JPH04253837A - Image processor - Google Patents

Abstract

PURPOSE:To improve quality of an image as a whole by correcting a partial unevenness of an image. CONSTITUTION:Image processing is performed for an original digital image A with an image processing processor and an image memory provided in an image processor as follows: An original digital image A is inputted at the step 101 to perform a division averaging processing of the original image at the steps 101, 103 and 104 and a smoothing processing is carried out at the step 105 to achieve a standardization of a concentration level at the steps 106 and 107. The results are outputted to an image monitor 6 at the step 108.

Description

[Detailed description of the invention]

0001

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus that performs image processing on digital images in order to improve the image quality of, for example, medical images.

0002

2. Description of the Related Art In recent years, digital images that can be processed are often used for medical images, and various image processing devices have been proposed to improve image quality. For example, if there is local density unevenness in the captured image, such as shading that is often seen in fundus images, the lookup table values for changing the density gradation of the input image and output image may be changed, or the histogram may be changed. Processing such as smoothing processing to improve the contrast of the entire image is performed.

0003

[Problems to be Solved by the Invention] However, in the above-mentioned conventional example, processing is performed not only on areas with uneven density but also on the entire image, resulting in areas where the density level is extremely low or high in some parts. There is a risk that the image quality will deteriorate.

An object of the present invention is to provide an image processing apparatus that improves the image quality of the entire image by correcting local density unevenness.

[0005]

[Means for Solving the Problems] An image processing device according to the present invention for achieving the above-mentioned object includes: a first calculation means for dividing and averaging an original image to calculate an average image; and a third calculation means that calculates a processed image by dividing the original image by the smoothed image. It is.

[0006]

[Operation] The image processing device having the above configuration calculates a final processed image by dividing the original image by a smoothed image calculated by performing dividing and averaging processing and smoothing processing on the original image. Partial density unevenness is corrected.

[0007]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be explained in detail based on the illustrated embodiments.

FIG. 1 shows a configuration diagram of an embodiment in which the present invention is applied to a fundus camera.
The output of the CD camera 2 is connected to the image processing processor 4 via the A/D converter 3.
The output of is connected to an image memory 5 and an image monitor 6. In this example, the image is composed of 512 x 512 pixels, and the density level of each pixel is 8 bits, that is, 2
It is assumed that it is given as a digital value of 56 gradations.

The fundus image of the subject's eye taken by the CCD camera 2 is converted into a digital value by the A/D converter 3, then input to the image processing processor 4, and further recorded in the image memory 5. Generally, a fundus image has local density unevenness such as shading, and image processing for correcting density unevenness is performed on this original image A in the image processing processor 4, and a processed image B is output to the image memory 5. Ru.

FIG. 2 is a flowchart of image processing. First, in step 101, an original image A is input to the image processing processor 4. In the next step 102, as shown in FIG. 3, the average value of the density level AVE(PO) to AVE(P15) is calculated in each region PO to P15 of 128×128 pixels obtained by dividing the entire image into 16 equal parts, An image MP as shown in FIG. 4 is created in which each region PO to P15 is set to the density level of the respective average value, and is stored in the image memory 5. Then, in step 103, as shown in FIG. 5, in each of the 128 x 128 pixel areas QO to Q8, which are obtained by equally dividing the central 384 x 384 pixel area into 9, and in the surrounding area Q9, the average value AV of the density level is determined.
E(QO) to AVE(Q9) are calculated, and in the same manner, an image MQ shown in FIG. 6 is created in which each area QO to Q9 has the density level of the respective average value, and is stored in the image memory 5. Incidentally, the relationship between the occupied areas of the regions PO to P15 and the regions QO to Q9 is as shown in FIG.

In step 104, an image A1 is created by averaging the two previously created images MP and MQ and stored in the image memory 5. In step 105, the 16× image shown in FIG.
Image A2 is created by performing smoothing processing multiple times using a 16 pixel size filter and a 3×3 pixel size maximum value filter. Then, in step 106, the image A
The maximum concentration level MAX of 2 is detected, and step 107
Then, from this maximum density level MAX and each pixel value Ai, A2i (i=1 to 512×512) of images A and A2, each final pixel value Bi of image processing B is calculated by the following equation. Bi=Ai {(A2i + (255-MAX)}

00
12] In this example, the maximum density level value is 2.
55, and Bi cannot exceed this, so in step 106 the maximum value MAX is detected and the formula (1
) is used to prevent the pixel value Bi from overflowing. Note that depending on the level of image A or the system configuration, overflow may not need to be considered in the software, and in that case, the maximum density level MAX of image A2 may not be used in the calculation to obtain the pixel value Bi. It's over.

The effect of the smoothing process in step 105 differs depending on the filter size used and the number of times the process is repeated. The size of the filter used in this example is 1
As shown in Fig. 8, this corresponds to 1/16 of the area of the 64 x 64 pixel micro region in Fig. 7, and was actually smoothed by repeating this filter 10 times. A good effect was obtained when the chemical treatment was performed. The filter size may be larger than this, in which case it is possible to reduce the number of repetitions of the smoothing process, improve the smoothing effect, and obtain a good image, but the processing time will be longer. Therefore, the size used in this example is appropriate.

In this embodiment, in order to enhance the smoothing effect, smoothing processing is further performed using a maximum value filter. As the size of the maximum value filter also increases, the area to be smoothed expands and the processing effect improves, but since this is after processing by the smoothing filter, considering the processing time, the above-mentioned 3×3 pixels or so is appropriate.

[0015] In this embodiment, the aspect ratio is 1:1.
In this example, an image of 512 x 512 pixels was used, but the size and aspect ratio of the image are arbitrary, and the number of divided regions can also be changed depending on the processed image.In the case of a color image, each RGB image This can be done by performing similar processing on . Furthermore, as the method of inputting the fundus image A, in addition to the present embodiment, digital input using a slide scanner, analog input using a still video, a video recorder, etc. are also possible.

[0016]

Effects of the Invention As explained above, the image processing device according to the present invention calculates a processed image by dividing the original image by a smoothed image calculated by performing dividing average value processing and smoothing processing on the original image. This has the effect of correcting local density unevenness in the original image and improving image quality.

[Brief explanation of the drawing]

FIG. 1 is a configuration diagram of an apparatus.

FIG. 2 is a flowchart diagram of image processing.

FIG. 3 is an explanatory diagram of a divided area P.

FIG. 4 is an explanatory diagram of a created image MP.

FIG. 5 is an explanatory diagram of a divided area Q.

FIG. 6 is an explanatory diagram of a created image MQ.

FIG. 7 is an explanatory diagram of an average value image.

FIG. 8 is an explanatory diagram of smoothing processing.

[Explanation of symbols]

1 Fundus camera device 2 CCD camera 3 A/D converter 4 Image processing processor 5 Image memory 6 Image monitor

Claims (4)

[Claims] 1. A first calculation means for dividing and averaging an original image to calculate an average image; a second calculation means for calculating a smoothed image by smoothing the average image; an image processing device comprising: third calculation means for calculating a processed image by dividing the image by the smoothed image; 2. The image processing apparatus according to claim 1, wherein the first calculation means performs the division multiple times by changing the division method. 3. The image processing apparatus according to claim 1, wherein the second calculation means is performed a plurality of times. 4. The image processing apparatus according to claim 1, wherein the second calculation means performs maximum value filter processing after smoothing processing using a smoothing filter.