JPH0594523A - Method and device for processing image - Google Patents

Abstract

PURPOSE:To automatically execute emphasizing and smoothing processing at optimum degree even without allowing an operator to select a space filter by evaluating the quality of an objective image by fuzzy inference and executing the emphasizing or smoothing processing in accordance with degree correspond ing to the quality of the objective image. CONSTITUTION:A fuzzy processor 4 extracts an objective image from an image storing device 3 and calculates the standard deviation of a pixel value for the objective image. A difference of data between a certain pixel and its adjacent one is also calculated. A processing degree determining means determines emphasizing or smoothing processing by fuzzy inference based upon the calculated standard deviation and the data difference. Namely the quality of the objective image which differs variously in accordance with measuring conditions is evaluated by fuzzy inference based upon its standard deviation and data difference, and after executing the normalization of the space filter, the emphasizing or smoothing processing is executed by the degree corresponding to the quality of the objective image. Thereby it is unnecessary for an operator to select the space filter.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing method and an image processing apparatus, and more particularly to an image processing method and an image processing apparatus capable of automatically determining the degree of enhancement or smoothing processing on a target image.

[0002]

2. Description of the Related Art FIG. 6 shows an example of a conventional image processing apparatus.
The image diagnostic apparatus 51 is shown in FIG. This diagnostic imaging device 51
Is an image reconstruction device 2 such as CT or MR, an image storage device 3 for storing an image (target image) obtained by the image reconstruction device 2, and an operation device 54 for an operator to select a spatial filter. And a plurality of spatial filters (F1,
F2, ...) and stores and outputs the spatial filter selected by the operator.
And an arithmetic processing unit 56 for enhancing or smoothing an image stored in the image storage unit 3 by using a spatial filter output from the data storage unit 55.
And an image storage device 7 that stores an image (processed image) that has been subjected to emphasis or smoothing processing, and a display device 8 that displays the image stored in the image storage device 7.

FIG. 7 is a flow chart showing the flow of image processing of the image diagnostic apparatus 51. In step R1, the target image is input by the image reconstruction device 2 and the image storage device 3. In step R2, the operating device 5
4 and the data storage device 55 to select a spatial filter. Depending on how to select the spatial filter at this time,
Either enhancement or smoothing processing can be selected, and the degree of enhancement or smoothing processing can be selected. Step R3
Then, the input target image is spatially filtered by the arithmetic processing unit 56 using the selected spatial filter, and the processed image is stored in the image storage unit 7. In step R4, the image stored in the image storage device 7 is output from the display device 8.

[0004]

In the conventional image diagnostic apparatus 51 described above, the operator selects the spatial filter used for image processing. However, there is a problem that an operator with little experience cannot select the optimum spatial filter for the target image or it takes time to select it. Therefore, an object of the present invention is to provide an image processing method and an image processing apparatus capable of automatically performing enhancement or smoothing processing at an optimum degree even if an operator does not select a spatial filter.

[0005]

According to the image processing method of the present invention, the quality of the target image is evaluated by fuzzy inference, and the enhancement or smoothing process is performed according to the degree corresponding to the quality of the target image. It is a feature.

The image processing apparatus of the present invention is an image processing apparatus for emphasizing or smoothing a target image, and a first calculation means for calculating the variance or standard deviation of each pixel value of the target image, and the target processing unit. Second calculation means for calculating the data difference between each pixel value of the image and its neighboring pixel value, and processing degree determination for determining the degree of emphasis or smoothing processing by fuzzy inference based on the calculated variance or standard deviation and data difference It is characterized in that it is provided with means.

[0007]

According to the image processing method of the present invention, the quality of the target image that differs depending on the observation conditions is evaluated by fuzzy inference, and the enhancement or smoothing process is performed according to the degree corresponding to the quality of the target image. Although it is difficult to set a general evaluation criterion for the quality of the target image, fuzzy reasoning allows the evaluation criterion under specific conditions to be independently made into a rule and accumulated, so it is appropriate for each case. It becomes possible to perform emphasis processing or smoothing processing in quality evaluation.

In the image processing apparatus of the present invention, the variance or standard deviation of each pixel value of the target image is calculated by the first calculation means. Further, the data difference between each pixel value of the target image and its neighboring pixel value is calculated by the second calculation means. Then, the processing degree determining means determines the degree of the emphasizing or smoothing processing by fuzzy inference based on the calculated variance or standard deviation and the data difference. That is, the image processing apparatus of the present invention evaluates the quality of a target image that varies depending on the observation conditions by fuzzy inference based on the variance or standard deviation and the data difference, and emphasizes or smoothes the image according to the degree corresponding to the quality of the target image. Process. Therefore, even if the operator does not select the spatial filter, the enhancement or smoothing process is always performed at the optimum degree.

[0009]

The present invention will be described in more detail with reference to the embodiments shown in the drawings. However, this does not limit the present invention. FIG. 1 is a block diagram of an image diagnostic apparatus 1 which is an embodiment of the image processing apparatus of the present invention. In the image diagnostic apparatus 1, the image reconstruction apparatus 2, the image storage apparatus 3, the image storage apparatus 7 and the display apparatus 8 are the same constituent elements as those of the conventional image diagnostic apparatus 51 shown in FIG.

The fuzzy processing device 4 takes out the target image from the image storage device 3 and calculates the standard deviation SD of the pixel value of the target image. In addition, a data difference D between a pixel and its neighboring pixels is calculated. Then, W (2,2) is obtained by fuzzy inference based on the calculated standard deviation SD and the data difference D. And the following 3 × 3 spatial filter,

[0011]

[Equation 1]

After setting and normalizing the spatial filter, the target image is enhanced by the spatial filter.

FIG. 2 is a flow chart showing a flow of the operation of the image diagnostic apparatus 1. In step S1, the target image is input by the image reconstruction device 2 and the image storage device 3.

In step S2, the fuzzy processor 4 calculates the standard deviation SD of the pixel values of the target image. In step S3, the fuzzy processing device 4 calculates a data difference D (i, j) between a pixel (i, j) and α × β pixels (k, l) in the vicinity thereof. The data difference D (i, j) is D (i, j) = min (| f (i, j) -f (k, l) | where f (i, j) is the pixel (i, j) The pixel value f (k, l) of is the pixel value k = i-α, ..., I + α l = j-β, ..., j + β of the pixel (k, l).

In step S4, the fuzzy processor 4 obtains W (2,2) using fuzzy inference based on the standard deviation SD and the data difference D. This fuzzy inference is performed as follows, for example.

First, two fuzzy production rules are used. -Rule 1- Increase IF "SD is large" THEN "W (2,2)". Membership functions A1 and B1 of the condition part and the operation part are shown in FIG. -Rule 2-IF "D is large" THEN "W (2,2)" is increased. Membership functions A2 and B2 of the condition part and the operation part are shown in FIG.

In the matching process, min operation and max operation are performed.
Use arithmetic. For rule 1, μ1 = A1 (SD1) B1 ′ = μ1 Λ B1 This is geometrically that in FIG. 3, the SD of the target image is <S
When it is D1>, it means that the membership grade <μ1> is obtained from the <SD1> and the membership function A1 and the inference result B1 ′ is obtained from the membership grade <μ1> and the membership function B1.

For rule 2, μ2 = A2 (D2) B2 '= μ2Λ B2 This is geometrically that in FIG.
If D2>, the <D2> and membership function A
This means that the membership grade <μ2> is obtained from 2, and the inference result B2 ′ is obtained from the membership grade <μ2> and the membership function B2.

The integration process uses the max operation. B ′ = B1′V B2 ′ This means that, geometrically, as shown in FIG. 5, the membership functions B1 ′ and B2 ′ are overwritten and the upper contour thereof is taken.

In the defuzzification process, the centroid method (C
G method) is used.

[0021]

[Equation 2]

In this example, the integration range is W (2,2) =
8 to 11

In step S5, the fuzzy processor 4 causes a spatial filter,

[0024]

[Equation 3]

Is set, the spatial filter is normalized to create a new spatial filter, and the target image is enhanced by the spatial filter.

In step S6, steps S3 to S5 are repeated for all pixels. In step S7,
The processed image is output by the image storage device 7 and the display device 8.

In the image diagnostic apparatus 1 described above, the optimum spatial filter is automatically set for the target image, and it is not necessary for the operator to select it. Moreover, since the spatial filters are set by calculation, it is not necessary to store a large number of spatial filters in advance. The membership function is
Determine based on trial results and expert opinion.

In another embodiment, fuzzy inference incorporates the purpose of photographing an image and a region to be photographed (for example, information on an affected area photographed by a CT apparatus). Further, as another embodiment, instead of the standard deviation SD, the variance (SD × S
Those using D) can be mentioned. Further, there is one in which a large number of spatial filters are stored and one spatial filter is selected based on fuzzy inference. The present invention can be applied to the smoothing processing as in the above.

[0029]

According to the image processing method and the image processing apparatus of the present invention, since the optimum degree of enhancement or smoothing processing is automatically determined for the target image, an image of the best quality is always obtained. Will be available. Further, the operator does not have to select the spatial filter, so that the processing efficiency is improved.

[Brief description of drawings]

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

FIG. 2 is a flow chart of the operation of the image diagnostic apparatus of FIG.

FIG. 3 is an exemplary diagram of a membership function regarding SD.

FIG. 4 is an exemplary diagram of a membership function regarding D.

FIG. 5 is a conceptual diagram of integration.

FIG. 6 is a block diagram of an example of a conventional image diagnostic apparatus.

7 is a flowchart of the operation of the image diagnostic apparatus of FIG.

[Explanation of symbols]

 1 image diagnostic device 2 image reconstruction device 3 image storage device 4 fuzzy processing device 7 image storage device 8 display device

Claims (2)

[Claims] 1. An image processing method, characterized in that the quality of a target image is evaluated by fuzzy inference, and enhancement or smoothing processing is performed according to a degree corresponding to the quality of the target image. 2. An image processing apparatus for performing enhancement or smoothing processing on a target image, wherein first calculation means for calculating a variance or standard deviation of each pixel value of the target image and each pixel value of the target image A second calculation means for calculating the data difference of the neighboring pixel values, and a processing degree determining means for determining the degree of the emphasizing or smoothing processing by fuzzy inference based on the calculated variance or standard deviation and the data difference. An image processing device characterized by.