JPH11306344A - Method and device for picture processing - Google Patents

Abstract

PROBLEM TO BE SOLVED: To effectively realize granulation suppression as well as sharpness emphasis of an inputted picture signal. SOLUTION: Inputted picture signals Rin, Gin, and Bin are individually subjected to granulation suppression processing in a granulation suppression processing means and sharpness emphasis processing in a sharpness emphasis processing means, and with respect to picture signals R1, G1, and B1 obtained by the granulation suppression processing and picture signals R2, G2, and B2 obtained by the sharpness emphasis processing, one of both picture signals is selected for each picture element, and selected picture signals are taken as processed picture signals Rout, Gout, and Bout.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

[0001] 1. Field of the Invention [0002] The present invention relates to an image processing method and an image processing apparatus, and more particularly to a processing method and an apparatus for enhancing the sharpness of an image while suppressing the granularity (high frequency noise) of the image. .

[0002]

2. Description of the Related Art Conventionally, an image (including a color image) recorded on a photographic film or a print is photoelectrically read by a sensor such as a CCD to obtain an image signal, which is subjected to various image processing. A reproduced image is reproduced on a print or a CRT. Examples of such image processing include frequency processing that operates on a predetermined spatial frequency component included in an image, and gradation processing that operates on the density of an image.

Further, as the frequency processing, there are a sharpness enhancement processing for suppressing a blur of an outline of an image, and a granularity suppression processing such as a smoothing processing for suppressing noise (granularity) caused by the granularity of the photosensitive material. .

[0004] Sharpness enhancement processing includes unsharp masking processing, high-frequency emphasis filter processing, and JP-A-9-224.
No. 60, a process for suppressing an intermediate frequency component while enhancing a high frequency component of an image is known, and as a granular suppression process, a median filter process, a hysteresis smoothing process, a noise removal process by repetition, etc. ,
A granular suppression process using a morphological operation is known.

According to the sharpness enhancement process, the sharpness of the image is improved, but the graininess of the image is also enhanced to leave a rough feeling. On the other hand, the graininess suppression process suppresses the graininess of the image. While the feeling can be reduced, there is a problem that the sharpness of the image is reduced.

[0006]

Therefore, there is a demand for an image processing method that enhances sharpness while suppressing graininess, and various image processing methods for simultaneously realizing graininess suppression and sharpness enhancement have been desired. Image processing methods have been proposed (US Pat. No. 4,812,903, JP-A-63-26783, JP-A-9-2246).
However, at present, none of them has been able to simultaneously effectively achieve the suppression of graininess and the enhancement of sharpness.

For example, the technique disclosed in the above-mentioned Japanese Patent Application Laid-Open No. 9-22460 suppresses an intermediate frequency component that affects graininess that gives a rough feeling while enhancing a high frequency component that affects image sharpness. By processing, sharpness is emphasized while suppressing graininess. This is because, in the color correlation information, the granularity has low color correlation and the video signal (edge) portion has high color correlation. It utilizes the property of In this process, the image is developed in the frequency domain, the intensity of the middle and high frequency components is controlled, and the degree of low color correlation is reduced to reduce the degree of granularity. That is, in this processing method, since the factor of the connection between adjacent pixels in the real image is not taken into consideration, the degree of control suddenly changes depending on the location of the image, and it is difficult to grasp that the graininess has been suppressed. Therefore, the effect of the graininess suppression is smaller than the effect of the sharpness enhancement, and from the viewpoint of the effect, the sharpness enhancement processing is actually stopped rather than the graininess suppression sharpness enhancement processing.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and has as its object to provide an image processing method and an image processing apparatus capable of effectively suppressing graininess and sharpness enhancement of an image. Is what you do.

[0009]

According to an image processing method of the present invention, a process for enhancing sharpness and a process for suppressing graininess are individually performed on an original image signal, and the image signal after these processes is processed. Accordingly, one processed image signal is obtained by selecting, for each pixel, the granularity suppression processing image signal, the sharpness enhancement processing image signal, or the original image signal after each processing.

That is, the image processing method of the present invention performs image processing for suppressing graininess and sharpness for an original image signal (including an image signal based on a color image) fin that defines the values of pixels constituting an image. Image processing for enhancing each is separately performed, and in accordance with the granularity suppression processing image signal f1 obtained by the image processing for suppressing the graininess and the sharpness enhancement processing image signal f2 obtained by the image processing for enhancing the sharpness, One of the two processed image signals f1, f2 and the original image signal fin (f1, f2, or f
in) is selected for each pixel and used as a processed image signal fout.

Here, it is desirable to select one of the two processed image signals and the original image signal according to the following equation (1) according to the two processed image signals.

[0012]

(Equation 1)

That is, the processed image signal f1 or f2 having a larger difference | f1−fin |, | f2−fin | between the granularity suppression processed image signal f1 and the sharpness enhanced processed image signal f2 and the original image signal fin. Is selected as the processed image signal fout. When the difference | f2−fin | is larger, the original image signal fin may be selected instead of selecting the sharpness enhanced image signal f2. When the two differences | f1−fin | and | f2−fin | are completely equal, the graininess suppression processed image signal f1 is regarded as the processed image signal fout according to the equation (1). Difference | f
Even when 1−fin | and | f2−fin | are equal, it is necessary to select one of them. This is a processing for convenience, and the sharpness enhancement processed image signal f2 may be used as the processed image signal fout.

As the image processing for suppressing the graininess, a median filter process, a hysteresis smoothing process, a noise removal process by repetition, a graininess suppression process (smoothing process) using a morphological operation, and the like can be applied. Of these, it is desirable to apply a graininess suppression (smoothing) process using a morphology operation. As the image processing for enhancing the sharpness, an unsharp masking process, a high-frequency emphasis filter process, and A component, an intermediate frequency component, and a high frequency component are decomposed, a high frequency component is emphasized, an enhancement suppression process for suppressing the intermediate frequency component is performed, and the frequency component and the low frequency component after the enhancement suppression process are combined (particularly, Kaiping
9-22460) can be applied, but among them, the sharpness enhancement processing by combining after suppressing the intermediate frequency components while enhancing the high frequency components of the image (Japanese Patent Laid-Open No. 9-22460) It is desirable to apply the method described above.
The combination with the sharpness enhancement processing of 9-22460 is optimal.

Here, the morphology arithmetic processing is also called morphology or morphology, and is generally developed as a set theory in an N-dimensional space, but is often applied to an image which is a two-dimensional space ( JP-A-8-272961, JP-A-9-248291, JP-A-9-91421, etc.). Here, the morphological operation processing will be briefly described below using a grayscale image as an example.

The point of coordinates (x, y) is represented by a density value f
Consider a space having a height corresponding to (x, y), and consider a one-dimensional function f (x) corresponding to this cross section. The structural element g used in the morphological operation is a symmetric function symmetrical with respect to the origin as shown in the following equation (2).

[0017]

(Equation 2)

It is assumed that the value is 0 in the domain and the domain G is represented by the following equation (3).

[0019]

(Equation 3)

At this time, the basic form of the morphological operation is a very simple operation as shown in equations (4) to (7).

[0021]

(Equation 4)

That is, the dilation processing is performed in a range of ± m (a value determined according to the structural element B and corresponding to the mask size in FIG. 4) around the target pixel. (A) in the figure, while erosion processing is a processing for searching for a minimum value within a range of ± m around the pixel of interest. (See FIG. 2B). The opening process is a process of performing a dilation process after the erosion process, that is, a process of searching for a maximum value after searching for a minimum value.
ing) The process corresponds to a process of performing an erosion process after a dilation process, that is, a process of searching for a minimum value after searching for a maximum value.

That is, in the opening process, the density curve f (x) is smoothed from the low density side, and a convex density variation portion (a portion having a higher density than the surrounding portion) which fluctuates in a spatially narrower range than the mask size 2 m. (See FIG. 3C).

On the other hand, in the closing process, the density curve f (x) is smoothed from the high density side, and a concave density variation portion (a portion having a density lower than the surrounding portion) that fluctuates in a spatially narrower range than the mask size 2 m. (See FIG. 3D).

Here, in the case of a high-density high-signal level signal in which the higher the density, the higher the density, the higher the density value f
Since the magnitude relationship is reversed with respect to the case where the image signal value of (x) is at the high luminance and high signal level, the dilation processing for the high density and high signal level signal and the erosion processing for the high luminance and high signal level (FIG. )), The erosion process for the high-density high-signal level signal and the dilation process for the high-brightness high-signal level (FIG. 10A) match the opening process for the high-density high-signal level signal. The closing process for a high-brightness high-signal level and the opening process for a high-brightness / high-signal level (FIG. 10C) match with the closing process for the high-brightness / high-signal level. .

By subjecting the image signal representing the original image to an opening process or a closing process by a morphological operation process, graininess (meaning noise as an image signal) is suppressed (or removed) from the image. (Obata “Morphology” (Corona) etc.).

Next, the sharpness enhancement process disclosed in Japanese Patent Application Laid-Open No. 9-22460 will be briefly described in which the intermediate frequency component is suppressed while the high frequency component of the image is enhanced.

In this processing, the original image signal is converted into low frequency components,
Decomposes into intermediate frequency components and high frequency components, emphasizes high frequency components, performs emphasis suppression processing to suppress intermediate frequency components, synthesizes each frequency component and low frequency component after these processes, and processes the processed image Get the signal.

Here, the low-frequency component, intermediate-frequency component, and high-frequency component of the original image signal refer to frequency components distributed as shown in FIG. When the subsequent data is reproduced as a visible image, a frequency component distributed with a peak around 1/3 of the Nyquist frequency of the output is referred to as a low frequency component, and the Nyquist frequency of the output is zero. The component distributed with the frequency as the peak is referred to. The high frequency component is a component distributed with the Nyquist frequency of the output as the peak, and the sum of the low, middle, and high frequency components becomes 1 at each frequency. Component.

In this processing method, it is preferable that after the decomposition, a luminance component is extracted from the high frequency component and the intermediate frequency component, and the emphasis suppressing process and the synthesis are performed based only on the luminance component. .

Further, in this processing method, it is preferable that a specific color region in the predetermined image is extracted, and the emphasis suppressing process is performed by further suppressing the intermediate frequency component corresponding to the specific color region.

In this processing method, after the decomposition, an evaluation value of the intermediate frequency component and / or the high frequency component is obtained, and the intermediate frequency component for a pixel whose evaluation value is smaller than a predetermined threshold is evaluated. It is preferable that the emphasis suppression processing is performed by suppressing a pixel whose value is larger than the predetermined threshold to be larger than the intermediate frequency component.
Further, in this case, the emphasis suppression process is performed by emphasizing the high-frequency component for a pixel whose evaluation value is smaller than a predetermined threshold smaller than the high-frequency component for a pixel whose evaluation value is larger than the predetermined threshold. Is preferred.

Here, the evaluation value is RG as described later.
This means a value such as a correlation value between at least one set of two colors of B3 colors and a local variance of a frequency component of an image signal.

Further, the evaluation value is a correlation value between at least one set of two of the three RGB colors of the intermediate frequency component and / or the high frequency component, for corresponding pixels. Is preferred.

After the evaluation value is filtered by a median filter, the emphasis suppression processing may be performed based on the predetermined evaluation value based on the processed evaluation value, and the intermediate frequency component and / or Alternatively, the high frequency component and the evaluation value may be calculated based on different colors among the three colors RGB.

Further, the degree of emphasis and suppression of the emphasis suppression processing may be determined by selecting from a plurality of emphasis suppression processing conditions predetermined based on reproduction conditions for reproducing the processed image signal. preferable.

Here, the reproduction condition means the type of the original such as a negative film or a reversal film, the size of the print to be output, or the time when an image such as a key correction input by the operator to perform desired image processing is reproduced. Refers to conditions affected by

As described above, the graininess suppression in the emphasis suppression process according to Japanese Patent Application Laid-Open No. 9-22460 does not consider the connection factor between adjacent pixels in an actual image, and it is difficult to grasp that graininess has been suppressed. However, the graininess suppression processing based on the morphological operation is processing on the real image surface utilizing the property of granular isolation (the continuity of the image signal (density) with the adjacent pixels is low), so that the granularity suppression processing The connection between pixels is good, the degree of suppression of granularity is easily visually grasped, and the granularity suppressing effect is high.

An image processing apparatus according to the present invention is an apparatus for carrying out the above-described image processing method according to the present invention. Graininess suppression processing means for performing processing; sharpness enhancement processing means for performing image processing for enhancing sharpness on the original image signal; and image processing for suppressing the graininess by the graininess suppression processing means. Either one of the processed image signal and the original image signal according to the granularity suppression processed image signal and the sharpness enhanced processing image signal acquired by the image processing for enhancing the sharpness by the sharpness enhancement processing unit. Signal processing means for selecting one for each pixel to generate a processed image signal.

Here, the signal processing means selects one of the two processed image signals and the original image signal according to the following equation (1) according to the two processed image signals. desirable.

[0041]

(Equation 1)

Image processing for suppressing graininess by the graininess suppression processing means includes median filter processing, hysteresis smoothing processing, noise removal processing by repetition,
Granular suppression processing (smoothing processing) using morphological operation can be applied. Among these, it is desirable to apply granular suppression (smoothing) processing using morphological operation. The image processing for enhancing the sharpness by the above includes unsharp masking processing, high-frequency emphasis filter processing, decomposing the original image signal into low frequency components, intermediate frequency components and high frequency components, emphasizing the high frequency components and A process of performing emphasis suppression processing for suppressing frequency components and synthesizing each frequency component and low frequency component after the emphasis suppression processing (Japanese Patent Application Laid-Open No.
2460), etc., but among them, sharpness enhancement processing (JP-A-9-22460) is applied by suppressing the intermediate frequency components while emphasizing the high frequency components of the image and then combining them. It is desirable to perform the granularity suppression processing using the morphological operation and
The combination with sharpness enhancement processing of No. 2460 is optimal.

[0043]

According to the image processing method and the image processing apparatus of the present invention, each of the processing obtained by separately performing the processing for enhancing sharpness and the processing for suppressing graininess on the original image signal is performed. In order to select a grain suppression processing image signal or a sharpness enhancement processing image signal (or an original image signal) for each pixel in accordance with the image signal after processing and to obtain a processed image signal after image processing, various conventional image processing methods are used. Compared with the processing method or apparatus, it is possible to effectively achieve both the suppression of graininess and the enhancement of sharpness.

If the arithmetic processing is represented by the equation (1), the difference | f1−fin between the original image signal fin of the granularity suppression processed image signal f1 and the sharpness enhancement processed image signal f2.
The processed image signal f1 or f2 or the original image signal fin with the larger |, | f2 -fin |
Therefore, the image signal of the pixel corresponding to the density flat portion (the image portion where the density (or luminance) change is small) in which the existence of the grain is relatively more noticeable than the sharpness is set as the grain suppression processing image signal f1, and the grain is suppressed. The image signal of a pixel corresponding to an edge portion (an image portion having a sharp change in density (or luminance)) where the sharpness is relatively more noticeable than the granularity is defined as a sharpness-enhanced image signal f2 to enhance the sharpness. can do. Even when the original image signal fin is selected instead of the sharpness enhancement processed image signal f2, the edge portion is not dulled by not selecting the graininess suppression processed image signal.

The graininess suppression processing using morphology operation as image processing to suppress graininess is disclosed in Japanese Patent Application Laid-Open No. 9-22460 as an image processing which hardly smooths an edge portion and enhances sharpness. The sharpness enhancement process by suppressing the intermediate frequency component while emphasizing the high frequency component of the processed image and combining the processed high frequency component, intermediate frequency component, and low frequency component can also provide a certain degree of granularity suppression effect. Therefore, it is desirable to apply these in each processing, and when a configuration in which these are combined is adopted, it is particularly effective in the following cases.

That is, especially when the arithmetic processing shown in the equation (1) is applied and no granularity suppression is applied to the sharpness enhancement portion, the sharpness enhancement will greatly reduce the granularity. As a result, the difference between the original image signal and the original image signal becomes larger than the difference between the granularity suppression processed image signal and the original image signal, and the granularity becomes conspicuous. For this reason, when Equation (1) is applied, a certain degree of graininess suppression effect can be obtained even by the sharpness enhancement processing by applying the sharpness enhancement processing disclosed in JP-A-9-22460. By applying the granularity suppression processing using the morphological operation, the edge portion is less likely to be blunted.

As described above, as the image processing for suppressing the graininess, the graininess suppression processing using the morphological operation and the graininess suppression processing also having the effect of preserving the edges are applied to enhance the sharpness. As the image processing to be performed, a sharpness enhancement process having a certain degree of graininess suppression effect, such as a sharpness enhancement process disclosed in Japanese Patent Application Laid-Open No. 9-22460, can be applied. ) Is applied, it is a more desirable configuration to apply these processes.

[0048]

DESCRIPTION OF THE PREFERRED EMBODIMENTS Specific embodiments of an image processing method and an image processing apparatus according to the present invention will be described below with reference to the drawings.

FIG. 1 is a flowchart showing a processing flow of an embodiment of the image processing method according to the present invention, and FIG. 2 is a diagram showing an image processing apparatus for executing the image processing method shown in FIG.

The illustrated image processing apparatus receives an RGB image signal Rin, Gin, Bin representing a color image, which is taken by a digital still camera or photoelectrically read from a color photographic print or a color film. Each of these RGB image signals Rin, Gin, Bin has a graininess suppression processing means 11 for performing image processing for suppressing graininess, a sharpness enhancement processing means 12 for performing image processing for enhancing sharpness, and The granularity suppression processing image signals R1, G1 obtained by the granularity suppression processing by the suppression processing means 11
, B1 and the sharpness-enhanced processed image signals R2, G obtained by the sharpness-enhancing processing by the sharpness-enhancing processing means 12.
2 and B2, one of the two processed image signals R1 or R2, G1 or G2, B1 or B2 is selected for each of RGB and for each pixel, and these selected processed image signals are respectively processed. The processed image signal Rout,
And a signal processing means 20 for outputting Gout and Bout.

Here, either one of the above-mentioned selections by the signal processing means 20 is performed in accordance with the granularity suppression processed image signals R1, G1,.
This is performed according to the following equation (1) according to B1 and the sharpness-enhanced image signals R2, G2, B2.

[0052]

(Equation 1)

That is, the difference | R1−Rin | and | R2−Rin | between the grain suppression processing image signal R1 and the sharpness enhancement processing image signal R2 from the original image signal Rin is the larger of the processing image signal R1 or R2. Is selected as a processed image signal Rout. The same applies to image signals of other colors G and B.

More specifically, for a pixel corresponding to a density flat portion (an image portion having a small change in density (or luminance)) in which the presence of grains is more conspicuous than sharpness, the grain suppression processing image signal and the original image signal are used. The difference | R1 -Rin | is the difference | R2 between the sharpness-enhanced image signal and the original image signal.
−Rin |, the granularity-suppressed image signal R1 is selected. Conversely, the pixel corresponding to the edge portion (image portion where the change in density (or luminance) is sharper) where the sharpness is relatively more noticeable than the granularity is selected. , The difference | R2 -Rin | between the sharpness-enhanced image signal and the original image signal is
Difference between granularity-suppressed image signal and original image signal | R1 -Rin
Is greater than |, the sharpness enhanced image signal R2 is selected.

Here, as the graininess suppression processing using the morphology operation as the graininess suppression processing by the graininess suppression processing means 11, and the sharpness enhancement processing by the sharpness enhancement processing means 12, the intermediate frequency component is emphasized while emphasizing the high frequency components of the image. Sharpness enhancement processing by suppressing noise (JP-A-9-22460)
No.) shall apply.

Next, the operation of the image processing apparatus according to the present embodiment will be described with reference to an R image signal Rin shown in FIG. 3A, which is one of the original image signals.

First, RGB original image signals Rin, Gin, Bin representing a color image are input to a granular suppression processing unit 11, a sharpness enhancement processing unit 12, and a signal processing unit 20, respectively, from a digital still camera or the like. Is done. Original image signal Rin
Is a signal having a distribution as shown in FIG. 3A as described above, and the other original image signals Gin and Bin also have a predetermined distribution (not shown).

The original image signal Rin represents an edge portion having a relatively large density variation and a density flat portion having a small density variation, and high-frequency noise is superimposed on these density distributions. It becomes visually conspicuous in the density flat portion.

The granularity suppression processing means 11 performs granularity suppression processing using a morphological operation on each of the input original image signals Rin, Gin, Bin to calculate the granularity suppression processed image signals R1, G1, B1. I do. FIG. 3 (2) is a diagram showing a granularity suppression processed image signal R1 by the granularity suppression process on the original image signal Rin.

On the other hand, the sharpness enhancement processing means 12 separately enhances the sharpness of the input original image signals Rin, Gin, Bin by suppressing the intermediate frequency components while enhancing the high frequency components of the image. Processing is performed to calculate sharpness enhancement processed image signals R2, G2, and B2. FIG. 3 (3) is a diagram showing a sharpness-enhanced image signal R2 obtained by a sharpness-enhancing process on the original image signal Rin.

As can be seen from the figures, the granularity-suppressed image signal R1 is a signal in which the granularity of the original image signal Rin has been suppressed and smoothed, while the sharpness-enhanced image signal R1 has been reduced.
Reference numeral 2 denotes a signal in which the density variation portion is emphasized in the original image signal Rin.

The other grain-suppression-processed image signals G 1 and B 1, like the grain-suppression-processed image signal R 1, are smoothed by suppressing the graininess, and the other sharpness-enhancement-processed image signal G 1
2 and B2, like the sharpness-enhanced processed image signal R2, are signals in which the density fluctuation portion is enhanced.

Each of the granularity suppression processed image signals R1, G1, B1 and each of the sharpness enhancement processed image signals R2, G2, B2 calculated by the granularity suppression processing means 11 are input to the signal processing means 20.

The signal processing means 20 associates pixels for each of the input image signals with each of the colors RGB, and calculates the above-described equation (G) according to the granularity suppression processing image signal, the sharpness enhancement processing image signal, and the original image signal. Perform selection processing according to 1),
A processed image signal is selected for each color. At this time, as described above, the equation (1) selects the graininess suppression processing image signal for the pixel corresponding to the density flat portion where the presence of graininess is more conspicuous than sharpness, and the edge in which sharpness is more conspicuous than graininess. For the pixel corresponding to the section, a sharpness enhancement processed image signal is selected.

FIG. 3D shows the selection processing of the granularity suppression image signal R1 shown in FIG. 2B and the sharpness enhancement image signal R2 shown in FIG. 3C according to the equation (1). Shows the processed image signal Rout obtained as a result.

As can be seen from the figure, the processed image signal R
out is smaller than the original image signal Rin (FIG. 3A) in a density flat portion where the presence of a grain is relatively conspicuous, and is reduced in an edge portion where the sharpness is relatively conspicuous. Since the emphasis is achieved, both the suppression of granularity and the enhancement of sharpness can be effectively achieved.

Similarly to the processed image signal Rout, the other processed image signals Gout and Bout are also signals in which granular suppression and sharpness enhancement have been effectively performed.

As described above, according to the image processing apparatus of the present embodiment, the input image signal is subjected to the graininess suppression process and the sharpness enhancement process separately, so that the image signal in which graininess is suppressed and the sharpness To obtain one processed image signal by selecting one of these obtained image signals for each pixel in accordance with the equation (1) to obtain one processed image signal. The granularity existing in the image can be effectively suppressed, and the sharpness can be effectively enhanced.

In the image processing apparatus of this embodiment, RGB image signals representing a color image are processed. However, the image processing method and the image processing apparatus of the present invention target such color image signals. The present invention is not limited to this, and various signals such as luminance and color difference can be processed.

[Brief description of the drawings]

FIG. 1 is a flowchart showing a processing flow of an embodiment of an image processing method of the present invention.

FIG. 2 is a diagram illustrating an image processing apparatus that performs the image processing method illustrated in FIG. 1;

3A is a diagram showing an original image signal Rin, and FIG. 3B is a diagram showing a granularity suppression processed image signal R1 based on the original image signal Rin.
(3) A diagram showing a sharpness enhancement processed image signal R2 based on the original image signal Rin, and (4) a diagram showing a processed image signal Rout

FIG. 4 is a diagram for explaining a basic operation of a morphological operation;

FIG. 5 is a graph showing distribution of low, middle, and high frequency components.

[Explanation of symbols]

 11 Granularity suppression processing means 12 Sharpness enhancement processing means 20 Signal processing means

Claims (8)

[Claims] 1. An image processing for suppressing graininess and an image processing for enhancing sharpness are individually performed on an original image signal that defines values of pixels constituting an image, and the image processing is performed by the image processing for suppressing graininess. One of the processed image signal and the original image signal for each pixel in accordance with the obtained granularity suppression processing image signal and the sharpness enhancement processing image signal acquired by the image processing for enhancing the sharpness. An image processing method characterized by selecting a processed image signal. 2. The method according to claim 1, wherein the selection of one of the two processed image signals and the original image signal is performed according to the following equation (1) according to the two processed image signals. Image processing method. (Equation 1) 3. The image processing for enhancing the sharpness includes decomposing the original image signal into a low-frequency component, an intermediate-frequency component, and a high-frequency component to enhance the high-frequency component and suppress the intermediate-frequency component. 3. The image processing apparatus according to claim 1, wherein the emphasis suppression processing is performed, and the frequency components after the emphasis suppression processing and the low frequency components are combined to obtain the sharpness enhancement processing image signal. Image processing method. 4. The image processing method according to claim 1, wherein the image processing for suppressing the graininess is a smoothing processing based on a morphological operation. 5. A grain suppression processing means for performing image processing for suppressing graininess on an original image signal defining the value of a pixel constituting an image, and an image for enhancing sharpness of the original image signal. Sharpness enhancement processing means for performing processing; and a graininess suppression processing image signal obtained by the image processing for suppressing the graininess by the graininess suppression processing means, and image processing for enhancing the sharpness by the sharpness enhancement processing means. One of the two processed image signals and the original image signal in accordance with the obtained sharpness-enhanced processed image signal.
Signal processing means for selecting one for each pixel to generate a processed image signal. 6. A method according to claim 1, wherein the signal processing means selects one of the two processed image signals and the original image signal according to the following equation (1) according to the two processed image signals. The image processing apparatus according to claim 5, wherein (Equation 1) 7. The image processing for enhancing the sharpness by the sharpness enhancement processing means decomposes the original image signal into a low frequency component, an intermediate frequency component, and a high frequency component, and emphasizes the high frequency component. Performing an emphasis suppression process for suppressing the intermediate frequency component, and acquiring the sharpness emphasis processing image signal by synthesizing each frequency component and the low frequency component after the emphasis suppression process. 7. The image processing apparatus according to claim 5, wherein 8. The image according to claim 5, wherein the image processing for suppressing the graininess performed by the graininess suppression processing unit is a smoothing process based on a morphological operation. Processing equipment.