JP2000013607A - Image processing utilizing gradation processing - Google Patents

Abstract

PROBLEM TO BE SOLVED: To relieve the definition deterioration of the entire image at the time of performing gradation processing of the image. SOLUTION: An outline map which separates an outline region that includes an outline included in a processing object image and expands around the outline from non-outline region and shows them is produced by processing the processing object image. And, 1st gradation processing whose gradation intensity is relatively high is preformed to an image part in the non-outline region according to the outline map and also 2nd gradation processing whose gradation intensity is relatively low is performed to an image part in the outline region.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a technique for performing image processing using a blurring process using a computer.

[0002]

2. Description of the Related Art A high-sensitivity film is often used for photographing a scene in which a subject moves fast or a dark scene.
However, photographs taken with high-sensitivity film generally have the property that the image is “coarse”. (The roughness of an image is also called “granularity.”) In particular, when a photographic image taken with a high-sensitivity film is enlarged, the granularity may become conspicuous.

[0003]

Heretofore, in order to reduce the graininess of a photographic image, there has been a case where the entire image is uniformly processed. Here, the blurring process is a process of blurring an image using an averaging filter or the like. But,
If the blurring process is performed uniformly on the entire image, the contour in the image (the contour of the subject) is also blurred, and the sharpness of the entire image is degraded.

[0004] Such a problem similarly occurs when a halftone image printed on a printing paper is read by a scanner and a blurring process is performed on the read image. The blurring process in this case is performed to remove a rosette pattern (turtle pattern) included in an image read by the scanner.

The present invention has been made to solve the above-mentioned problems in the prior art, and provides a technique capable of mitigating deterioration in sharpness of the entire image when performing blurring processing on the image. The purpose is to:

[0006]

In order to solve at least a part of the above problems, an image processing method according to the present invention is a method for processing an image to be processed using a computer. a) By processing the processing target image, a contour region including a contour included in the processing target image and extending around the contour is separated from a non-contour region which is a region other than the contour region. Creating a contour map to be shown; and (b) according to the contour map,
The first blur processing having relatively high blur intensity is performed on the image portion of the non-contour area in the processing target image, and the first blur processing is performed relatively on the image part of the contour area in the processing target image. Performing a second blurring process with low blurring strength.

In this image processing method, relatively strong blur processing is performed on a non-contour area, and relatively weak blur processing is performed on a contour area, so that the overall sharpness of an image to be processed is prevented from deteriorating. be able to. That is, it is possible to reduce the granularity and the rosette pattern (the turtle pattern) while alleviating the deterioration of the sharpness of the entire image.

The above-mentioned image processing method may further comprise a step (c) of performing a sharpness enhancement process on the blurred image obtained in the step (b).

This makes it possible to improve the sharpness of the entire image deteriorated by the blurring process.

The step (a) is performed by applying a first averaging filter to the image to be processed.
A process of generating an averaged image of the image, a process of obtaining the first difference pixel value by taking a difference between a pixel value of the image to be processed and a pixel value of the first averaged image, A process of creating the contour map by binarizing one difference pixel value with a predetermined threshold value may be substantially included.

In this case, the outline of the image to be processed is included,
A contour map representing a contour area extending around the contour can be successfully created.

The image to be processed includes a plurality of color components, and the first difference pixel value is calculated as a value proportional to a luminance value of a composite color composed of the plurality of color components. It may be.

When the first difference pixel value is calculated as a value corresponding to a luminance value, the outline region indicated by the outline map includes the outline better than the case where the first difference pixel value for each color component is used. Furthermore, a contour map can be created with higher accuracy.

In the above-mentioned image processing method, the first and second blurring processes are respectively performed by adding a second
A process of creating a second averaged image by applying the averaging filter, and taking a difference between a pixel value of the image to be processed and a pixel value of the second averaged image to obtain a second averaged image. A process of obtaining a difference pixel value, a process of determining a blur amount by multiplying the second difference pixel value by a predetermined adjustment coefficient, and a blur process by subtracting the blur amount from the pixel value of the processing target image And a process of creating a completed image. At this time, the first and second blurring processes are performed by setting at least one of the size of the second averaging filter and the size of the adjustment coefficient to a different value between the first and second blurring processes. Is set so that the blur intensity of the first blur process is higher than the blur intensity of the second blur process.

This makes it possible to adjust the blurring intensity of the first and second blurring processes to an appropriate value.

An image processing apparatus according to the present invention processes an image to be processed into an outline region including an outline included in the image to be processed and extending around the outline, and an area other than the outline region. A contour extraction unit for creating a contour map indicating the non-contour area, and a first image having a relatively high blur intensity for an image portion of the non-contour area in the processing target image according to the contour map. And a blur processing unit that performs a second blur process with relatively low blur intensity on the image portion of the contour area in the processing target image.

According to this image processing apparatus, it is also possible to reduce the graininess and the rosette pattern by using the blurring process while alleviating the deterioration of the sharpness of the entire image to be processed.

The recording medium according to the present invention is a computer-readable recording medium that records a computer program for processing an image to be processed by using a computer. A contour extraction function for creating a contour map that classifies a contour area including a contour included in a processing target image and extending around the contour, and a non-contour area other than the contour area; According to the map, a first blur processing having a relatively high blur intensity is performed on an image portion of the non-contour area in the processing target image, and an image part of the contour area in the processing target image is processed. Is a computer program for causing a computer to implement a blur processing function of performing a second blur processing having a relatively low blur strength. A computer-readable recording medium recording a beam.

When a computer program recorded on such a recording medium is executed by a computer,
The graininess and the rosette pattern (turtle pattern) can be reduced by the blurring process while alleviating the deterioration of the sharpness of the entire image to be processed.

[0020]

Other Embodiments of the Invention The present invention includes the following other embodiments. A first aspect is an aspect as a program supply device that supplies, via a communication path, a computer program that causes a computer to realize the functions of each step or each part of the above-described invention. In such an embodiment, the above-described method and apparatus can be realized by placing the program on a server or the like on a network, downloading the necessary program to a computer via a communication path, and executing the program.

[0021]

DETAILED DESCRIPTION OF THE INVENTION Configuration of Apparatus: Hereinafter, embodiments of the present invention will be described based on examples. FIG. 1 is a block diagram illustrating a configuration of an image processing apparatus according to a first embodiment of the present invention. This image processing apparatus includes a CPU 20 and an R
A computer including a main memory 22 including an OM and a RAM, a frame memory 26, a keyboard 30, a mouse 32, a display device 34, a hard disk 36, a modem 38, and a bus 40 connecting these components. It is. In FIG. 1, various interface circuits are omitted. The modem 38 is connected to a computer network via a communication line (not shown). The server (not shown) of the computer network
It has a function as a program supply device that supplies a computer program to an image processing device via a communication line.

The main memory 22 has a blur processing section 50.
And computer programs for realizing the functions of the contour extraction unit 52 and the sharpness enhancement processing unit 54, respectively. In the main memory 22, a contour map storage area 56 for storing a contour map created by the contour extracting unit 52 is also secured.

A computer program for realizing the functions of the processing units 50, 52, and 54 in FIG. 1 is provided in a form recorded on a computer-readable recording medium such as a flexible disk or a CD-ROM. The computer reads the computer program from the recording medium and transfers it to an internal storage device or an external storage device. Alternatively, a computer program may be supplied to a computer via a communication path. When implementing the functions of the computer program, the computer program stored in the internal storage device is executed by the microprocessor of the computer. Further, a computer may read a computer program recorded on a recording medium and directly execute the computer program.

In this specification, a computer is
The concept includes a hardware device and an operation system, and means a hardware device that operates under the control of the operation system. In the case where an operation system is unnecessary and a hardware device is operated by an application program alone, the hardware device itself corresponds to a computer. The hardware device includes at least a microprocessor such as a CPU and means for reading a computer program recorded on a recording medium. The computer program includes a program code that causes such a computer to realize the functions of the above-described units. Some of the functions described above may be realized by an operation system instead of the application program.

The “recording medium” in the present invention includes a flexible disk, a CD-ROM, a magneto-optical disk, an IC card, a ROM cartridge, a punch card, a printed matter on which a code such as a bar code is printed, and an internal storage of a computer. Device (RAM, ROM, etc.)
And various computer-readable media such as an external storage device.

B. FIG. 2 is a flowchart showing the overall processing procedure in the embodiment. In steps S1 to S3, the contour extraction unit 52 processes the image data representing the original image to be processed (also referred to as a “processing target image”), thereby forming a contour map indicating a contour region including a contour in the original image. Is the process of creating FIG. 3 is an explanatory diagram showing the processing contents of steps S1 to S3.

First, in step S1, a preliminary blurring process is performed on an original image according to Equation 1 to create an image for contour extraction.

[0028]

(Equation 1)

Here, So (i, j) is the pixel value of the original image (original pixel value), Sc (i, j) is the pixel value of the image for contour extraction (pixel value for contour extraction), and r is 1 or more. Is a predetermined integer. Although (i, j) is a coordinate value indicating a pixel position in an image, a symbol in which (i, j) is omitted in the following description may be used.

The preliminary blurring process given by Equation 1 is an averaging process using a simple averaging filter having one side of (2r + 1) pixels (also called a “smoothing filter”). In this embodiment, the value of the integer r is set to 3, for example.

FIG. 3A shows an original image, and FIG. 3B shows an image for contour extraction. The original image has a left half first region R1 and a right half second region R1.
It is divided into two. The outline OL of the second region R2 is
It corresponds to the boundary between the first and second regions R1 and R2. The first region R1 is a region having a relatively low density, and includes several island-like noises (high-density portions) therein. Second
Is a region having a relatively high density. The second region R2 may also include some noises (low density portions). In addition, since an image or a photographic image obtained by reading a printed matter with a scanner is actually used as an original image,
The contents of the image are more complicated, but are simplified in FIG. 3 for convenience of illustration.

When the original image is a color image, the pixel value of each pixel in the original image is composed of a plurality of color components. For example, each pixel value may be composed of three RGB color components, or may be composed of four CMYK color components. In the processing of this embodiment, the same processing is executed for each of these color components unless otherwise specified.

As shown in FIG. 3B, the contour extracting image includes a contour area OLAa between the first and second areas R1a and R2a. The outline region OLAa is a region extending around the outline OL in the original image substantially at the center. Note that in FIG. 3B, the outline area OLAa
And the boundaries between the region and other surrounding regions R1a and R2a are clearly drawn, but in reality, these boundaries are ambiguous.

The reason why a preliminary blurring process is performed to create an image for contour extraction is to reduce noise included in the original image so that the contour of the noise portion is not extracted. However, it is also possible to omit step S1 and use the original image as it is as an image for contour extraction.

In step S2 of FIG.
Creates a contour map by processing the contour extraction image. FIG. 4 is a flowchart showing a detailed procedure of step S2. First, in step S11, a first averaged pixel value Sm1 is obtained by applying a first averaging filter to the contour extraction pixel value Sc according to the following Expression 2.

[0036]

(Equation 2)

Here, p is an integer of 1 or more, for example, a value of about 1 to 3 is preferable. In this embodiment, the integer p is set to 3
Is set to That is, the first averaging filter used in Expression 2 is a simple averaging filter having seven pixels on one side.

In step S12, the contour extraction pixel value Sc and the first averaged pixel value Sm1 are calculated according to the following equation (3).
(First difference) d1 is calculated.

[0039]

(Equation 3)

The first difference d1 is calculated for each color component. For example, the first for the three color components of RGB
Are written as d1 _R , d1 _G and d1 _B , respectively.

In step S13, from the first differences d1 _R , d1 _G and d1 _B of the respective color components, a value proportional to the luminance value of the composite color reproduced by these color components (referred to as “difference luminance value”). Is required. The difference luminance value i_dif is calculated according to, for example, the following Expressions 4 and 5.

[0042]

(Equation 4)

[0043]

(Equation 5)

K on the right side of Equation 4 is a coefficient, and in this embodiment, k = 12. Any value including 1 can be used as the value of k.

Instead of obtaining the difference luminance value i_dif from the first difference relating to a plurality of color components, a value corresponding to the luminance value (“pixel luminance value”) is used as the contour extraction pixel value Sc.
May be obtained in advance, and the processes of steps S11 and S12 described above may be performed on the pixel luminance value Sc.

FIG. 3C shows the distribution of the difference luminance value i_dif. Since the difference luminance value i_dif corresponds to the difference between the pixel value Sc for contour extraction and the first averaged pixel value Sm1, the pixel value Sc for contour extraction and the first averaged pixel value Sm1 are substantially the same. , The difference luminance value i_dif is almost 0. Therefore, in a significant part of the first and second regions R1b and R2b, the difference luminance value i_
dif is a value close to 0. On the other hand, the outline area OL
The difference luminance value i_dif between Ab and the island-shaped noise portion in the first region R1b is maintained at a slightly high value. Note that the contour area OLAb in FIG.
It is slightly wider than the contour area OLAa in FIG.

In step s14 of FIG. 4, the difference luminance value i
An outline map map is created by binarizing _dif with a predetermined threshold Th. That is, the contour map map is determined as in the following Expression 6.

[0048]

(Equation 6)

As the threshold value Th, for example, the range of the difference luminance value i_dif is 0 to 255 (ie, 8 bits)
In this case, a value of about 100 is appropriate.

In FIG. 3C, the difference luminance value i_dif of the image portion (the outline portion OLAb and the noise portion in the first region R1b) indicated by the sand is larger than the threshold value Th. The contour map m
The value of ap becomes 1. On the other hand, in the image area other than the outline area OLAb and the noise part, the value of the outline map map is 0. As described above, the contour map map is data representing the contour area OLAb which is an area including the contour OL of the original image, but may include noise of the original image.

In step S3 in FIG. 2, a final contour map map * from which noise has been removed is obtained by applying a median filter to the contour map map obtained in step S2. Here, the “median filter” is a filter that employs a value located at the center of the array when a plurality of values existing in the area of the filter are arranged in order of magnitude. For example, when a median filter of 3 × 3 pixels is used, the fifth value among the nine values included therein is adopted. Note that the contour map ma
Since the value of p is 0 or 1, the value resulting from applying the median filter is also 0 or 1. FIG. 3D shows the contour map map * after noise removal. In this contour map map *, the first region R1 shown in FIG.
It can be seen that the noise included in b has been removed.

As can be seen by comparing FIG. 3A and FIG. 3D, the final value of the contour map map * is determined by comparing the contour included in the original image and the area around the contour. It is 1 in the included outline area OLAc, and is 0 in the non-outline areas R1c and R2c which are areas other than the outline area. That is, the contour map map * is information indicating the contour area OLAc and the non-contour areas R1c and R2c separately.

As described above, in this embodiment, the outline map map * is determined using the difference luminance value i_dif, but the first differences d1 _R and d1 for each color component are determined.
_G, a portion of d1 _B may be determined a contour map map * using. However, if the contour map is created from the difference luminance value i_dif, the contour map map
The outline OL of the original image is included in the outline area OLAc represented by *.
Contour map m with higher accuracy so that
The advantage is that ap * can be created.

In steps S4 and S5 of FIG. 2, the blur processing section 50 executes the first and second blur processing on the non-contour areas R1c and R2c and the contour area OLAc in the original image according to the contour map map *, respectively. I do. FIG. 5 is a flowchart showing a detailed procedure of the processing in steps S4 and S5. In steps S4 and S5, step S in FIG.
Since the processes of S21 to S24 are respectively executed, the contents of steps S4 and S5 will be described together below.

In step S21, a second averaging filter is applied to the pixel value (original pixel value) So of the original image according to Equation 7 to obtain a second averaged pixel value Sm2.

[0056]

(Equation 7)

Here, q is an integer of 1 or more, and for example, a value of about 1 to 3 is preferable. In the present embodiment, the first blur processing for the non-contour areas R1c and R2c (step S
In 4), the integer q is set to 3 and the contour area OLAc
In the second blur processing (step S5) for
Is set to 2. In general, the greater the value of the integer q, the higher the blur intensity. Therefore, the non-contour areas R1c, R
The blur processing is performed with 2c with a higher blur intensity than the contour area OLAc. The “blur intensity” means the degree to which an image is blurred by the blur processing.

In step S22, a difference (second difference) d2 between the original pixel value Sc and the second averaged pixel value Sm2 is calculated according to the following equation (8).

[0059]

(Equation 8)

In step S23, the blur amount G is determined by multiplying the second difference d2 by the adjustment coefficient m as shown in the following equation (9).

[0061]

(Equation 9)

In this embodiment, the non-contour areas R1c, R2c
In the blur processing (step S4), the value of the adjustment coefficient m is set to 0.7, and in the blur processing of the contour area OLAc (step S5), the value of the adjustment coefficient m is set to 0.5. In general, the larger the value of the adjustment coefficient m, the larger the blur amount G and the higher the blur intensity. Accordingly, in the present embodiment, the non-contour areas R1c and R2c are more suitable for the contour area OLA.
The image will be blurred with a blur intensity higher than c. The adjustment coefficient m is preferably a value less than 1, but may be set to a value of 1 or more.

In step S24, the blurred pixel value Sgr is obtained by subtracting the blur amount G from the original pixel value So according to the following equation (10).

[0064]

(Equation 10)

Expressions 8 to 10 can be summarized into the following Expression 11.

[0066]

[Equation 11]

Therefore, the processing of steps S22 to S24 in FIG. 5 can be realized by one processing using equation (11). In this case, one process using Expression 11 substantially includes the processes of steps S22 to S24. As can be seen from this example, it is also possible to combine the processes of several steps of the above-described embodiment so that one step substantially includes some processes.

When obtaining the blurred pixel value Sgr, the blur strength is set high in the non-contour areas R1c and R2c (FIG. 3D), while the blur strength is set low in the contour area OLAc. . Therefore, the sharpness is degraded in the contour area OLAc of the blurred image, and the contour OL is reduced.
(FIG. 3A) is prevented from being unclear,
In the non-contour areas R1c and R2c, the graininess and the rosette pattern (turtle pattern) are reduced. In particular,
In the present embodiment, since the region extending around the outline OL is extracted as the outline region OLAc, the outline OL is extracted.
There is an advantage that the image between the contour region and the non-contour region looks smoother than when the blur intensity is reduced only in the portion. The width of the outline region OLAc can be adjusted by adjusting the size of the first averaging filter used in step S11 of FIG.

As described above, the blur intensity is determined by the size of the averaging filter used in step S21,
The value can be adjusted with the two values of the adjustment coefficient m used in step S23. Therefore, as one of these two values, a value common to the non-contour area and the contour area can be used. In other words, by setting at least one of these two values to be different from each other in the non-contour area and the contour area, it is possible to adjust the blur intensity.

When the blur processing in steps S4 and S5 is completed in this way, in step S6 in FIG. 2, the sharpness enhancement processing section 54 executes the sharpness enhancement processing (sharpness processing) on the entire image after the blur processing. I do. As described above, if the sharpness enhancement processing is performed after the blur processing, the sharpness deteriorated by the blur processing can be improved. Note that the sharpness enhancement processing is a well-known processing in the technical field of image processing, and thus details thereof are omitted.

As described above, according to the present embodiment,
Since the strong blur processing is performed on the non-contour area in the original image and the weak blur processing is performed on the contour area, the phenomenon that the sharpness of the entire image is deteriorated by the blur processing can be reduced. There is an advantage.

It should be noted that the present invention is not limited to the above-described examples and embodiments, but can be implemented in various modes without departing from the scope of the invention.
For example, the following modifications are possible.

(1) In the above embodiment, part of the configuration realized by hardware may be replaced by software, and conversely, part of the configuration realized by software may be replaced by hardware. You may do so.

(2) In the above embodiment, the simple averaging filter was used as the averaging filter.
A weighted average filter may be used. Further, it is also possible to use an algorithm other than the algorithm used in the above-described embodiment as an algorithm of the blur processing.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of an image processing apparatus as a first embodiment of the present invention.

FIG. 2 is a flowchart showing an overall processing procedure in the embodiment.

FIG. 3 is an explanatory diagram showing processing contents of steps S1 to S3.

FIG. 4 is a flowchart showing a detailed procedure of step S2.

FIG. 5 is a flowchart showing a detailed procedure of steps S4 and S5.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 20 ... CPU 22 ... Main memory 26 ... Frame memory 30 ... Keyboard 32 ... Mouse 34 ... Display device 36 ... Hard disk 38 ... Modem 40 ... Bus 50 ... Blur processing part 52 ... Contour extraction part 54 ... Sharpness enhancement processing part 56 ... Contour Map storage area

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 5B057 BA29 CA01 CA08 CA16 CB01 CB08 CB16 CC03 CE03 CE04 CH09 DA08 DC16 DC32 5C076 AA01 AA31 BA06 CA10 5C077 LL20 MP07 MP08 PP01 PP03 PP19 PP27 PP41 PP47 PP68 PQ08 PQ22 RR02RR

Claims (7)

[Claims] 1. A method of processing an image to be processed using a computer, comprising: (a) processing the image to be processed to include a contour included in the image to be processed and spread around the outline; A step of creating a contour map indicating the contour area and a non-contour area other than the contour area; and (b) an image of the non-contour area in the processing target image according to the contour map. Performing a first blur process with relatively high blur intensity on the portion and performing a second blur process with relatively low blur intensity on the image portion of the contour region in the processing target image An image processing method comprising: 2. The image processing method according to claim 1, wherein:
And (c) performing a sharpness enhancement process on the blurred image obtained in the step (b). 3. The image processing method according to claim 1, wherein in the step (a), a first averaged image is created by applying a first averaging filter to the image to be processed. A process of obtaining the first difference pixel value by calculating a difference between a pixel value of the processing target image and a pixel value of the first averaged image; and calculating the first difference pixel value. An image processing method substantially including a process of creating the contour map by binarizing the image with a predetermined threshold value. 4. The image processing method according to claim 3, wherein the processing target image includes a plurality of color components, and the first difference pixel value is a composite color including the plurality of color components. The image processing method is calculated as a value proportional to the luminance value of. 5. The image processing method according to claim 1, wherein the first and second blurring processes respectively apply a second averaging filter to the processing target image. And a process of obtaining a second difference pixel value by calculating a difference between a pixel value of the processing target image and a pixel value of the second averaged image. A process of determining a blur amount by multiplying the second difference pixel value by a predetermined adjustment coefficient; and a process of creating a blur-processed image by subtracting the blur amount from a pixel value of the processing target image. The first and second blurring processes substantially include at least one of the size of the second averaging filter and the size of the adjustment coefficient, in the first and second blurring processes. Different values for processing The image processing method is adjusted so that the blur intensity of the first blur process is higher than the blur intensity of the second blur process. 6. An image processing apparatus for processing a processing target image, wherein the processing target image is processed, and a contour region including a contour included in the processing target image and extending around the contour is provided. A contour extraction unit that creates a contour map indicating the non-contour area that is an area other than the contour area, and compares the non-contour area image portion in the processing target image according to the contour map. A blur processing unit that performs a first blur processing with a high target blur strength and performs a second blur processing with a relatively low blur strength on an image portion of the contour area in the processing target image. Image processing device. 7. A computer-readable recording medium that records a computer program for processing a processing target image using a computer, wherein the processing target image is processed to be included in the processing target image. A contour extraction function for creating a contour map that divides a contour area including a contour and extending around the contour, and a non-contour area other than the contour area; and the processing target image according to the contour map. The first blur processing having a relatively high blur intensity is performed on the image portion of the non-contour region in the image, and the blur intensity is relatively low on the image portion of the contour region in the processing target image. A computer-readable recording program for causing a computer to realize a blur processing function for performing a second blur processing; Recording medium that can be taken.