded thereon an image data modification program. 29. A medium on which the image data modifying program according to claim 28 is recorded, wherein the smoothing is performed by:
It is formed by a smoothing filter that is formed in a matrix having a predetermined number of pixels centered on the target pixel, and in which a predetermined coefficient for substantially averaging the target pixel is set at each pixel position of the matrix. A medium on which an image data modification program is recorded. 30. A medium on which the image data modifying program according to claim 21 is recorded, wherein the image data modifying function obtains a modified value for a luminance value of the image data, A medium in which an image data modifying program is recorded, wherein the image data is modified by adding the modifying value to a gradation value of an element color.