JP2000101841A - Image processor, its method and computer readable storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To freely adjust a width of a density distribution of an input image while amplitude of high frequency components of the received image is kept. SOLUTION: A pixel value fd(x, y) of a processed image, a pixel value fuso(x, y) of a smoothed image of a 1st image f0(x, y) (transformed image resulting from application of a gradation transformation to input image), a pixel value f1(x, y) of a 2nd image (input image), a pixel value fus(x, y) of a smoothed (low frequency) image of the 2nd image, a function F() controlling the processing effect and coordinated x, y on the image are used. Then image processing by means 101-106 is conducted so as to hold an arithmetic equation of fd(x, y)=fuso(x, y)+F(f1(x, y)×(f1(x, y))-fus(x, y)).

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing apparatus and method for performing gradation conversion while maintaining high-frequency components of an image such as an X-ray image, and a computer-readable storage medium used for the method. .

[0002]

2. Description of the Related Art For example, an X-ray chest image is composed of an image of a lung field through which X-rays are easily transmitted and an image of a mediastinum which is very hardly transmitted by X-rays. Is very wide. For this reason, it has been considered difficult to obtain an X-ray chest image that allows simultaneous observation of both the lung field and the mediastinum.

Therefore, as a method for avoiding this problem,
Conventionally, the following various methods have been proposed. First, SPIEVol. 626. MedicineXIV
/ PACSIV (1986).
This method uses a pixel value S _D after processing, an original pixel value (input pixel value) S _ORG , a pixel value S _US of a low-frequency image of the original image (input image), constants A, B, and C (for example, A = 3,
B = 0.7), and _SD = A [S _ORG −S _US + B (S _US )] + C─── (1).

In this method, the weighting of the high frequency component (first term) and the low frequency component (second term) can be changed. For example, when A = 3 and B = 0.7, the high frequency component is emphasized, and The effect of compressing the entire dynamic range can be obtained. This method has been evaluated by five radiologists as being more effective for diagnosis than unprocessed images.

[0005] Japanese Patent No. 2509503 discloses a processed pixel value S _{D an} original pixel value (input pixel value) S
_ORG , using the average profile Py of the Y direction profile of the original image (input image) and the average profile Px of the X direction profile, _SD = S _ORG + F [G (Px, Py) ─── (2) Formula (2) Are described.

Here, characteristics of the function f (x) will be described. First, when "x>Dth", f (0) becomes "0", and when "0≤x≤Dth", f (x) monotonically decreases as the intercept is "E" and the slope is "E / Dth". , (3). F [x] = E− (E / th) X── (3) Py = (ΣPii) / n───── (4) Px = (ΣPxi) / n───── (5) (I = 1 to n), Pyi and Pxi are profiles. Then, for example, G = (Px, Py) = max (px, py) ６ (6). In this method, a density range of a pixel value Dth or less of a low-frequency image is compressed.

[0007] As a method similar to the above publication, a "self-compensating digital filter" (National Cancer Center, Mr. Anan et al., Journal of the Japanese Society of Radiological Technology, Vol. 45, No. 8, 1989)
August, 1030). This method uses a pixel value S _D after compensation (after processing), an original pixel value (input pixel value) S _ORG , and an average pixel when an original image (input image) is subjected to a moving average with a mask size of M × M pixels. Using the value S _US and the monotonically decreasing function f (X) of FIG. 16, the following equation is obtained: S _D = S _ORG + f (S _US ) ─── (7) S _US = {S _ORG / M ² } (8) 7) and (8).

[0008] Here, to describe the characteristics of the function f (S _US) has, first, characteristics shown in FIG. 16, "S _US>
BASE ”, f (S _US ) becomes“ 0 ”and“ 0 ≦ S _US ”
≦ BASE ”, f (S _US ) sets the intercept to“ threshold BAS
E "and the slope" SLOPE "monotonically decrease. Accordingly, when the above equation (7) is executed with the original pixel value S _ORG as the density equivalent amount, an effect on the image is obtained in which the density is increased at a low average density of the image.

This method is different from the above equation (2) in the method of creating a low-frequency image. In the equation (2), a low-frequency image is created using one-dimensional data. This is for creating an image. This method also compresses a density value equal to or lower than Dth with a pixel value of a low-frequency image.

[0010] Also, Japanese Patent No. 2663189 discloses that
With the monotone increasing function f1 (X), there is described a method represented by S _D = S _ORG + f 1 (S _US ) ─── (9) S _US = {S _ORG / M ² ──── (10) .

Here, the characteristics of the function f1 (x) will be described. First, when "x <Dth", f1 (x) becomes "0", and when "Dth≤x", f1 (x) monotonically decreases as the intercept is "E" and the slope is "E / Dth". 11) It is represented by the formula. f1 [x] = E− (E / th) X── (11)

Japanese Patent No. 1530832 discloses that
A sharpening method for enhancing high-frequency components of an image having a certain density value or more is shown. This method emphasizes ultra-low frequency components, relatively reduces high-frequency components where noise occupies a large proportion, provides an image that is easy to see visually, prevents false images, and prevents noise. The purpose is to prevent the increase and improve the diagnostic performance.

The constant B is a variable that monotonically increases as the value of S _OR or S _US increases, and S _D = S _ORG + B (S _ORG −S _US ) ─── (12) S _US = ΣS _ORG / M ²も の (13) There is a formula represented by the formulas (12) and (13). When the above equation (12) is executed, there is an effect that the high frequency component of the image can be emphasized.

[0014]

However, the above-mentioned SPIEVo 1.626. MedicineXIV /
In the method described in PACSIV (1986), there is no idea to compress the dynamic range of a certain density range, so that the dynamic range of the entire image is compressed uniformly.
Therefore, it is not possible to compress only a certain concentration range,
Therefore, for example, when the present method is used for a lung frontal image, there is a problem that not only the mediastinal region but also the lung density range effective for diagnosis is compressed, which is more than the case where only the mediastinal region is compressed. There was a problem that the diagnostic ability was reduced.

The above-mentioned "self-compensating digital filter"
In the method according to the above-mentioned method, there is a problem that an unnatural distortion occurs in the high-frequency component unless the shape of the function f (S _US ) is reduced at a fixed ratio, for example, up to BASE (need to be linear). Therefore, there is a problem that the gradation cannot be freely and non-linearly compressed while maintaining the amplitude of the high-frequency component at the amplitude of the high-frequency component of the original image (input image).

In general, an image which has been subjected to dynamic range compression is subjected to gradation conversion again when CRT display and film output are performed. In the method using the “self-compensating digital filter” and the like, there is no idea to adjust the amplitude of the high-frequency component of the image after gradation conversion. Tone conversion is performed. Therefore, the amplitude of the high-frequency component varies depending on the gradient of the gradation conversion curve. Therefore, there is a problem that the amplitude after gradation conversion is nonlinearly distorted, and even if dynamic range compression is performed while maintaining the amplitude of the high-frequency component, the amplitude of the high-frequency component becomes small where the gradient of the gradation conversion curve is low. However, there is a problem that useful information is lost. In addition, there is a problem that overshoot and undershoot occur at the edge portion.

In the conventional sharpening method for emphasizing high-frequency components, the strength of addition of high-frequency components can be freely adjusted. However, there is no idea to compress the dynamic range, and one image having a wide density distribution can be obtained. There was a problem that it could not be displayed on such a film.

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems, and has as its object to enable the width of the density distribution of an image and the amplitude of a high frequency component to be freely adjusted.

[0019]

In order to achieve the above object, in an image processing apparatus according to the present invention, a gradation conversion means for converting a gradation of an input image to obtain a converted image, and a smoothing means for smoothing the converted image. A first smoothing unit that obtains a first smoothed image by using the input image and the second smoothed image; a second smoothing unit that smoothes the input image to obtain a second smoothed image. Subtraction means for calculating the difference between the two, a multiplication means for multiplying the output of the subtraction means by a constant, and an addition means for adding the output of the multiplication means and the first smoothed image.

In another image processing apparatus according to the present invention, a smoothing means for smoothing an input image to obtain a smoothed image, a tone converting means for tone-converting the smoothed image to obtain a converted image, Subtraction means for calculating the difference between the input image and the smoothed image, multiplication means for multiplying the output of the subtraction means by a constant, and addition means for adding the output of the multiplication means and the converted image are provided. ing.

Further, in another image processing apparatus according to the present invention, there is provided a gradation conversion means for converting a gradation of an input image to obtain a converted image, a smoothing means for smoothing the input image to obtain a smoothed image, Subtraction means for calculating the difference between the input image and the smoothed image, multiplication means for multiplying the output of the subtraction means by a constant, and addition means for adding the output of the multiplication means and the converted image are provided. I have.

In another image processing apparatus according to the present invention, there is provided a gradation converting means for converting a gradation of an input image to obtain a converted image, and a first converting means for smoothing the converted image to obtain a first smoothed image. A second smoothing means for smoothing the input image to obtain a second smoothed image; a subtracting means for calculating a difference between the input image and the second smoothed image; Multiplying means for multiplying the output of the means by a constant, and adding means for adding the output of the multiplying means and the first smoothed image are provided.

In another image processing apparatus according to the present invention, a gradation conversion means for converting a gradation of an input image to obtain a converted image, and a differential coefficient of a gradation conversion curve used in the gradation conversion means are provided. Storage means for storing; smoothing means for obtaining a smoothed image by smoothing the converted image; calculating means for calculating a difference between the smoothed image and the converted image to obtain a high-frequency component; Adding means for adding a component to the converted image based on the stored differential coefficient.

In another image processing apparatus according to the present invention, a gradation conversion means for converting a gradation of an input image to obtain a converted image, and a differential coefficient of a gradation conversion curve used by the gradation conversion means are used. Storage means for storing; a smoothing means for smoothing the input image to obtain a smoothed image; a calculating means for calculating a difference between the smoothed image and the input image to obtain a high-frequency component; Adding means for adding a component to the converted image based on the stored differential coefficient.

Further, in the image processing method according to the present invention, a converted image f0 (x, y) obtained by performing gradation conversion on an input image or the like.
And a high-frequency component obtained by subtracting the smoothed image of the input image from the input image, or the like, to the input image or the like. They will be added accordingly.

In the storage medium according to the present invention,
A gradation conversion process for converting the input image to obtain a converted image;
A first smoothing process for smoothing the converted image to obtain a first smoothed image; a second smoothing process for smoothing the input image to obtain a second smoothed image; A program for executing a subtraction process of subtracting the second smoothed image, a multiplication process of multiplying the subtraction output by a constant, and an addition process of adding the multiplication output and the first smoothed image are stored. are doing.

[0027] In another storage medium according to the present invention, a smoothing process for smoothing an input image to obtain a smoothed image;
A tone conversion process for converting the smoothed image into a tone to obtain a converted image; a subtraction process for subtracting the smoothed image from the input image; a multiplication process for multiplying an output of the subtraction process by a constant; And a program for executing an addition process of adding the conversion image and the converted image.

In another storage medium according to the present invention, a gradation conversion means for converting a gradation of an input image to obtain a converted image, a smoothing process for smoothing the input image to obtain a smoothed image, A program for executing a subtraction process of subtracting the smoothed image from the image, a multiplication process of multiplying the subtraction output by a constant, and an addition process of adding the multiplication output and the conversion image are stored. .

Further, in another storage medium according to the present invention, a gradation conversion process for converting a gradation of an input image to obtain a converted image, and a first conversion processing for smoothing the converted image to obtain a first smoothed image. A smoothing process, a second smoothing process for smoothing the input image to obtain a second smoothed image, a subtraction process for subtracting the second smoothed image from the input image, and a constant for the subtraction output. A program for executing multiplication processing for multiplication and addition processing for adding the multiplied output and the first smoothed image is stored.

In another storage medium according to the present invention, a tone conversion process for converting a tone of an input image using a tone conversion curve to obtain a converted image, and a smoothing image by smoothing the converted image. And a subtraction process of calculating a difference between the smoothed image and the converted image to obtain a high-frequency component,
A program for executing an adding process of adding the calculated high-frequency component based on the differential coefficient of the gradation conversion curve is stored.

Further, in the storage medium relating to each of the above-described image processing methods according to the present invention, a converted image f0 (x, y) obtained by gradation-converting an input image or the like or a smoothed image fuso thereof
For (x, y) and the like, a high-frequency component obtained by subtracting a smoothed image of the input image from the input image or the like is multiplied by a predetermined number, or a high-frequency component is added according to the input density or the like. A program to be executed is stored.

[0032]

Embodiments of the present invention will be described below with reference to the drawings. First, a first embodiment will be described.
FIG. 2 shows the gradation conversion function F used in the first embodiment.
1 () is shown. Here, f1 (x, y) is the density value of the two-dimensional input original image, f0 (x, y) is the density value of the output image (converted image) after the two-dimensional gradation conversion, and x, y 2
It is a coordinate on a dimension. The horizontal axis represents the density value f of the input image.
1 (x, y), the vertical axis represents the density value f of the output image (converted image)
0 (x, y). In this gradation conversion curve, the slope (SLOPE) below the input density value 2500 is 0.2, and the slope above the input density value 2500 is 1.

In FIG. 3, the solid line is the profile of the input image, f1 (X), and the dotted line is the smoothing (low frequency) of the input image.
The profile fus (X) of the image fus (x, y) is shown. 4, a solid line indicates a profile f0 (X) of an image obtained by performing gradation conversion on the input image using the gradation conversion curve shown in FIG.
A dotted line indicates a profile fuso (X) of a smoothed (low frequency) image of the image whose gradation has been converted. Here, X is a constant. FIG. 5 shows the result of the image processing method according to the present embodiment. The solid line indicates the profile f1 (X) of the input image, and the dotted line indicates the profile fd (X) of the processed image processed according to the present embodiment.

Next, the operation will be described. First, the input image f1 (x, y) is subjected to gradation conversion by the gradation conversion function F1 () shown in FIG.
(X, y) is obtained. f0 (x, y) = F1 (f1 (x, y)) (14)

The pixel value fd (x, y) of the processed image can be obtained according to equation (5). Here, F (x, y) is a function representing a processing effect depending on coordinates.
(X, y) = 1. fd (x, y) = fuso (x, y) + F (x, y) × (f1 (x, y) −fus (x, y)) ─── (15)

Here, fuso (x, y) is a smoothed (low frequency) image of the output image (converted image) f0 (x, y),
fus (x, y) is a smoothed (low frequency) image of the input image f1 (x, y), and is, for example, (16) to (2) described later.
0). Even if the average density is used for smoothing,
Erosion, Dai1ation, 0 penin
A morphological filter such as g, Clossing may be used.

The gradation conversion curve F used in this embodiment
1 () (FIG. 2), the amplitude of the high-frequency component having a density value of 2500 or less in the output image f0 (x, y) is compressed to 20%,
If the density value is higher than 2500, the amplitude of the input image is preserved as the amplitude of the high frequency component (solid line in FIG. 4).

The calculation method of fus (x, y) is (1)
6) to (20). Assuming that f1 (x, y) is a two-dimensional input original image, f2 (x, y) = min {f1 (x + x1, y + y1) -D (x1, y1) | x1 × x1 + y1 × y1 ≦ r1 × r1} {(16) f3 (x, y) = max {f2 (x + x1, y + y1) + D (x1, y1) | x1 × x1 + y1 × y1 ≦ r1 × r1} (17) f4 (x, y) = max {f3 (x + x1, y + y1) + D (x1, y1) | x1 * x1 + y1 * y1≤r1 * r1} (18) fus (x, y) = min @ f4 (x + x1, y + y1) -D (x1 , Y1) | x1 × x1 + y1 × y1 ≦ r1 × r1} (19)

Here, D (x, y) is a disc-shaped filter,
r1 is an arbitrary constant, and is selected according to the input image.

The obtained profile fus (x, y) fus (X) (dotted line in FIG. 3) preserves the edge structure, and has the disadvantages of the conventional dynamic range compression such as overshoot and undershoot. Shooting does not occur.

Similarly, the calculation method of fuso (x, y) is expressed by equations (21) to (24). is there. Let f0 (x, y) be the image after gradation conversion. f5 (x, y) = min {f0 (x + x1, y + y1) -D (x1, y1) | x1 × x1 + y1 × y1 ≦ r1 × r1} (21) f6 (x, y) = max ｛f5 ( x + x1, y + y1) + D (x1, y1) | x1 × x1 + y1 × y1 ≦ r1 × r1｝ (22) f7 (x, y) = max ｛f6 (x + x1, y + y1) + D (x1, y1) | x1 × x1 + yl × y1 ≦ r1 × r1} {(23) fuso (x, y) = min} f8 (x + x1, y + y1) −D (x1, y1) | x1 × x1 + y1 × y1 ≦ r1 × r1} ─ (24)

The obtained profile fuso (X, y) of fuso (x, y) (dotted line in FIG. 4) preserves the edge structure, and the position of the intersection with f0 (X) is f
It is the same point as the intersection point between us (X) and f1 (X).

The dotted line in FIG. 5 is the profile fd (X) of the processed image fd (x, y) obtained. The density distribution width having a density value of 2500 or less is compressed to 20% of the input image, and the amplitude of the high frequency component holds the amplitude of the input image.

FIG. 1 is a block diagram showing the configuration of the image processing apparatus according to the present embodiment, and realizes the above-mentioned expression (15). In FIG. 1, the input image f1 is subjected to gradation conversion by the gradation conversion means 101 based on the function in FIG. 2, and a converted image f0 is obtained. The converted image f0 is then smoothed by the smoothing means 102 to obtain a smoothed image fuso, which is sent to the adding means 103.

On the other hand, the input image f1 is processed by another smoothing means 1.
04 and becomes a smoothed image fus. Next, in the subtraction means 105, the smoothed image f
By subtracting us, a high-frequency component image is obtained. This high-frequency component image is multiplied by a constant by a multiplication unit 106, and then added to the smoothed image fu by an addition unit 103.
By adding to so, a processed image fd is obtained.

As described above, according to the first embodiment, the density distribution width of an arbitrary gradation area of an input image can be compressed and expanded, and the amplitude of the high-frequency component after gradation conversion can be reduced. There is an effect that can be adjusted freely.

Next, a second embodiment will be described. FIG.
Indicates a gradation conversion function F1 () used in the image processing method according to the second embodiment. Here, f1 (x, y) is 2
The density value of the two-dimensional input original image, the smoothed (low frequency) image of the input image is fus (x, y), and the output image (converted image) after gradation conversion is fus0 (x, y).

Next, the operation will be described. First, a smooth image fus (x, y) of the input image f1 (x, y) is created by, for example, equations (16) to (20), and the tone conversion function F1 () shown in FIG. Perform tone conversion as shown,
An output image fus0 (x, y) is obtained. fus0 (x, y) = F1 (fus (x, y)) (25)

The pixel value fd (x, y) of the processed image can be obtained according to equation (26). Here, F (x, y) is a function representing a processing effect dependent on coordinates. fd (x, y) = fus0 (x, y) + F (x, y) × (f1 (x, y) −fus (x, y)) (26)

FIG. 7 shows the configuration of the image processing apparatus according to the present embodiment, which realizes the above equation (26). In FIG. 7, an input image f1 is smoothed by a smoothing means 201 to become a smoothed image fus.
s is sent to the subtraction means 204 and the gradation conversion means 2
02, the gradation is converted based on the function of FIG.
us0, which is sent to the adding means 203.

On the other hand, the input image f1 is subtracted from the smoothed image fus by the subtracting means 204 to obtain a high-frequency component image. This high-frequency component image is multiplied by a constant by a multiplication unit 205, and then added to the output image fus0 by an addition unit 203.
Is added, the processed image fd is obtained.

As described above, according to the second embodiment, the time for creating a smoothed image after gradation conversion can be omitted, and the calculation time can be shortened as compared with the first embodiment. . In addition, the density distribution width of an arbitrary gradation area of the input image can be compressed and expanded, and the amplitude of the high-frequency component after gradation conversion can be adjusted freely.

Next, a third embodiment will be described. FIG.
Indicates a gradation conversion function F1 () used in the image processing method according to the third embodiment. Here, f1 (x, y) is 2
Let f0 (x, y) be the density value of the output image after the two-dimensional gradation conversion, and let x and y be the coordinates on the two-dimension. The horizontal axis represents the density value f1 of the input image.
(X, y), and the vertical axis indicates the density value f0 (x, y) of the output image.

In FIG. 9, the solid line is the profile f1 (X) of the input image, the dotted line is the profile fus (X) of the smoothed (low frequency) image fus (x, y) of the input image, and the dashed line is the profile of the processed image. fd (X).

Next, the operation will be described. First, the input image f1 (x, y) is subjected to gradation conversion by the gradation conversion function F1 () shown in FIG. 8 as shown in Expression (27), and the output image (converted image) f0 (x, y) is converted. obtain. f0 (x, y) = F1 (f1 (x, y)) (27)

The pixel value fd (x, y) of the processed image can be obtained according to the equations (28) and (29). Where c (x, y)
Is the gradation conversion rate, which is defined by equation (28). c (x, y) = {F1 (f1 (x, y)) / {f1 (x, y)} (28) fd (x, y) = f0 (x, y) + (1-c ( x, y)) × (f1 (x, y) −fus (x, y))） (29)

Here, fus (x, y) is converted to the input image f1.
This is a (x, y) smoothed (low frequency) image, for example, represented by Expression (30).

[0058]

(Equation 1)

Incidentally, any method may be used for the above-mentioned smoothing. For example, Erosion, Dai1atio
A morphological filter such as n, 0 pening, or Closingn may be used.

FIG. 10 shows the configuration of the image processing apparatus according to the present embodiment, which realizes the above equation (29). In FIG. 10, an input image f1 is converted by a gradation converting means 30.
In step 1, the converted image f0 is obtained by performing gradation conversion based on the gradation conversion curve in FIG. on the other hand,
The input image f1 is smoothed by the smoothing means 303 to become a smoothed image fus. The subtractor 304 subtracts the smoothed image fus from the input image f1 to obtain a high-frequency image. The high-frequency image is added to the converted image f0 by the adding means 302 to obtain a processed image fd.

As described above, according to the third embodiment, the density distribution width of an arbitrary gradation area of an input image can be compressed and expanded, and the amplitude of the high-frequency component after gradation conversion can be reduced. There is an effect that the amplitude can be made the same as the amplitude of the high frequency component of the input image. In addition, the smoothing process needs to be performed only once, which has the effect of shortening the calculation time. Furthermore, the smoothing method using the average density has the effect of shortening the calculation time of the morphological filter processing.

Next, a fourth embodiment will be described. In this embodiment, the pixel value fd (x, y) of the processed image and the pixel value fuso (x, y) of the smoothed image of the first image (output image after gradation conversion) f0 (x, y) ), The pixel value f1 (x, y) of the second image (input image), the pixel value fus (x, y) of the smoothed (low frequency) image of the second image, and a function F ( ), Using the coordinates x and y on the image,

Fd (x, y) = fuso (x, y) + F (f1 (x, y)) × (f1 (x, y) −fus (x, y)) ─── (31) fd (x , Y) = f0 (x, y) + F (f1 (x, y)) × (f1 (x, y) −fus (x, y)) (32) Equation (21) or (32) ).

As described above, according to the fourth embodiment, the function F () for controlling the processing effect depends on the density value f1 (x, y) of the second image. There is an effect that the amplitude of the component can be changed according to the density value of the second image.

Next, a fifth embodiment will be described. In the present embodiment, the pixel value fd (x, y) of the processed image
Pixel value fuso of the smoothed image of the image f0 (x, y)
(X, y), the pixel value f1 (x, y) of the second image, the second
Pixel value fus (x,
y), a function F () for controlling the processing effect, and coordinates x and y on the image,

Fd (x, y) = fuso (x, y) + F (f0 (x, y)) × (f1 (x, y) −fus (x, y)) ─── (33) fd (x , Y) = f0 (x, y) + F (f0 (x, y)) × (f1 (x, y) −fus (x, y)) (34) Equation (33) or (34) ).

As described above, according to the fifth embodiment, the function F () for controlling the processing effect depends on the density f0 (x, y) of the first image. There is an effect that the amplitude of the high frequency component of the image can be changed according to the density value of the first image.

Next, a sixth embodiment will be described. In the present embodiment, the pixel value fd (x, y) of the processed image
Pixel value fuso of the smoothed image of the image f0 (x, y)
(X, y), the pixel value f1 (x, y) of the second image, the second
Pixel value fus (x,
y), a function F () for controlling the processing effect, and coordinates x and y on the image,

Fd (x, y) = fuso (x, y) + F (fus (x, y)) × (f1 (x, y) −fus (x, y)) ─── (35) fd (x , Y) = f0 (x, y) + F (fus (x, y)) × (f1 (x, y) −fus (x, y)) (36) Equation (35) or (36) ).

As described above, according to the sixth embodiment, the function () for controlling the processing effect depends on the density value fus (x, y) of the smoothed (low frequency) image of the second image. Therefore, there is an effect that the amplitude of the high frequency component of the converted image can be changed according to the density value of the smoothed (low frequency) image of the second image. Further, since the amplitude of the high-frequency component is adjusted depending on the density of the smoothed image, there is an effect that the amplitude of the high-frequency component of the second image is not affected.

Next, a seventh embodiment will be described. In the present embodiment, the pixel value fd (x, y) of the processed image and the pixel value fuso of the smoothed image of the first image f0 (x, y)
(X, y), the pixel value f1 (x, y) of the second image, the second
Pixel fus (x,
y), a function F () for controlling the processing effect, and coordinates x and y on the image,

Fd (x, y) = fuso (x, y) + F (fuso (x, y)) × (f1 (x, y) −fus (x, y)) ─── (37) fd (x , Y) = f0 (x, y) + F (fuso (x, y)) × (f1 (x, y) −fus (x, y)) (38) Equation (37) or (38) ).

As described above, according to the seventh embodiment, the function F () for controlling the processing effect is replaced with the density value fuso (x, y) of the smoothed (low frequency) image of the first image. In order to make it dependent, the amplitude of the high frequency
There is an effect that it can be changed according to the density value of the smoothed (low frequency) image of the image. Furthermore, since the amplitude of the high frequency component is adjusted depending on the density of the smoothed image, there is an effect that the amplitude of the high frequency component of the first image is not affected.

Next, an eighth embodiment will be described. In this embodiment, FIGS. 2, 4, and 5 used in the first embodiment will be described.
FIG. 5 is used. In FIG. 2, as in the first embodiment, f1 (x, y) is a density value of a two-dimensional input original image,
f0 (x, y) is defined as the density value of the output image after the two-dimensional gradation conversion, and x and y indicate coordinates on the two dimensions. The horizontal axis indicates the density value f1 (x, y) of the input image, and the vertical axis indicates the density value f0 (x, y) of the output image. The slope below the input density value 2500 is 0.2, and the slope above the input density value 2500 is 1.

The solid line in FIG. 4 shows the profile f0 (X9) of the output image after gradation conversion, and the dotted line shows the profile fuso (X) of the smoothed (low frequency) image of the output image.
The solid line in FIG. 5 is the profile f1 of the input image.
(X), the dotted line indicates the profile fd (X) of the processed image which is the result of the image processing method according to the present embodiment.

Next, the operation will be described. First, the input image f1 (x, y) is subjected to gradation conversion by the gradation conversion function F1 () shown in FIG.
0 (x, y) is obtained. Next, the pixel value fd of the processed image
(X, y) can be obtained according to equation (39). Where c (x,
y) is a function representing the slope of the gradation conversion curve.
8) It is shown by the equation.

Fd (x, y) = fuso (x, y) + a × (1 / c (x, y)) × (f0 (x, y) −fuso (x, y)) (39) Here, a is a constant, and fuso (x, y) is the output image f0.
This is the pixel value of the (x, y) smoothed (low frequency) image, and is represented by, for example, the equations (16) to (20).

The gradation conversion curve F used in the present embodiment
1 () (FIG. 2), the output image (converted image) f0 (x,
The amplitude of the high frequency component having a density value of 2500 or less in y) is 20%.
If the density is higher than 2500, the amplitude of the high frequency component is the same as the amplitude of the input image (solid line in FIG. 4).
Note that, similarly to the first embodiment, the smoothed image may use, for example, the average density according to the equation (30), or may use the morphological filter.

The profile of the obtained processed image fd (x, y) is indicated by the dotted line in FIG. The density distribution width having a density value of 2500 or less is compressed to 20% of the input image, and the amplitude of the high frequency component holds the amplitude of the input image.

FIG. 11 shows the configuration of the image processing apparatus according to the present embodiment, and realizes the above equation (39). In FIG. 11, an input image f1 is subjected to gradation conversion by a gradation conversion unit 801 to obtain a converted image f0, sent to a subtraction unit 805, and smoothed by a smoothing unit 802 to obtain a smoothed image fuso. This smoothed image fu
so is sent to the adding means 803.

On the other hand, the subtraction means 805 outputs the converted image f0
By subtracting the smoothed image fuso from, a high-frequency component is obtained. This high frequency component is multiplied by a constant by a multiplication unit 806 and then added to the smoothed image f by an addition unit 803.
By adding to uso, a processed image fd is obtained.

As described above, according to the eighth embodiment, the density distribution width of an arbitrary gradation area of an input image can be compressed and expanded, and the amplitude of the high-frequency component after gradation conversion can be reduced. There is an effect that the amplitude of the high frequency component of the image before gradation conversion can be held. Further, there is an effect that overshoot and undershoot do not occur. In addition, when the density average is used for the smoothed image, there is an effect that the calculation time can be reduced.

FIG. 12 shows the configuration of an image processing apparatus according to the ninth embodiment. 12, reference numeral 900 denotes an input image as an original image, reference numeral 901 denotes a gradation conversion unit for converting the gradation of the original image 900, reference numeral 902 denotes a converted image obtained by gradation conversion, and reference numeral 903 denotes a floor used by the gradation conversion unit 901. 904 is a smoothed image creating means for creating a smoothed image (low-frequency image) 905 of the converted image 902, and 906 is a smoothed image creating means for storing the smoothed image. High-frequency component creation means for calculating the difference between
Reference numeral 907 denotes a high-frequency component adding unit that adds the high-frequency component created by the high-frequency component creating unit 106 to the converted image 902 based on the differential coefficient of the gradation conversion curve stored in the differential coefficient storage unit 903.

FIG. 13 is a flowchart showing the flow of the processing of this embodiment. 14 and 15 show a gradation conversion curve used by the gradation conversion unit 901. The horizontal axis indicates the pixel value of the input image, and the vertical axis indicates the pixel value of the output image. FIG. 14 shows S
In FIG. 15, the gradient below the input density value B is A / B, and the gradient above the input density value B is 1 in FIG.

Next, the operation will be described according to the processing flow of FIG. The gradation conversion means 901 converts the original image 900 based on the gradation conversion curve shown in FIG. 14 or FIG.
The gradation is converted as shown by equation (0) (step S20)
1). Here, f1 (x, y) is converted into a two-dimensional input original image 9
The density value is 00, f0 (x, y) is the density value of the converted image 902 after the two-dimensional gradation conversion, and F1 () is the gradation conversion curve. x and y indicate two-dimensional coordinates. f0 (x, y) = F1 (f1 (x, y)) ────── (40)

Then, the differential coefficient storage means 903 calculates the differential coefficient of the gradation conversion curve represented by the equation (41), and stores the density value as a table c (x) (S202). c (F1 (x)) = 1-[{F1 (x) / {x]} (41)

Next, the smoothed image creating means 904 calculates a smoothed image 905 from the image 902 according to the equation (30) (S203). Next, the high frequency component creating means 90
6 calculates a high-frequency image from the gradation-converted image 902 and the smoothed image 905 as shown in the equation (42) (S20).
4). Here, fh (x, y) is defined as a pixel value of the high-frequency image. fh (x, y) = f0 (x, y) -fus (x, y) (4)

Then, the high frequency component adding means 907
As shown by the equation (43), the converted image 902 after gradation conversion
Then, the high-frequency component calculated by the high-frequency component creation unit 906 is added based on the differential coefficient stored in the differential coefficient storage unit 103 to obtain a processed image fd (x, y) (S20).
5). fd (x, y) = f0 (x, y) tens a × c (f0 (x, y)) × fh (x, y) (43) where a is a constant.

Note that the smoothed image 905 is obtained by using the above (16) to
According to the equation (20), the calculation may be performed using a morphological operation. The profile of fus (x, y) obtained here preserves the edge structure, and does not cause overshoot and undershoot, which is a drawback of the conventional dynamic range compression.

According to the present embodiment, the density distribution width of an arbitrary gradation area of an input image can be compressed and expanded, and the amplitude of the high-frequency component after the gradation conversion can be reduced by the amplitude of the image before the gradation conversion. There is an effect that the amplitude of the high frequency component can be held. Further, there is an effect that overshoot and undershoot do not occur. Further, when the density average is used for the smoothed image, there is an effect that the calculation time can be reduced.

Next, the storage medium according to the present invention will be described. The system according to each embodiment including FIG. 1, FIG. 7, FIG. 10, FIG. 11, FIG. 12, and the like may be configured as hardware, or may be configured as a computer system including a CPU, a memory, and the like. . When configured in a computer system, the memory forms a storage medium according to the present invention. The storage medium stores a program for executing the processing of each of the above-described embodiments including FIG.

The storage medium is a ROM, R
Semiconductor memory such as AM, optical disk, magneto-optical disk,
A magnetic storage medium or the like may be used, and these may be a CD-ROM,
The present invention may be applied to an FD, a magnetic card, a magnetic tape, a nonvolatile memory card, or the like.

Therefore, this storage medium is used in a system or apparatus other than the system according to each embodiment including the above-described drawings, and the system or computer reads out and executes the program code stored in this storage medium. Accordingly, the same functions as those of the above-described embodiments can be realized, the same effects can be obtained, and the object of the present invention can be achieved.

An OS running on a computer
When performing part or all of the processing, or after the program code read from the storage medium is written to a memory provided in an extended function board or an extended function unit connected to the computer, Even when the CPU or the like provided in the above-mentioned extended function board or extended function unit performs a part or all of the processing based on the instruction of the program code, the same functions as those of the embodiments can be realized and the same effects can be obtained. Can be obtained, and the object of the present invention can be achieved.

[0095]

As described above, according to the image processing apparatus of the first to fourth aspects, there is an effect that the high-frequency component of the processed image can be freely adjusted.

According to the image processing apparatus of the fifth and sixth aspects, the density distribution of an arbitrary gradation area of the input image is compressed.
This has the effect of being able to expand and maintain the amplitude of the high-frequency component after gradation conversion.

In the image processing method according to the present invention, the high frequency component of the second image can be added to the smoothed image of the first image at an arbitrary ratio. Therefore, the contrast of the low-frequency image has an effect that the contrast of the first image is maintained and the high-frequency component of the second image can be freely added.

According to the tenth aspect, the high-frequency component of the second image can be added to the smoothed image of the first image at an arbitrary ratio according to the positional information of the image. Therefore, there is an effect that the strength of the application of the high frequency component can be adjusted according to the image position.

According to the eleventh aspect of the present invention, the function F () for controlling the processing effect is converted to the density value f1 of the second image.
Since it depends on (x, y), there is an effect that the amplitude of the high frequency component can be changed according to the density value of the second image.

According to the twelfth aspect of the present invention, the function F () for controlling the processing effect is converted into the density value f0 (x,
Since it depends on y), there is an effect that the amplitude of the high frequency component of the converted image can be changed according to the density value of the first image.

According to the thirteenth aspect, the function F () for controlling the processing effect is smoothed (low frequency) of the second image.
Since it depends on the density value fus (x, y) of the image, the amplitude of the high frequency component of the converted image can be changed according to the density value of the smoothed (low frequency) image of the second image. Further, since the amplitude of the high frequency component is adjusted depending on the density of the smoothed image, there is an effect that the amplitude of the high frequency component of the second image is not affected.

According to the fourteenth aspect of the present invention, the function F () for controlling the processing effect is smoothed (low frequency) of the first image.
Since it depends on the density value fuso (x, y) of the image, there is an effect that the amplitude of the high frequency component of the converted image can be changed according to the density value of the smoothed (low frequency) image of the first image. Furthermore, since the amplitude of the high frequency component is adjusted depending on the density of the smoothed image, there is an effect that the amplitude of the high frequency component of the first image is not affected.

According to the fifteenth aspect, the high-frequency component of the second image can be added to the smoothed image of the first image at an arbitrary ratio. Therefore, the contrast of the low-frequency image has an effect that the contrast of the first image is maintained and the high-frequency component of the second image can be freely added. Further, since the smoothed image is created only once, there is an effect that the calculation time can be reduced.

According to the sixteenth aspect, the high-frequency component of the second image can be added to the smoothed image of the first image at an arbitrary ratio according to the positional information of the image. Therefore, there is an effect that the strength of the application of the high frequency component can be adjusted according to the image position.

According to the seventeenth aspect of the present invention, the function f0 for controlling the processing effect is converted into the density value f1 (x,
Since it depends on y), there is an effect that the amplitude of the high frequency component can be changed according to the density value of the second image.

According to the eighteenth aspect of the present invention, the function F () for controlling the processing effect is converted into the density value f0 (x,
Since it depends on y), there is an effect that the amplitude of the high frequency component of the converted image can be changed according to the density value of the first image.

According to the nineteenth aspect, the function F () for controlling the processing effect is smoothed (low frequency) of the second image.
Since it depends on the density value fus (x, y) of the image, the amplitude of the high frequency component of the converted image can be changed according to the density value of the smoothed (low frequency) image of the second image. Further, since the amplitude of the high-frequency component is adjusted depending on the density of the smoothed image, there is an effect that the amplitude of the high-frequency component of the second image is not affected.

According to the twentieth aspect, the function F () for controlling the processing effect is smoothed (low frequency) of the first image.
Since it depends on the density value fuso (x, y) of the image, there is an effect that the amplitude of the high frequency component of the converted image can be changed according to the density value of the smoothed (low frequency) image of the first image. Furthermore, since the amplitude of the high frequency component is adjusted depending on the density of the smoothed image, there is an effect that the amplitude of the high frequency component of the first image is not affected.

According to the present invention, the width of the density distribution of the second image and the high frequency component can be freely changed.

According to the twenty-third aspect, the width of the density distribution of the second image and the high-frequency component can be freely changed. Further, there is an effect that the calculation time can be reduced since the smoothed image needs to be created only once.

According to the twenty-fourth aspect, the addition amount of the high-frequency component is adjusted in accordance with the gradation conversion rate. Therefore, even if the width of the density distribution is arbitrarily changed, the amplitude of the high-frequency component is not changed. Can be kept at the amplitude of the high-frequency component of the image.
Therefore, there is an effect that the width of the density distribution can be arbitrarily changed while the amplitude of the high frequency component is kept constant.

According to the twenty-fifth aspect, the density distribution width of an arbitrary gradation area of an input image can be compressed and expanded, and the amplitude of the high-frequency component after the gradation conversion can be changed before and after the gradation conversion. There is an effect that the amplitude of the high frequency component of the image can be held.

According to the seventh and 26th aspects of the present invention, since the smoothed image is created by the morphological filter, the edge structure of the original image can be preserved, and there is an effect that undershoot and overshoot do not occur. .

According to the eighth and 27th aspects of the present invention, since a smoothed image is created using an average density value, there is an effect that the calculation time can be reduced.

Further, according to the storage medium of the present invention, the effects corresponding to the effects described in the respective claims can be obtained.

[Brief description of the drawings]

FIG. 1 is a block diagram of an image processing apparatus according to a first embodiment of the present invention.

FIG. 2 shows a gradation conversion function F according to the first and eighth embodiments.
FIG. 3 is a characteristic diagram showing 1 ().

FIG. 3 is a characteristic diagram showing a profile of an input image according to the first embodiment and a profile of a smoothed image obtained by a morphological filter.

FIG. 4 is a characteristic diagram showing profiles of a gradation conversion image and a smoothed image by a morphological filter according to the first and eighth embodiments.

FIG. 5 is a characteristic diagram showing profiles of an input image and a processed image according to the first and eighth embodiments.

FIG. 6 shows a gradation conversion function F1 () according to the second embodiment.
FIG.

FIG. 7 is a block diagram of an image processing device according to a second embodiment.

FIG. 8 shows a gradation conversion function F1 () according to the third embodiment.
FIG.

FIG. 9 is a characteristic diagram illustrating profiles of an input image, a smoothed image of the input image, and a processed image according to the third embodiment.

FIG. 10 is a block diagram of an image processing device according to a third embodiment.

FIG. 11 is a block diagram of an image processing apparatus according to an eighth embodiment.

FIG. 12 is a block diagram of an image processing device according to a ninth embodiment.

FIG. 13 is a flowchart illustrating a process according to a ninth embodiment.

FIG. 14 shows a gradation conversion function F according to the ninth embodiment.
FIG. 3 is a characteristic diagram showing 1 ().

FIG. 15 shows another gradation conversion function F according to the ninth embodiment.
FIG. 3 is a characteristic diagram showing 1 ().

FIG. 16 is a characteristic diagram showing a monotone decreasing function used for conventional dynamic range compression.

[Explanation of symbols]

101, 202, 301, 801, 901 Tone conversion means 102, 104, 201, 303, 802, 904 Smoothing means 103, 203, 302, 803 Addition means 105, 204, 304, 805 Subtraction means 106, 205, 305, 806 Multiplication means 900, f1 input image 902, f0, fus0 output image (converted image) 905, fus, fuso smoothed image 906 High frequency component creation means 907 High frequency component addition means fd Processed image

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[Procedure amendment]

[Submission date] December 17, 1999 (1999.12.
17)

[Procedure amendment 1]

[Document name to be amended] Statement

[Correction target item name] Claim 21

[Correction method] Change

[Correction contents]

[Procedure amendment 2]

[Document name to be amended] Statement

[Correction target item name] Claim 22

[Correction method] Change

[Correction contents]

[Procedure amendment 3]

[Document name to be amended] Statement

[Correction target item name] Claim 23

[Correction method] Change

[Correction contents]

[Procedure amendment 4]

[Document name to be amended] Statement

[Correction target item name] 0087

[Correction method] Change

[Correction contents]

Next, the smoothed image creating means 904 calculates a smoothed image 905 from the image 902 according to the equation (30) (S203). Next, the high frequency component creating means 90
6 calculates a high-frequency image from the gradation-converted image 902 and the smoothed image 905 as shown in the equation (42) (S20).
4). Here, fh (x, y) is defined as a pixel value of the high-frequency image. fh (x, y) = f0 (x, y) -fus (x, y) (42)

[Procedure amendment 5]

[Document name to be amended] Drawing

[Correction target item name] FIG.

[Correction method] Change

[Correction contents]

FIG. 11

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI Theme coat ゛ (Reference) H04N 5/262 H04N 1/40 101C

Claims (34)

[Claims] 1. A gradation conversion means for converting a gradation of an input image to obtain a converted image, a first smoothing means for obtaining a first smoothed image by smoothing the converted image, and a smoothing means for smoothing the input image. Second smoothing means for obtaining a second smoothed image by subtraction, subtraction means for calculating a difference between the input image and the second smoothed image, and multiplication means for multiplying an output of the calculation means by a constant. An image processing apparatus comprising: an adding unit that adds an output of the multiplying unit and the first smoothed image. 2. A smoothing means for smoothing an input image to obtain a smoothed image, a tone converting means for tone-converting the smoothed image to obtain a converted image, and a difference between the input image and the smoothed image. An image processing apparatus comprising: a subtraction unit that calculates the following equation; a multiplication unit that multiplies the output of the subtraction unit by a constant; and an addition unit that adds the output of the multiplication unit and the converted image. 3. A gradation conversion means for performing gradation conversion of an input image to obtain a converted image, a smoothing means for smoothing the input image to obtain a smoothed image, and a difference between the input image and the smoothed image. An image processing apparatus comprising: subtraction means for calculating; multiplication means for multiplying an output of said subtraction means by a constant; and addition means for adding an output of said multiplication means and said converted image. 4. A gradation conversion means for converting a gradation of an input image to obtain a converted image; a first smoothing means for obtaining a first smoothed image by smoothing the converted image; A second smoothing means for obtaining a second smoothed image by subtraction, a subtraction means for calculating a difference between the input image and the second smoothed image, a multiplication means for multiplying an output of the subtraction means by a constant, An image processing apparatus comprising: an adding unit that adds an output of the multiplying unit and the first smoothed image. 5. A gradation conversion means for converting a gradation of an input image to obtain a converted image; a storage means for storing a differential coefficient of a gradation conversion curve used by the gradation conversion means; Smoothing means for obtaining a smoothed image, calculating means for calculating a difference between the smoothed image and the converted image to obtain a high-frequency component, and calculating the calculated high-frequency component in the converted image. An image processing apparatus, comprising: adding means for adding based on a coefficient. 6. A gradation conversion means for converting a gradation of an input image to obtain a converted image; a storage means for storing a differential coefficient of a gradation conversion curve used in the gradation conversion means; A calculating means for calculating a difference between the smoothed image and the input image to obtain a high-frequency component; and a differential storing the calculated high-frequency component in the converted image. An image processing apparatus, comprising: adding means for adding based on a coefficient. 7. An image processing apparatus according to claim 1, wherein said smoothing means uses a morphological filter. 8. The image processing apparatus according to claim 1, wherein said smoothing means performs smoothing based on a density average value. 9. A smoothed image (low-frequency image) of the first image
An image processing method characterized by adding or subtracting a high frequency component of a second image at an arbitrary ratio to the pixel value of the second image. 10. A pixel value fd (x,
y), the pixel value fuso (x, y) of the smoothed image of the first image f0 (x, y), and the pixel value f1 (x, y) of the second image.
y), the pixel value fu of the smoothed (low frequency) image of the second image
fd (x, y) = fuso (x, y) + F (x, y) × using s (x, y), a function F () for controlling the processing effect, and coordinates x, y on the image.
(F1 (x, y) -fus (x, y)) An image processing method represented by the following arithmetic expression. 11. The pixel value fd (x, x) of the processed image
y), the pixel value fuso (x, y) of the smoothed image of the first image f0 (x, y), and the pixel value f1 (x, y) of the second image.
y), the pixel value fu of the smoothed (low frequency) image of the second image
fd (x, y) = fuso (x, y) + F (f1 (x, y) using s (x, y), a function F () for controlling the processing effect, and coordinates x, y on the image.
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 12. A pixel value fd (x, x,
y), the pixel value fuso (x, y) of the smoothed image of the first image f0 (x, y), and the pixel value f1 (x, y) of the second image.
y), the pixel value fu of the smoothed (low frequency) image of the second image
Using s (x, y), a function F () for controlling the processing effect, and coordinates x, y on the image, fd (x, y) = fuso (x, y) + F (f0 (x,
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 13. The pixel value fd (x, x) of the processed image
y), the pixel value fuso (x, y) of the smoothed image of the first image f0 (x, y), and the pixel value f1 (x, y) of the second image.
y), the pixel value fu of the smoothed (low frequency) image of the second image
fd (x, y) = fuso (x, y) + F (fus) using s (x, y), function F () for controlling the processing effect, and coordinates x, y on the image.
(X, y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 14. A pixel value fd (x, x,
y), the pixel value fuso (x, y) of the smoothed image of the first image f0 (x, y), and the pixel value f1 (x, y) of the second image.
y), the pixel value fu of the smoothed (low frequency) image of the second image
fd (x, y) = fuso (x, y) + F (fuso) using s (x, y), function F () for controlling the processing effect, and coordinates x, y on the image.
(X, y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 15. An image processing method, wherein a high-frequency component of a second image is added to or subtracted from a pixel value of a first image at an arbitrary ratio. 16. The pixel value fd (x, x,
y), the pixel value fo (x, y) of the first image, the pixel value f1 (x, y) (f0 (x, y) ≠ f1 (x,
y)), the pixel value f of the smoothed (low frequency) image of the second image
fd (x, y) = f0 (x, y) + F (x, y) × (f
1 (x, y) -fus (x, y)). 17. The pixel value fd (x, x,
y), the pixel value f0 (x, y) of the first image, the pixel value f1 (x, y) (f0 (x, y) ≠ f1 (x,
y)), the pixel value f of the smoothed (low frequency) image of the second image
Using us (x, y), a function F () for controlling the processing effect, and coordinates x, y on the image, fd (x, y) = f0 (x, y) + F (f1 (x,
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 18. A pixel value fd (x,
y), the pixel value f0 (x, y) of the first image, the pixel value f1 (x, y) (f0 (x, y) ≠ f1 (x,
y)), the pixel value f of the smoothed (low frequency) image of the second image
Using us (x, y), a function F () for controlling the processing effect, and coordinates x, y on the image, fd (x, y) = f0 (x, y) + F (f0 (x,
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 19. The pixel value fd (x, x,
y), the pixel value f0 (x, y) of the first image, the pixel value f1 (x, y) (f0 (x, y) ≠ f1 (x,
y)), the pixel value f of the smoothed (low frequency) image of the second image
fd (x, y) = f0 (x, y) + F (fus (x, y), using us (x, y), a function F () for controlling the processing effect, and coordinates x, y on the image.
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 20. A pixel value fd (x, x,
y), the pixel value f0 (x, y) of the first image, the pixel value fuso (x, y) of the smoothed (low frequency) image of the first image,
Pixel value f1 (x, y) of second image (f0 (x, y))
f1 (x, y)), the pixel value fus (x, y) of the smoothed (low frequency) image of the second image, and the function F for controlling the processing effect
(), Using coordinates x and y on the image, fd (x, y) = f0 (x, y) + F (fuso (x, y
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 21. Using a gradation conversion function of F1 (), a first image f0 (x, y) and a second image f1 (x, y), and coordinates x and y on the image, f0 (x, 20. The image processing method according to claim 7, wherein a relationship y) = F1 (f1 (x, y)) is satisfied. 22. Using a gradation conversion function of F1 (), a first image f0 (x, y) and a second image f1 (x, y), and coordinates x and y on the image, f0 (x, 20. The apparatus according to claim 7, wherein a relationship of y) = F1 (fuso (x, y)) is satisfied.
The image processing method according to the item. 23. A gradation conversion function F1 (), a pixel value fuso (x, y) of a smoothed (low frequency) image of the first image and a pixel of a smoothed (low frequency) image of the second image Value fus
14. A system according to claim 8, wherein (x, y) and coordinates x, y on the image have a relationship of fus (x, y) = F1 (fuso (x, y)). The image processing method according to the item. 24. A tone conversion function F1 (), a tone conversion rate c (x, y), a pixel value fd (x, y) of a processed image,
First image f0 (x, y), pixel value f1 of second image
F0 (x, y) = F1 (f1 (x, y), the pixel value fus (x, y) of the smoothed (low frequency) image of the second image, and the coordinates x, y on the image. , Y)), c (x, y) = ∂F1 (f1 (x, y)) / ∂f1
Fd (x, y) = f0 (x, y) + (1-c (x, y)
y)) × (f1 (x, y) −fus (x, y)) An image processing method represented by an arithmetic expression: 25. A tone conversion function F1 (), a tone conversion rate c (x, y), a pixel value fd (x, y) of a processed image,
The pixel value f0 (x, y) of the image after gradation conversion, and the pixel value fuso (x, x) of the smoothed (low frequency) image of the image after gradation conversion
y), the pixel value f1 (x, y) of the image before gradation conversion, the coordinates x, y on the image, and the constant a, f0 (x, y) = F1 (f1 (x, y)), c (X, y) = ∂F1 (f1 (x, y)) / ∂f1
Fd (x, y) = fuso (x, y) + a × (1 / c)
(X, y)) × (f0 (x, y) -fuso (x, y
y)) An image processing method represented by the following arithmetic expression. 26. The image processing method according to claim 9, wherein a smoothed image using a morphological filter is used. 27. The image processing method according to claim 9, wherein a smoothed image using an average density value is used. 28. The image processing method according to claim 9, wherein the first image is an image obtained by performing gradation conversion on an input image, and the second image is the input image. The image processing method according to 1. 29. A gradation conversion process for obtaining a converted image by performing a gradation conversion on an input image, a first smoothing process for obtaining a first smoothed image by smoothing the converted image, and a smoothing process for the input image. A second smoothing process for obtaining a second smoothed image by subtraction, a subtraction process for calculating a difference between the input image and the second smoothed image, a multiplication process for multiplying the subtraction output by a constant, A computer-readable storage medium storing a program for executing an addition process for adding a multiplied output and the first smoothed image. 30. A smoothing process for smoothing an input image to obtain a smoothed image, a tone conversion process for tone-converting the smoothed image to obtain a converted image, and a difference between the input image and the smoothed image. A computer-readable storage medium storing a program for executing a subtraction process for calculating the following formula, a multiplication process for multiplying the subtraction output by a constant, and an addition process for adding the multiplication output and the conversion image. 31. A tone conversion process for tone-converting an input image to obtain a converted image, a smoothing process for smoothing the input image to obtain a smoothed image, and a difference between the input image and the smoothed image. A computer-readable storage medium storing a program for executing a subtraction process for calculation, a multiplication process for multiplying the subtraction output by a constant, and an addition process for adding the multiplication output and the conversion image. 32. A tone conversion process for obtaining a converted image by performing a tone conversion on an input image, a first smoothing process for obtaining a first smoothed image by smoothing the converted image, and smoothing the input image. A second smoothing process for obtaining a second smoothed image by subtraction; a subtraction process for calculating a difference between the input image and the second smoothed image; a multiplication process for multiplying the subtraction by a constant; A computer-readable storage medium storing a program for executing an addition process for adding an output and the first smoothed image. 33. A gradation conversion process for converting a gradation of an input image to obtain a converted image; a smoothing process for smoothing the converted image to obtain a smoothed image; A computer-readable storage device storing a program for executing a subtraction process of calculating a difference to obtain a high-frequency component, and an addition process of adding the subtracted high-frequency component to the converted image based on the stored differential coefficient. Possible storage medium. 34. A computer-readable storage medium storing a program for executing an arithmetic process using the arithmetic expression according to any one of claims 9 to 25.