JPH02288667A - Density uniformizing method for digital picture - Google Patents

Abstract

PURPOSE:To easily uniformize the density of plural digital pictures by obtaining a mean density of an optional area of a picture to be a reference and the density of a corresponding area of a picture of other conversion object and correcting the density of each picture element of the picture of the conversion object according to the difference of both densities. CONSTITUTION:In the case of incorporating the picture to an image format, a picture data and its respective management information stored once on a hard disk while picked up already by an ITV camera 2, a CCD scanner 3, an X ray microanalyzer 4 and a scanning type electromicroscope 5 are sent to a control computer 9 and each picture and its respective management information are stored on an optical disk 10 as information in pairs. Then the density of the picture to be the reference is converted into an optimum density to obtain the mean density of an optional area of the picture converted into the optimum density and the mean density of the area corresponding to the area of the other picture is obtained and the density of each picture element of the other picture is corrected based on the difference of both mean densities. Thus, the density of the plural digital pictures is easily uniformized.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to a method for correcting and equalizing density differences between a plurality of digital images having gradations.

[Conventional technology]

In conventional general photographic techniques, the density of the +i image is adjusted by selecting a photosensitive material and exposure conditions (aperture opening and shutter speed) depending on the brightness of the subject itself or its surroundings.

Even for images captured by a television camera, electron microscope, etc., each individual image can be adjusted by 7 degrees by adjusting the aperture.

However, there is no known method for automatically equalizing density differences between a plurality of consecutively captured images. Furthermore, there is no known method for equalizing the difference in degrees between the images when photos with a plurality of images printed on the same sheet of paper are arranged side by side.

For example, appearance used for inspection and development of metal materials, etc.
Photographs of macro and microstructures such as fracture surfaces require high image quality from the standpoint of quality judgment.

However, traditional photography methods only involve imaging and developing light-sensitive materials.

The process of printing onto photographic paper, arranging individual photographs, creating records of them, and editing and pasting them onto mounts is completed as an instruction manual or report.

The conventional method as described above is shown in the flowchart of FIG. Here, the "imaging" step includes external photography using a normal optical camera, microscopic photography using an optical microscope, photography using a scanning electron microscope, etc., and films of different shapes can be obtained from each. Additionally, although the "developing" step is generally automated, there are cases where special films require manual processing. Furthermore, the "enlarging/printing" step can be automatically processed for a specific size (so-called hand version), but must be done manually for other sizes. Then, in the "organizing and recording" step, it is necessary to preserve and organize a huge number of photographs and original plates (positive and negative), and to attach records to each one. The final “paste”
The "editing" process requires manual work to trim each photo and paste it onto a mount.

Such conventional methods require a large number of personnel and man-hours to complete a series of operations, and also require an enormous amount of working time. Furthermore, work such as imaging work, developing/printing etc. is W1.
It requires sophisticated technology, and there are also problems from an economic standpoint, such as high running costs for consumables such as film, chemicals, and photographic paper.

In view of these circumstances, by applying digital image processing technology using a computer system, everything from image capture to photo pasting and editing can be done with high efficiency and in a short time. A method has been put into practical use that allows high image quality to be obtained without the need for.

This method uses a television camera, scanning electron microscope (SEM), or electron beam microanalyzer (EPM), as shown in the flowchart of the outline procedure in Figure 11.
A) Digital image data with 1024 x 1024 pixels or more and 256 or more gradations of gradation is obtained by digitally converting an image captured by an analytical electron microscope or the like, and processed by a combinator system. Is the digital image data once stored on a hard disk system or RA? After being stored in a storage medium such as an optical disc, etc., and subjected to image processing as necessary, each image is given management information (shooting location, date, time, magnification, etc.) and sent to a host computer, where it is stored on an optical disc, etc. are stored and stored on mass storage media. In addition, automatic editing processing is performed in parallel with such storage processing, and editing is performed, for example, when the imaging of images to be placed in each image embedding area on the image format as shown in FIG. 12 is completed. The image is then printed onto an image formant using a laser printer, developed using an automatic processor, and output. The image format shown in FIG. 12 includes four image embedding areas 1, 2, 3.4, and 21
There are ~24 magnification marker incorporation areas and 25 to 28 imaging position information incorporation areas.

[Problem to be solved by the invention]

In this way, image processing methods using computer systems automatically process captured images, so
If left as is, the final output photo will be the captured image itself. Therefore, if there is a difference in density between a plurality of images in the image format when they are captured, the overall image quality will deteriorate, leading to errors or misunderstandings when inspecting total refraction materials. Under these circumstances, in the image processing method using the computer system as described above, it is necessary to equalize the density of the image.

The present invention has been made in view of the above-mentioned problems, and it is an object of the present invention to provide a method for equalizing the density of a plurality of digital images processed by a computer system.

[Means to solve the problem]

The digital image density uniformization method of the present invention calculates the average density of an arbitrary area of a reference image and the density of a corresponding area of another image to be converted, and then calculates the average density of the image to be converted according to the difference between the two. A method of correcting the density of each pixel is adopted.

[Effect]

In the method of the present invention, when a plurality of images are assembled and printed on a single sheet of paper, each image is printed as a photograph with uniform density.

[Embodiments of the invention]

DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below based on drawings showing embodiments thereof.

FIG. 2 is a block diagram showing the configuration of equipment used to implement the method of the present invention.

1 in the figure is a communication network.

2 is an ITV camera, each of which is connected to an image human power device 6.

3 is a CCD scanner, which is connected to an image input device 6.

4 is EPMA (Electron Probe Mic
roanalyzer (electron beam microanalyzer), and is connected to the image input device 6.

5 is SEM (Scanning Electron M
icroscope: scanning electronic W4M mirror),
It is connected to an image input device 6.

Above (7) ITV camera 21 CCD scanner 3. E
PMA4. Each of the SEMs 5 captures an input to be tracked, that is, an image of a metal tissue piece or the like as an object.

The image input device 6 converts each captured image into digital image data and sends it to the communication network l.

7 is a high-resolution monitor, which is connected to the image editing device 8.

The monitor 7 displays images when an operator performs various operations in carrying out the method of the present invention, which will be described later. The image editing device 8 processes digital image data according to various operations and commands performed by an operator on the monitor 7.

Reference numeral 9 denotes a supervising computer, which is connected to the communication network l.

10 is an optical disk, which is connected to the supervising computer 9.

The supervising computer 9 is the control center of the apparatus for carrying out the method of the invention. The optical disk IO stores the processing target and the processed digital image data. The laser printer 11 is used to obtain a hard copy of the image stored on the optical disk 10 and the image displayed on the monitor 7.

Each image input device 6, image editing device 8, and supervising computer 9 are interconnected through a communication network 1, and mutually send and receive image data, control instructions, commands, and the like.

FIG. 1 is a flowchart showing the procedure of digital image processing incorporating the digital image density uniformization method of the present invention.

First, if you want to equalize the density between multiple images when importing images into an image format, you should already use the ITV camera 2.
．． CCD scanner 3. EP gate A4. SE? Image data captured by the I5 or the like and temporarily stored in a hard disk or the like and respective management information are input to the supervising computer 9. The individual images and their respective management information are stored on the optical disc 10 as a set of 1n information. When a plurality of image ratios to be incorporated into one image format as shown in FIG. 12 are prepared, information for assembling them is created and registered. When the output order of the individual images comes, each image is subjected to density correction, that is, density uniformization processing based on the method of the present invention, and then arranged and incorporated in the image format in order, and finally printed by the laser printer 11. and developed.

By the way, although the four-degree equalization method for digital images according to the present invention is basically the same concept, three different embodiments can be applied depending on the image to be processed or the purpose of image processing. First, a first example will be described.

A first embodiment of the inventive method is referred to as an area-fixed density correction method. The processing procedure is shown in the flowchart of FIG.

First, initial raw image data without density correction is input (step 511). This raw image is the first of a plurality of images to be arranged on one image format, and is hereinafter referred to as a basic image. Next, the density distribution of the entire reference image is measured and converted into an optimal image density (step 512).

FIG. 4 is a schematic diagram showing a method for measuring this concentration distribution.

The average 7 degree value in the X-axis direction and the average concentration value in the Y-axis direction are determined by the following formulas.

Vf11= Y(ll= However, DYnIndividual pixel density value in the X-axis direction D": Individual pixel density value in the Y-axis direction Y(11: Average density value of each line in the X-axis direction '7(11
n Average density value i of each line in the Y-axis direction =0.1.2・
. . . n n: Once the density distribution is determined using the final pixel number or higher of each line, conversion to the optimum density value is then performed. This conversion is performed using either of the following equations.

D=a-1)8+b oN=a -1nD8+ b However, D R' Density value before conversion DN: Density value after conversion a: Contrast component coefficient b Nib brightness component coefficient Next, any predetermined position of the reference image An area for density comparison (hereinafter referred to as a window) is set in , and the average density value AO within this window is determined (step 513).

FIG. 5 is a schematic diagram showing the state of this window setting.

That is, one point (xs, yt) in the image and another point (to).

, y, ) is defined as a window. Then, the average density value ^0 within the window of the reference image is determined by the following formula.

(xa xs) (ya ys) However, x: Starting point coordinate in the x-axis direction x. : End point coordinate in the X-axis direction ys: Start point coordinate in the X-axis direction ya: End point coordinate in the X-axis direction The average density value Ao within the window of the reference image obtained is stored in the storage means as the average density value of the reference image. (Step 514). With the above steps, the processing for the reference image is completed.

Next, raw images other than the reference image (hereinafter referred to as converted images) are processed. That is, as in steps Sll and S13, image data is input (step 515), a window is set in the same area as the f and f4q images, and the average density value film within the window is determined (step 316). Then, calculate the difference S between the average density values within the window of both images (step 517).
, correct the density of all pixels of the converted image using the following formula (
step 318).

D庳=D8+S The processes from steps 315 to 319 are repeated until the density correction of all images to be incorporated into the same image format is completed (step 519).

As described above, in this area-fixed Q-degree correction method, the average density value within a fixed area, ie, window, is always equalized. However, depending on the situation of each image, there is no problem in moving the window setting area.

Next, a fixed magnification density correction method as a second embodiment will be described.

FIG. 6 is a flowchart showing the procedure of the fixed magnification density correction method. Incidentally, steps corresponding to those in the flowchart showing the procedure of the region-fixed density correction method shown in FIG. 2 described above are given the same step numbers.

In this magnification rate fixed density correction method, first, one piece of raw image data is input (step 511), and it is determined whether this has the same magnification rate as the image data that has already been input (step 521). If image data with the same magnification has not been input in the past, the image data is used as the reference image of the image group with that magnification in step 512, as in the case of the area fixed density correction method described above. S13. The process of S14 is performed, and the average density value Ao of the window of the reference image is determined.

If the magnification rate of the image data input in step Sll is the same as that of image data input in the past, in other words, the average density value of the image data with the same magnification rate as that of the image data has already been calculated. If so, steps 816 and 517 of the area-fixed density correction method described above.
．． Processing 518 is performed, and density correction is performed for all pixels.

Since the above processing is performed for all images, density uniformization is performed for a group of images having the same magnification. That is, as shown in the schematic diagram in FIG.
When a 00x image ■ is input, this image will be enlarged to a magnification of 100.
The average density value ^0 is calculated as the standard image for the double image, and then when the image ■ with the magnification rate of 100 times is input again, this image becomes the average of the previously calculated image with the magnification rate of 100 times. The density is corrected according to the density value ^0. Next, for example, when an image ■ with a magnification of 200 times is input, this image is used as the reference image for the image with a magnification of 200 times, the average density value AO is calculated, and then an image ■ with a magnification of 100 times is input again. When input, this image is density-corrected in accordance with the previously determined average density value ^0 of the image with a magnification of 100 times.

Then, when the 200x image ■ is input, the density of this image is corrected according to the previously determined average density value Ao of the 200x image.

Next, a fixed density concentration correction method as a third embodiment will be explained.

FIG. 8 is a flowchart showing the procedure of the fixed magnification density correction method. Incidentally, steps corresponding to the flowcharts showing the procedures of the fixed area density correction method and fixed magnification density correction method shown in FIGS. 3 and 6 are given the same step numbers.

In this fixed density density correction method, step S11. S
12. S13. The process proceeds to step S14, and the average 4 degree value ^0 of the reference image is determined. Next, in step 315, the transformed image is manually input, as in the case of the region fixed l;degree correction method.

Next, the window setting coefficient B of the new image manually input in step 315 is determined (step 531).

As shown in the schematic diagram in FIG. 9, when the enlargement ratios of the reference image input in step S11 and the converted image input in step 315 are different, a window corresponding to the enlargement ratio is created on the converted image. This is the process for setting. The window setting coefficient B is determined by the following formula, where Mo is the magnification rate of the reference image and Mc is the magnification rate of the converted image.

B=Mc/unit 0 Specifically, as shown in Figure 9 (al), for example, the magnification is 1
Assuming that the number of pixels in the X-axis direction of the window on the reference image captured at 00x is x and the number of pixels in the Y-axis direction is y, the window of the converted image is as shown in Figure 8 (bl). The number of pixels is B-x, and the number of pixels in the Y-axis direction is sy.

When a window is set on the converted image in this way,
From then on, step S1 is performed as in the case of the area fixed one-degree correction method.
6. Processing is performed in steps S17, 31B, and S19, and density correction of the converted image is performed.

In the above embodiment, for convenience of explanation, after image information data is extracted from a storage medium such as an optical disk, the density is equalized between a plurality of images when the images are incorporated into the image format. It is more efficient to equalize the density immediately before storing the image data on the optical disk, and in actual processing, it is better to uniformize the image density while visually checking the monitor surface 7 immediately after image capture. is practical.

〔Effect of the invention〕

As described above, the fixed area density correction method as the first embodiment, the fixed magnification density correction method as the second embodiment, and the fixed density density correction method as the third embodiment of the method of the present invention are explained respectively. did.

In the region-fixed density correction method, the reference image is set regardless of the magnification ratio during imaging, so only one basic image is required in one set of images, and the processing time for the reference image is reduced.

Fixed magnification density (In the 11i regular method, it takes time to set the reference image because the standard image is set according to each magnification ratio during imaging, but fixed area density correction uniformly corrects the density of images with different magnification ratios) Better correction results can be obtained compared to the density correction method.Furthermore, the fixed density density correction method combines the advantages of both the area fixed density correction method and the fixed magnification rate 4 degree correction method, but the magnification rate Since it may be impossible to set a window between images whose values are extremely different, it is only necessary to use the window appropriately depending on the situation of each image and the purpose of image processing.

[Brief explanation of the drawing]

FIG. 1 is a flowchart showing the procedure of digital image processing including the digital image density uniformization method of the present invention, FIG. 2 is a block diagram showing the configuration of an apparatus used therein, and FIG. 4 and 5 are schematic diagrams showing the same procedure, FIG. 6 is a flow chart showing the procedure of the second embodiment of the method of the present invention, and FIG. 7 is a schematic diagram showing the same procedure. Schematic diagram showing the procedure,
FIG. 8 is a flowchart showing the procedure of the second embodiment of the method of the present invention, FIG. 9 is a schematic diagram also showing the procedure, and FIG.
Figure 0 is a flowchart showing the steps of conventional manual image processing, Figure 11 is a flowchart showing the steps of conventional image processing using a computer system, and Figure 12 is a mount for placing the images used. FIG.

Claims (1)

[Claims] 1. A method for equalizing the density of a plurality of images having gradations, comprising: converting the density of an image to be a reference into an optimum density, and converting an arbitrary region of the image into the optimum density; A digital image characterized by: determining the average density of a region corresponding to the region of another image, and correcting the density of each pixel of the other image based on the difference between the two average densities. concentration uniformization method. 2. In a method of equalizing the density of a plurality of images having gradations and different enlargement ratios, for each group of images with the same enlargement ratio among the plurality of images, the density of the image to be a reference is determined as the optimum density. , find the average density of an arbitrary region of the reference image converted to the optimum density, and find the average density of a region corresponding to the region of another image with the same magnification as the reference image. . A method for equalizing the density of a digital image, comprising correcting the density of each pixel of another image having the same magnification as the reference image based on the difference between the two average densities. 3. In a method of equalizing the density of multiple images having gradations and different enlargement ratios, the density of an image to be a reference is converted to an optimum density, and any of the images converted to the optimum density value is Find the average density of the region, set a region corresponding to the region in another image in a similar shape according to its enlargement rate, find the average density, and create the reference image based on the difference between the two average densities. A method for equalizing the density of a digital image, comprising correcting the density of each pixel of another image having the same magnification.