JPS6217654A - Image pick-up apparatus - Google Patents

Abstract

PURPOSE:To make it possible to display a sharp detailed examination image, by allowing a measuring apparatus to determine the resolving power inherent to said apparatus and converting a measured spectrum corresponding to resolving power. CONSTITUTION:The contents of a reference shape memory 1 and a spectrum memory 2 having a measured result stored therein receive functional conversion by a Fourier transform device 9 corresponding to outputs '1', '0' of a change-over controller 3 to be separated into a real number part and imaginary number part while both parts are stored in a reference spectrum memory 10 and a gamma-spectrum memory 11 and the content of the memory 11 is further stored in an R-spectrum memory 12 through a spectrum divider 14. The contents of the memories 11, 12 are stored in an I-spectrum memory 13 through the divider 14 and subsequently converted by an inverse Fourier transform device 15, operated by a power operator 17 through a memory 16, converted by an address converter 19 through a power spectrum memory 18, again converted by a power converter 21 through a shift spectrum memory 20 and processed by an address converter 22 to be applied to an image display device 23 as a vertical/ horizontal deflection signal with predetermined voltage and an image having no blur is displayed.

Description

[Detailed Description of the Invention] [Field of Application of the Invention] The present invention relates to an imaging device, and is particularly aimed at imaging a measuring device with a low resolution, such as an ultrasonic flaw detection device, a radiation CT table device, or a radar imaging device. The present invention relates to an imaging device that is connected to a measuring device and is suitable for displaying high-resolution images.

[Background of the invention]

Conventional imaging devices can only be applied to measuring devices whose spatial resolution can be approximated by a normal distribution, and a spectrum with improved resolution is derived from the measured spectrum by inverse Wire Strass transformation. For this reason, there was a problem in that it could not be used for measurement devices with unknown spatial resolution or resolutions different from normal distribution.

In addition, as prior art related to this, Tokkokuho 49-4
There is one disclosed in the No. 2228 specification.

[Purpose of the invention]

The present invention was made in view of the above-mentioned problems of the prior art.The present invention is connected to a measuring device, allows the device itself to grasp the resolution specific to the measuring device, and automatically converts a measured spectrum whose resolution has deteriorated depending on the resolution into a high-resolution one. The purpose of the present invention is to provide an imaging device that can display a clear and detailed inspection image by converting it into a spectrum.

[Summary of the invention]

The imaging device of the present invention images a test specimen with a known shape and divides the Fourier transform function of the measured shape of the test specimen by the Fourier transform function of the true shape of the test specimen, thereby obtaining 11! l
The resolution of the fixed device is maintained as a Fourier transform function, and the Fourier transform function of the shape measured by first imaging the test object to be measured is divided by the above Fourier transform function, and the spectrum obtained thereby is inversely Fourier transformed. The present invention is further characterized in that the power spectrum of the transformed spectrum obtained by inverse Fourier transform is transformed into a spectrum whose coordinates are folded around the spectral width, and this spectrum is displayed as an image.

That is, the imaging device of the present invention focuses on the fact that the ratio of the Fourier transform function of the measured spatial spectrum to the Fourier transform function of the true spatial spectrum matches the Fourier transform function of the spatial resolution specific to the measuring device, and A Fourier transform function representing the spatial resolution of the measuring device is determined from the measured shape and the true shape of the test specimen, and the Fourier transform function of the obtained resolution is used to calculate the blur obtained by measuring the unknown test specimen. This is to display a high-resolution spectrum from a spectrum that has a lot of variation due to measurement errors.

Next, the principle of the present invention will be explained. Non-destructive inspection equipment that displays images of internal defects or the shape of internal structures;
For example, in ultrasonic flaw detection equipment, radiation C, T, and microwave radar detection devices, images may be blurred due to the spatial spread of ultrasonic waves, radiation, or microwaves, and the size of the aperture of the sensor receiving section. arise. This blur is
It can be regarded as the spatial resolution specific to the measuring device. The spatial resolution is
When a boiled object is also displayed as an image, it is the spatial spread of the image. The gist of the present invention is to grasp the spatial resolution unique to the device, correct the blurring of the image caused by the spatial resolution, and display an image close to the true shape. First, we will describe the principle of deriving an unblurred image from a blurred image if the spatial resolution is known.

First, for the sake of simplicity, we will consider a mathematical process for correcting one-dimensional blur. Although the actual image is two-dimensional, the mathematical processing for correcting one-dimensional blur described below can be applied in exactly the same way to a two-dimensional image. This is because a measuring device such as an ultrasonic flaw detector is configured to output a one-dimensional image signal and obtain a two-dimensional image by scanning in the main scanning direction and the sub-scanning direction.

For convenience, the image signal from the measuring device will be referred to as a spectrum. The horizontal axis of the spectrum is spatial position, and the vertical axis is intensity. The spectrum (with blur) measured by the measuring device is called spectrum 0 and is shown in FIG. On the other hand, the spatial resolution representing the blur of the device is called spectrum R and is shown in FIG.

Spectrum O shown in Figure 2 and spectrum R shown in Figure 3
are expressed by the functions 0(X) and R(X), respectively, and the spectrum when there is no blur is called the spectrum ■ and the function I (X)
When expressed as , there is a relationship expressed by the following equation (1).

Here, the unknown function I (X) is derived using the relationship described below.

First, both sides of equation (1) are Fourier transformed. That is,
The left side is defined as . Here, j is an imaginary number and ω is a frequency. Similarly, the Fourier transform function of I (X) is T(ω).

Let the Fourier transform function of R(X) be R(ω), and use the following formula (3
), defined in (4).

When the right side of equation (1) is Fourier transformed, it becomes as follows.

...(5) By the way, the Fourier transform of the function f(X-xo) can be found as follows. That is, convert X−x into variables using t, where f(ω) is! From the relationship of equation (6), which is the Fourier transform function of

...(7) Therefore, equation (5) is: =R(ω)・I(ω) ...(8
) can be transformed into

When the relationship in Equation (1) holds true, as is clear from Equation (8), the following relationship in Equation (9) expressed by the product of Fourier transform functions is obtained.

Therefore, if 0(X) and R(X) are known spectra, the unknown spectrum E(X) can be derived in the form of the Fourier transform function of the following equation.

Now, in order to return the Fourier transform function I(ω) to the actual spatial spectrum I(), it is possible to use the inverse Fourier transform procedure shown in the following equation.

= I (X) ... (1
1) From formulas (10) and (11), find I (X) using the following formula.

...(12) Now, in equation (12), 0(ω) is obtained by Fourier transforming the measured spectrum 0(), but R(ω)
The challenge is how to obtain the spectrum R(X), which is the original function of . If the spectrum R(X) is the spatial resolution of the measurement bag, it is possible to image a point-like object using a measurement device and consider the spatial spread of the image as the spectrum R(X). However, in reality, , point-like objects cannot exist, and the spatial resolution may change depending on the position.

Therefore, an object whose shape is known is imaged using a measuring device, and the spatial resolution of the measuring device is derived from a comparison with an image of the true shape. Using the resolution derived from this, equation (12
) to derive the true image of the object.

First, to derive the resolution, that is, the spectrum R of the measuring device, if the spectrum E representing the true shape is 6, and the spectrum representing the image of a known object is 0°, then from the relationship of Equation 1 (9), R(ω )=O, (ω)/Ia(ω) ...(
13) is obtained. Here, R(ω) is 0.
(ω) is the spectrum 0. , and Ia(ω) are spectra 1. are respectively Fourier transform spectra.

In this way, the spatial resolution of the measuring device can be derived in the form of R(ω), and the blurred images obtained in subsequent measurements can be calculated using R(ω).
ω) can be used to correct the procedure of equation (12) and calculate the spectrum E(X) representing the true image.

FIG. 1 is a block diagram showing a first embodiment of the present invention.

First, the operation of the embodiment shown in FIG. 1 will be described in the case of determining the spectrum i(ω) of the measuring device. When obtaining the R(ω) spectrum of the measuring device, the output of the switching controller 3 is set to 1411+.

As a result, the terminals a and C of the switches 5, 6.7 become conductive. When the output of the 0th and 5 selection instruction circuit 24 is set to "1", the output of the AND circuit 25 becomes "P1", and the switch 4 Terminals a and C become conductive.This makes it possible to obtain the spectrum R(ω) of the measuring device.
When "1" is output from the switching controller 3, the terminals C of the switches 5, 6 and 7 become conductive. Further, the terminals a and C of the switch 4 are brought into conduction only when the AND circuit 25 outputs "1".

In other cases, the terminal C becomes conductive.

Now, since the terminals a and C of the switch 4 are in a conductive state, the contents stored in the reference shape memory 1 (the spatial position of the known shape corresponds to the address and the 1 intensity is set as the stored content).

) is input to the Fourier transformer 9 via the switch 4, and the Fourier transform function (ω
) is calculated.

The Fourier transform function (ω) is stored in the real part and imaginary part of the reference spectrum memory 10 via the switch 5.

Next, the output of the selection indicator 24 is set to "0", and the spectrum obtained by measuring the sample of the reference shape is input from the measuring device and stored in the Ws constant spectrum memory 2. The contents of the 8I constant spectrum memory 2 are inputted to the Fourier transformer 9 via the switch 4, where the spectrum 0 is calculated according to equation (4), and the result is divided into a real part and an imaginary part and stored in the O spectrum memory 11. . The contents of the zero spectrum memory 11 are input to port A of the vector divider 14, and
The contents of the reference spectrum memory 10 are input to port B of the vector divider 14 via switch 6. The vector divider 14 uses the values A, (real part), A1 (imaginary part) input to boat A and the values B, (real part), B, (imaginary part) input to boat B to calculate the following: The real value c according to the formula
2. Imaginary value c1. Calculate.

C, , Ct calculated by the above formula are sent to the real part of the R spectrum memory 12 via the switch 7.

Stored in the imaginary part. This results in a spectrum R related to the spatial resolution of the measuring device.

Next, the output of the switching controller 3 is set to "0".

Then, the results of measuring the unknown sample are input from the measuring device to the Fourier transformer 9 via the switch 4.

According to equation (2), calculate the spectral ratio and calculate the real part.

It is divided into imaginary parts and recorded in the O spectrum memory 11 via the switch 5. The contents of the zero spectrum memory 11 are transferred to the port A of the vector divider 14 via the switch 6.
The contents of the spectrum memory 12 are input to the port B of the divider 14 via the switch 6, and the divider 14 calculates the equation (14).
, executes the operation according to (IS), and the result is C,,C
, are recorded in the real part and imaginary part of the varnish vector memory 13 via the switch 7, respectively, as a spectrum.

■The contents of the spectrum memory 13 are stored in the inverse Fourier transformer 1.
5, where according to equation (11).

The spectrum I is calculated, and the result is stored in the I spectrum memory 16 separately into a real part and an imaginary part. The power calculator 17 uses the real part value I1 and the imaginary part value I of the spectrum memory 16 to calculate I according to the following formula.

I,=(I,"+Iz")"...(
16) This value is recorded in the power spectrum memory 18.

The address converter 19 shifts the contents of the memory 18 by address and rearranges and records them in the shift spectrum memory 20.The shift of the 1st address is performed as follows. If the content at the address is expressed as air (k), then the memory 2 at address m according to the following formula:
Contents of 01. , (m) are determined.

...(17) The power converter 21 stores the contents I of the memory 20 at address m, .
(m), the 1 address converter 22 outputs the voltage value vx proportional to the address m of the memory 20 as a vertical deflection signal and a horizontal deflection signal of the image display 23, respectively.
In the image display 23.

An unblurred image is displayed.

Next, an example will be described in which the thickness of an object is measured by a radiographic transmission method and the spectrum obtained thereby is processed using the apparatus shown in FIG. 1st! I is a diagram showing an example of a test specimen thickness measuring device using a radiographic method. radiation source 1
Radiation 101 emitted from 00 is collimated by a collimator 103.

It is detected by the detector 104. Source 100 and collimator 1
03 is translated and scanned in the X-axis direction. The test object 1 is placed between the radiation source 100 and the detector 104.
02 is placed. Thickness measuring device! ! 105 is the scanning axis
The thickness of the test specimen 102 in the Y-axis direction is recorded. Let φ(X) be the detection intensity by the radiation 101 detector 104 at the scanning position WtX, and φ is the detection intensity at a place where there is no test object 102.

If the thickness of the test specimen 102 in the Y-axis direction is d(),
The detection intensity φ(X) can be expressed as follows.

φ(X)=φ*exp(-p d (X ))
-(18) Here, μ is the radiation 101 of the specimen 102
is the linear absorption coefficient for

When the relationship in equation (18) is transformed, it becomes as shown in the following equation.

* (X)/ $a=exp(-p d (X))
-(19) Taking the logarithm of both sides of equation (19), d (X) = -Q n (+6/ φ(X))
−(20) μ is obtained. The thickness measuring device uses the relationship of equation (20) to calculate the thickness distribution d(
') to measure.

! @5 Figure (a) is a diagram showing the thickness distribution obtained by measuring the test specimen 102, and the vertical axis d indicates the thickness.

The horizontal axis X indicates the position. Figure 5(b) shows test specimen 1.
02 is a diagram showing the true thickness distribution. Figure 5(b) shows
3 is a diagram showing the true thickness distribution of the test specimen 102. FIG. Figure 5 (
The thickness distribution obtained by the measurement shown in a) is shown in Figure 5 (b).
) is a smooth distribution, that is, a blurred distribution compared to the true thickness distribution shown in ().

The resolution of the measuring device shown in FIG. 4 becomes the distribution shown in FIG. A spectral distribution shown in Figure (b) is obtained. Fifth
Comparing the true thickness distribution shown in Figure (b) with the spectrum shown in Figure 6 (b).

It can be seen that almost the same thickness distribution is obtained.

Now, in the apparatus shown in FIG. 1, if there is a large variation in the measured values in the spectrum measured by the measurement apparatus, there is a tendency to emphasize the variation. Therefore, it is necessary to reduce the variation due to measurement errors in the measured spectrum and derive a clear spectrum. If the measured spectrum contains many variations due to measurement errors, the first
The spectral image obtained by the apparatus shown in the figure looks like the spectrum shown in FIG. As is clear from Figure 7,
A specific frequency component appears in a ripple pattern.

A second means of reducing this noise is to smooth the spectrum I to remove high spatial frequency components.

Smoothing processing as shown in the following equation is performed on the spectrum shown in FIG. The average value of the spectral intensity Iap(Xt*h) of 1. is the new spectral intensity 1. ,' (x,),
This process is based on a linear equation.

1,,' (X,)=(Σ I□(X, or k))/(
2Q+ 1 )...(21) A new spectrum obtained by smoothing the spectrum in FIG. 7 using equation (21) is shown in FIG. 8. Subtracting the spectrum shown in FIG. 8 from spectrum I shown in FIG. 7, The spectrum shown in FIG. 9 is obtained. The spectrum in FIG. 9 is ripple-like noise included in the spectrum in FIG. 7.

Therefore, by Fourier transforming the spectrum shown in FIG. 9, characteristic frequencies of ripple-like noise can be extracted. FIG. 10 is a diagram showing an example of a spectrum obtained by Fourier transforming the spectrum shown in FIG. 9. Since the spatial frequency of the ripple-like noise is high, in the spectrum shown in FIG. 10, the peak formed at the center of the ω-axis is the noise caused by the ripple-like noise. Therefore, from the spectrum shown in FIG. 10, only the spectrum within the range of the center width W on the ω axis (shown in FIG. 11) is extracted, and the spectrum stored in the varnish vector memory 13 shown in FIG. By subtracting the spectrum shown in FIG. 11 from I, frequency components that form ripple-like noise can be removed from spectrum I.

FIG. 12 is a block diagram showing a second embodiment of the present invention that executes the series of processes described above (processes related to FIGS. 7 to 11). In FIG. 12, the devices inside the dotted line frame execute the series of processes described above, and the devices outside the dotted line frame are the same as those shown in FIG. As shown in the figure, a switch 201 is inserted between the varnish vector memory 13 and the inverse Fourier transformer 15, and a switch 201 is inserted between the power spectrum memory 18 and the address converter 19. A switch 202 is inserted between them. When the output of the ripple removal indicator 200 is set to "1", the switches 201 and 202
Terminal C and terminal a become conductive, and when the output of the ripple removal indicator 200 is set to "0", the switches 201 and 2
Terminal C of 02 and terminal S become conductive. First, the contents of the I-spectrum memory 13, which sets the output level of the ripple removal indicator 200 to "1", are input to the inverse Fourier transformer 15 via the switch 201, and as explained below with respect to the apparatus of FIG. A spectrum with ripples as shown in FIG. 7 is stored in the power spectrum memory 18. This spectrum is transmitted to the smoothing calculator 203 via the switch 202.
The zero-order subtracter 205 processes the spectrum according to equation (21), converts it into a smoothed spectrum shown in FIG. 8, and stores it in the smoothed spectrum memory 204.

The contents of the smooth spectrum memory 204, that is, the smooth spectrum, are subtracted from the contents of the power spectrum memory 18, that is, the spectrum with ripples, and the spectrum with ripples as shown in FIG. 9 is subtracted from the spectrum memory 20.
6. The Fourier transformer 207 performs a Fourier transform on the contents of the subtraction spectrum memory 206, divides the frequency spectrum of the ripple shown in FIG. As shown in FIG. 11, the contents of the noise spectrum memory 208 are converted into a spectrum in which only the spectrum with a width W at the center of the spectrum in FIG. The ripple spectrum is stored in the ripple spectrum memory 210 separately.

The subtracter 211 is connected to the varnish vector memory 1 as shown in the figure.
Subtract the contents of the ripple spectrum memory 210 from the contents of 3 and store the real part and the imaginary part separately in the ripple removal spectrum memory 212. Next, if the output of the ripple removal indicator 200 is set to 110'', The contents of the ripple-removed spectrum memory 212 are inputted to the inverse Fourier transformer 15 via the switch 201, and the spectra are stored up to the power spectrum memory 18 as explained in connection with the apparatus shown in FIG. The stored contents flow to the address converter 19, and an image with ripples removed is displayed.

Next, a specific example will be described in which the apparatus shown in FIG. 12 is used to correct image blur caused by an ultrasonic flaw detector.

FIG. 13 is a diagram showing an example of an ultrasonic flaw detection device, and the device shown in FIG. 12 is used to visualize the irregularities on the surface of a test specimen. In FIG. 13, a probe 300 is scanned in the X-axis direction by a scanning device 301 while transmitting an ultrasonic beam 307 and receiving ultrasonic waves reflected from the surface of a test specimen 304 placed underwater 303 in a water tank 302. do. The flaw detector 305 measures the time interval t(X) between ultrasonic transmission and reception at a position, and measures the thickness d(X) of the sample using the following equation.

d (X) = d ov t (X)/2
(22) In equation (22), do is the distance from the probe 300 to the bottom of the water tank 302, and ■ is the water 303.
The speed of sound is . Since the ultrasonic beam 307 spreads in the water 303, the spatial resolution of the measurement system at this time is close to the spatial intensity distribution of the ultrasonic beam 307, as shown in Fig. 14 (b).
) is the spectrum R shown in FIG.

Due to this spatial resolution, when measuring the specimen 304 having the thickness distribution as shown in FIG. 14(a), the flaw detector 305
From this, the spectrum shown in FIG. 14(c) is obtained. 1st
When the spectrum shown in FIG. 4(c) is visualized with the apparatus shown in FIG. 1, a thickness distribution with many ripples is obtained as shown in FIG. 15(a).

However, if the device shown in FIG. 12 is added to the device shown in FIG. 1, a thickness distribution close to the true thickness without ripples can be obtained, as shown in FIG. 15(b).

As mentioned above, if the device shown in FIG. 12 is added to the device shown in FIG. It is possible to derive a clear spectrum without any

When the measured spectrum is a spectrum with large variations, a second means of reducing ripples and deriving a clear spectrum is as follows.

Multiply by X to obtain the spectrum shown in FIG. 16(b), and multiply by ΔX to obtain the spectrum shown in FIG. 16(c). 16th
If Figure 16(b) is the spectrum of the real part and Figure 16(c) is the spectrum of the imaginary part, Fourier transform is performed.

The intensity of harmonic components due to noise can be reduced.

FIG. 17 is a diagram showing an example of the configuration of a device that executes the above processing. The device within the dotted line frame in FIG. 17 is a part that is added to the device shown in FIG.

The operation of the primary and additional equipment inserted between the measurement spectrum memory 2 and the switch 4 in FIG. 1 will be described. In FIG. 17, a cos generator 400 multiplies the value of the generator 400 proportional to the address of the measured spectrum memory 2 by the contents of the measured spectrum memory 2, and records the value in the real part of the carrier spectrum memory 405. - million multiplier 403.

The content of the carrier spectrum memory 405 is the result of multiplying the value of the generator 401 by the content of the measured spectrum memory 2. Instead of the content of the measured spectrum of only the real part in FIG. It is input to the device shown in the figure and processed. The image obtained at this time may have some ripples compared to when the apparatus shown in FIG. 12 is added, but the ripples as shown in FIG. 15(a) can be definitely reduced.

If both the devices shown in FIGS. 12 and 17 are added to the device shown in FIG. 1, the effect will be further improved.

The device of the present invention as described above determines the inherent spatial resolution of the measuring device, and converts the measured spectrum that is blurred due to that resolution into a spectrum that is not blurred, that is, equivalent to a spectrum measured with a measuring device that has higher resolution. This will give you a spectrum.

The operation of the device of the present invention shown in FIG. 1 can be simply expressed in a flowchart as follows:
The result will be as shown in FIG. When the device shown in FIG. 17 is added to the device shown in FIG. 1, the process in step S1 in the flow chart shown in FIG.
The flowchart shown in FIG. 20 is inserted instead of the process shown in FIG.

The flow chart of the operation when the device shown in FIG. 12 is added to the device shown in FIG. 1 is the flow chart shown in FIG.
The flowchart shown in FIG. 21 is inserted between the processes in step 4.

〔Effect of the invention〕

The imaging device of the present invention can convert a measurement spectrum degraded by the spatial resolution inherent to the measurement device into a spectrum with significantly improved resolution without any modification of the measurement device. We were also able to realize a function that can reduce the effects of variations caused by measurement errors contained in spectra.

Further, since the imaging device of the present invention measures the spatial resolution specific to the measurement device, it can be widely used as an imaging device for measurement devices having any resolution, including those with unknown resolution. Therefore, it is now possible to display high-resolution images using ultrasonic flaw detection methods, radar imaging methods, radiation imaging methods, etc., which were generally said to have poor resolution.

[Brief explanation of the drawing]

Fig. 1 is a block diagram showing a first embodiment of the imaging device of the present invention, Fig. 2 is a diagram showing an example of spectrovano obtained by measuring with a measuring device with low resolution, and Fig. 3 is a diagram showing measurement Figure 4 shows an example of the spatial resolution of the device.
Figure (a) shows an example of the specimen thickness distribution measured with the apparatus shown in Figure 4, Figure 5 (b) shows the true thickness distribution, and Figure 6 shows the apparatus shown in Figure 4. A diagram showing the spatial resolution of
FIG. 6(b) shows the fifth embodiment using the first embodiment shown in FIG.
Figure 7 shows the specimen thickness distribution derived from the measured spectrum shown in Figure 7, which is obtained by the first embodiment shown in Figure 1 when there is variation due to error in the spectrum obtained by measurement. Figure 8 shows the spectrum shown in Figure 7, smoothed, and Figure 9 shows the ripple noise spectrum obtained by subtracting the spectrum in Figure 8 from the spectrum in Figure 7. Figure 10 shows the spectrum obtained by Fourier transforming the spectrum in Figure 9, Figure 11 shows the spectrum extracted from the width W at the center of the spectrum in Figure 10, and Figure 12 shows ripple noise. FIG. 13 is a diagram showing an example of an apparatus for measuring sample thickness using ultrasonic waves, and FIG. 14(a) is a diagram showing a second embodiment of the imaging device of the present invention for reducing Figure 14(b) is a diagram showing the true thickness distribution of the sample measured under the conditions, Figure 14(b) is a diagram showing the spatial resolution of the measuring device in Figure 13, and Figure 14(c) is a diagram showing the thickness distribution of the measured sample. , FIG. 15(a) is a diagram showing the thickness distribution of the sample derived using the first example shown in FIG. 1, FIG. 15(b)
is a diagram showing the thickness distribution of the sample derived using the second example shown in FIG. 12, FIG. 16
A diagram showing a spectrum obtained by multiplying the spectrum shown in FIG. 16(a) by a cosine wave, FIG. 16(Q) is a diagram showing a spectrum obtained by multiplying the spectrum shown in FIG.
7 is a diagram showing the third embodiment for reducing ripple noise, FIG. 18 is a flowchart explaining the operation of the first embodiment shown in FIG. 1, and FIG. 19 is a diagram showing the operation of the first embodiment shown in FIG. 17. By adding the device according to the second embodiment to the first embodiment shown in FIG. 1, a new flowchart is added to the flowchart in FIG. 18, and FIG. 20 is a flowchart of newly added operations similar to FIG. FIG. 21 shows a flowchart of operations newly added to FIG. 18 when the device according to the second embodiment shown in FIG. 12 is added to the first embodiment shown in FIG. This is a diagram. DESCRIPTION OF SYMBOLS 1... Reference shape memory, 2... Measured spectrum memory, 3... Switching controller, 4, 5, 6.7... Switch. 9... Fourier transformer, 10... Reference spectrum memory, 11... O spectro memory, 12... R spectrum memory, 13... Varnish vector memory, 14
...vector divider, 15...inverse Fourier transformer,
16... Varnish vector memory, 17... Power calculator, 18... Power spectrum memory, 19... Address converter, 20... Shift spectrum memory, 21...
...Power converter, 22...Address converter, 23...
Image display device, 103... collimator, 104... detector, 105... thickness measuring device, 200... ripple removal indicator. 201.202...Switch, 203...Smoothing calculator, 204...Smoothing spectrum memory, 205...
Subtractor, 206... Subtraction spectrum memory, 207.
...Fourier transformer, 208...Noise spectrum memory, 209...Frequency gate, 210...Ripple spectrum memory, 211...Subtractor, 212...
- Ripple removal spectrum memory, 300... Probe, 301X 403... Multiplier, 405... Carrier spectrum memory.

Claims (1)

[Claims] 1. Fourier transform a signal representing the shape obtained by imaging a test specimen with a known shape using a measuring device, and Fourier transform a signal representing the true shape of the test specimen to obtain the known shape. A first means for obtaining a Fourier transform function indicative of the resolution of the measuring device by dividing a Fourier transform function obtained by imaging the shape of the test object by the Fourier transform function according to the true shape; A signal representing the shape obtained by imaging with the above measuring device is Fourier transformed, and the Fourier transform function obtained by imaging the above-mentioned target test object is divided by the Fourier transform function indicating the resolution of the above measuring device. A second means for obtaining a spectrum obtained by inverse Fourier transform of the Fourier transform function obtained, and converting the power spectrum of the spectrum obtained by the second means into a spectrum whose coordinates are folded around the spectral width as an image. An imaging device comprising: third means for displaying. 2. The third means smoothes the power spectrum, subtracts the power spectrum after smoothing from the power spectrum before smoothing to obtain a ripple spectrum, and calculates the spectral width from the spectrum obtained by Fourier transforming the ripple spectrum. The imaging system according to claim 1, further comprising means for extracting a spectrum within a predetermined range from the center of the image pickup apparatus, and subtracting the extracted spectrum from the spectrum output from the second means. Device. 3. The second means multiplies the Fourier transform function obtained by imaging the target test object by a cosine function and a sine function of a predetermined period, and transmits the resulting spectrum to the measuring device. Claim 1, further comprising means for dividing by a Fourier transform function indicating resolution.
The imaging device described in Section 1.