JP7208737B2 - Camera evaluation value measuring device and camera evaluation value measuring method - Google Patents

Description

The present invention relates to a camera evaluation value measuring device and camera evaluation value measuring method for measuring a performance evaluation value of a camera.

Conventionally, MTF (Modulation Transfer Function), which represents spatial frequency characteristics, and Signal-to-Noise Ratio (SNR), which represents the ratio of signal to noise, have been used as indices for camera performance evaluation.
A slanted-edge method, which requires a relatively small chart size and does not require framing, has been proposed for MTF measurement. In the slanted-edge method, a camera captures a black-and-white pattern with a straight boundary that is tilted several degrees from the vertical (or horizontal) direction with respect to the imaging device. ]) (see Patent Documents 1 and 2 and Non-Patent Documents 1 to 4).
There are various techniques for measuring SNR. For example, ISO 15739 is defined as a noise evaluation method for digital cameras (see Non-Patent Document 5). In the case of a broadcast camera, the SNR is expressed as the noise level when shooting in the dark with respect to 100% signal output.
In addition, in the measurement of MTF and SNR, it is customary to perform measurement without performing signal processing such as enhancement on the input signal for the sake of accuracy of performance evaluation.

JP 2010-237177 A JP 2018-13416 A

ISO 12233:2017, “Photography - Electronic still picture imaging - Resolution and spatial frequency responses” K. Masaoka et al., “Real-Time Measurement of Ultra-High Definition Camera Modulation Transfer Function,” SMPTE 2017 Annual Technical Conference & Exhibition, Hollywood, CA, October 2017 K. Masaoka et. al., Modified slanted-edge method and multidirectional modulation transfer function estimation,” Optics Express 22(5):6040-6046, March 2014 "Resolution Characteristics Measurement Method for Television Camera Systems Technical Data (ARIB TR-B41)", Version 1.0, P3-7, Association of Radio Industries and Businesses, Established September 29, 2016 ISO 15739:2013(E), “Photography - Electronic still-picture imaging - Noise measurements”

Conventionally, in the case of cameras with different MTFs and SNRs, there is a problem that it is difficult to evaluate the superiority or inferiority of the cameras. For example, if there is a camera that has a good MTF but a bad SNR, or a camera that has a bad MTF but a good SNR, it is not possible to integrally evaluate the superiority or inferiority of the camera.
Further, as described above, when measuring the MTF and SNR, the measurement is performed in a state in which no signal processing is performed inside the camera (a state in which the signal processing filter is turned off). However, there are also cameras, such as single-plate cameras, in which a signal processing filter (demosaicing processing, etc.) is always interposed. This signal processing filter has a wide variety depending on the camera manufacturer, and depending on the filter design, it is possible to increase the SNR at the expense of the MTF, so comprehensive camera evaluation becomes even more difficult. Therefore, there is a demand for a method that can integrate the MTF and SNR and perform camera evaluation in a unified manner.

The present invention has been made in view of such problems, and measures the SNR while adjusting the MTF to a predetermined level, or measures the MTF while adjusting the SNR to a predetermined level. It is an object of the present invention to provide a camera evaluation value measuring device and a camera evaluation value measuring method capable of centrally evaluating the superiority or inferiority of a camera through measurement.

In order to solve the above-mentioned problems, the camera evaluation value measuring device according to the present invention adjusts the MTF representing the spatial frequency characteristics of the camera to a predetermined level, and represents the ratio of the video signal captured by the camera and the noise. A camera evaluation value measurement device for measuring SNR, comprising a signal processing means, an MTF measurement means, a parameter control means, and an SNR measurement means.

In such a configuration, the camera evaluation value measuring device adjusts the degree of modulation of the video signal captured by the camera to be measured based on the parameter by means of the signal processing means.
This parameter is a coefficient specifying a filter for the video signal. The signal processing means adjusts the degree of modulation of the video signal by convolving the video signal using this filter.
Then, the camera evaluation value measuring device uses the MTF measuring means to measure the MTF of the video signal whose degree of modulation has been adjusted by the signal processing means.
Then, the camera evaluation value measuring device controls parameters to be output to the signal processing means by the parameter control means so that the MTF becomes a predetermined level.
Then, the camera evaluation value measuring device uses the SNR measuring means to measure the SNR of the video signal whose degree of modulation has been adjusted by the signal processing means based on the parameters.
Thereby, the camera evaluation value measuring device can measure the SNR based on the MTF when evaluating a plurality of cameras to be measured.

In the camera evaluation value measuring device, the parameter control means controls parameters to be output to the signal processing means so that the SNR reaches a predetermined level, and the signal processing means adjusts the degree of modulation based on the parameters. The MTF of the video signal may be measured by MTF measuring means.

Further, in order to solve the above-mentioned problems, the camera evaluation value measuring method according to the present invention adjusts the MTF representing the spatial frequency characteristics of the camera to a predetermined level, and the ratio of the video signal captured by the camera to the noise A camera evaluation value measurement method for measuring an SNR that represents a procedure including an MTF measurement step, a parameter control step, a signal processing step, and an SNR measurement step.

In this procedure, the camera evaluation value measuring method, in the MTF measuring step, uses the MTF measuring means to measure the MTF in the video signal shot by the camera and having the degree of modulation adjusted by the signal processing means.
Then, in the camera evaluation value measuring method, in the parameter control step, the parameters used by the signal processing means are controlled by the parameter control means so that the MTF reaches a predetermined level.
Then, in the camera evaluation value measuring method, in the signal processing step, the signal processing means adjusts the degree of modulation of the video signal based on the parameter.
By repeating the above operation, the camera evaluation value measuring method can adjust the MTF of the video signal captured by the camera to a predetermined level.
In the camera evaluation value measuring method, after the MTF is adjusted to a predetermined level in the SNR measuring step, the SNR is measured by the SNR measuring means in the video signal whose modulation degree is adjusted by the signal processing means.
Thus, the camera evaluation value measurement method can measure the SNR with the same MTF level when evaluating a plurality of cameras to be measured.

In the camera evaluation value measurement method, the parameter control step controls the parameters used by the signal processing means so that the SNR reaches a predetermined level, and the signal processing step adjusts the degree of modulation based on the parameters. The MTF of the video signal may be measured in the MTF measurement step.

ADVANTAGE OF THE INVENTION This invention has the outstanding effect shown below.
According to the present invention, in a plurality of cameras to be measured, the SNR can be measured with the MTF levels aligned, or the MTF can be measured with the SNR levels aligned.
The present invention measures the SNR of a camera with the same MTF level, or measures the MTF with the same SNR level, thereby making it possible to evaluate the overall superiority or inferiority of a camera under the same conditions. .

1 is a block configuration diagram showing the configuration of a camera evaluation value measuring device according to an embodiment of the present invention; FIG. FIG. 4 is a diagram for explaining ROIs, in which (a) is a vertical ROI (vertical edge image) and (b) is a horizontal ROI (horizontal edge image). Graphs with x-coordinate on the horizontal axis and pixel values on the vertical axis for explaining changes in pixel values due to the parameter α, where (a) is α=0, (b) is α>0, and (c) is α <0 is a graph. FIG. 10 is an explanatory diagram for explaining the correspondence between each pixel position of the ROI image and the bins of the projection axis; FIG. 10 is an explanatory diagram for explaining a method of generating an edge profile; FIG. 4 is a diagram showing an example of an MTF graph in which the horizontal axis represents the spatial frequency and the vertical axis represents the MTF value; It is a graph of MTF for explaining an ideal MTF curve. 4 is an MTF graph showing a state in which the MTF value is smaller than the ideal MTF curve. 7 is a graph of MTF for explaining a state of adjusting to an ideal MTF curve; 4 is a flow chart showing the operation of the camera evaluation value measuring device according to the embodiment of the present invention;

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[Configuration of Camera Evaluation Value Measuring Device]
First, the configuration of a camera evaluation value measuring device 1 according to an embodiment of the present invention will be described with reference to FIG.

The camera evaluation value measuring device 1 measures the SNR as the evaluation value of the camera 2 by adjusting the MTF to a predetermined level.
Here, the camera evaluation value measuring device 1 connects the camera 2 and the display device 3 .

The camera 2 is a camera to be measured, and outputs a video signal obtained by imaging the chart CH to the camera evaluation value measuring device 1 . For example, the camera 2 is an HD (High Definition) camera.

The chart (MTF chart) CH is a chart with different contrasts at boundaries, and is a slanted black-and-white pattern in which the boundaries are straight at a predetermined angle from the vertical or horizontal direction with respect to the imaging device (not shown) of the camera 2. It is a chart used in the -edge method. The camera 2 captures the chart CH in a state in which the boundary between black and white is tilted at a predetermined angle (about several degrees).

Here, when measuring the frequency characteristic in the horizontal direction as the MTF, the camera 2 captures the chart CH with the boundary line obliquely vertical as shown in FIG. 2(a). When measuring the frequency characteristics in the vertical direction, the camera 2 captures the chart CH with the boundary line obliquely horizontal as shown in FIG. 2(b).

The display device 3 provides a user interface for operating the camera evaluation value measuring device 1, and displays chart images captured by the camera 2, MTF measurement results, SNR measurement results, and the like. For example, the display device 3 is a liquid crystal display, an organic EL display, or the like.
Note that the display device 3 may be separately provided with a display device for displaying the chart image captured by the camera 2 and a display device for displaying the measurement results.
The configuration of the camera evaluation value measuring device 1 that measures the SNR by adjusting the MTF of the camera 2 based on the video signal output by the camera 2 will be described below in detail.
As shown in FIG. 1 , the camera evaluation value measuring device 1 includes signal processing means 10 , MTF measuring means 11 and SNR measuring means 12 .

The signal processing means 10 adjusts the degree of modulation of the video signal output from the camera 2 based on the parameters to change the apparent resolution.
The signal processing means 10 adjusts the degree of modulation of the video signal using parameters output from the parameter control means 113 of the MTF measuring means 11 .
For example, the signal processing means 10 performs a convolution operation on the video signal using a one-dimensional filter (1 row, 3 columns) with 3 taps shown in the following equation (1), in which the coefficient of the enhancement filter is adjustable.

α is a scalar parameter that adjusts the degree of modulation and is input from the parameter control means 113 of the MTF measurement means 11 .
Here, with reference to FIGS. 3(a), 3(b) and 3(c), the change of the pixel value of the video signal using the parameter α will be described. In FIGS. 3A, 3B, and 3C, the horizontal axis indicates the horizontal coordinate value (x-coordinate value), and the vertical axis indicates the pixel value.
FIG. 3(a) shows an example of a video signal in which an edge exists at the horizontal coordinate value x0 when α= ₀ .

By increasing the value of α (α> ₀ , for example, “ _+0.2 ”), as shown in FIG. _The value becomes smaller, and the pixel value becomes larger at the horizontal coordinate value _x1 to the right of the horizontal coordinate value x0. As a result, the edge of the video signal is emphasized and the resolution can be improved.
Also, by decreasing the value of α (α<0, for example, “−0.2”, etc.), as shown in FIG. 3C, the left horizontal coordinate value _{x −1} The pixel value increases at the horizontal coordinate value _x0 , and the pixel value decreases at the horizontal coordinate value _x1 to the right of the horizontal coordinate value x0. As a result, the edges of the video signal are dulled, and the resolution can be lowered.
As shown in FIG. 2B, when the chart CH is imaged with the boundary line in the oblique horizontal direction, the signal processing means 10 uses a one-dimensional filter ( 3 rows and 1 column) may be used to perform a convolution operation on the video signal.

Alternatively, the signal processing means 10 may perform a convolution operation on the video signal using a two-dimensional filter (3 rows and 3 columns) with 3 taps shown in the following equation (3).

In this way, by performing a convolution operation using a filter with parameters as variables, the signal processing means 10 can change the degree of modulation of the video signal according to the parameter values.
Note that the above formulas (1) to (3) may be obtained by changing the sign of α as shown in the following formulas (4) to (6).

In this case, the magnitude of the parameter value for adjusting the degree of modulation of the video signal is simply reversed. Of course, the filter is not limited to the formulas (1) to (6) as long as the filter can specify the parameter α as a scalar.
Returning to FIG. 1, the description of the configuration of the camera evaluation value measuring device 1 is continued.

The MTF measuring means 11 measures the MTF from the video signal of the chart CH whose modulation degree has been adjusted by the signal processing means 10 .
The MTF measurement means 11 includes ROI setting means 110, ROI image extraction means 111, MTF calculation means 112, and parameter control means 113, as shown in FIG.

The ROI setting means 110 sets a region of interest (ROI) including boundaries (edges) in the chart image captured by the camera 2 . For example, the ROI setting means 110 designates a rectangular area in the chart image displayed by the display device 3 with a pointing device (not shown) operated by the measurer, so that the ROI area (position, size, etc.) is set as ROI information.

Here, when measuring the frequency characteristics in the horizontal direction, the ROI setting means 110 designates a vertically long rectangular region (ROI) from the chart image obtained by imaging the chart CH, as shown in FIG. Then, ROI information is set. In this case, the ROI specifies an ROI image (vertical edge image) R with different brightness levels in the horizontal direction.

Also, when measuring the frequency characteristics in the vertical direction, the ROI setting means 110 is designated by the measurer as a horizontally long rectangular region (ROI) from a chart image obtained by imaging the chart CH, as shown in FIG. 2(b). ROI information is set by In this case, the ROI specifies an ROI image (horizontal edge image) R whose brightness varies in the vertical direction.
Note that the ROI setting by the ROI setting unit 110 can be set once if there is no need to change the ROI in chart images that are sequentially input. Also, the ROI set by the ROI setting means 110 does not necessarily have to be rectangular as long as the shape of the area can be specified.
The ROI setting means 110 outputs ROI information indicating the set ROI region (position, size, etc.) to the ROI image extraction means 111 .

The ROI image extracting means 111 extracts an image of the ROI area (position, size, etc.) indicated by the ROI information set by the ROI setting means 110 from the video signal whose degree of modulation has been adjusted by the signal processing means 10 as an ROI. It is extracted as an image.
The ROI image extraction means 111 outputs the extracted ROI image to the MTF calculation means 112 .

The MTF calculation means 112 calculates the MTF from the ROI image extracted by the ROI image extraction means 111 .
The MTF calculation means 112 calculates the MTF by a general Slanted-edge method.

Specifically, the MTF calculation unit 112 obtains the slope of the edge in a coordinate system (xy coordinate system) having two axes, the horizontal and vertical axes in the ROI image.
Then, as shown in FIG. 4, the MTF calculator 112 projects the pixels of the ROI image onto the horizontal axis (x-axis) at the same angle as the inclination θe of the edge e. At this time, the width (bin width) of the coordinates of the projection axis is set in units of sub-pixels smaller than pixels (for example, the width of 1/4 of one pixel).
Then, as shown in FIG. 5, the MTF calculation means 112 averages the pixel values for each bin on the projection axis to generate an edge profile indicating edge characteristics.
Then, the MTF calculation means 112 obtains a line spread function (LSF) by differentiating the edge profile, and obtains an MTF by Fourier transforming the LSF.
Thereby, the MTF calculation means 112 can calculate the MTF from the ROI image.

The MTF calculation means 112 displays the calculated MTF measurement result on the display device 3 . Here, the MTF calculation means 112 graphs the MTF and displays it on the display device 3, for example, as shown in FIG. 6, with the horizontal axis as the spatial frequency (cycles/pixel) and the vertical axis as the MTF value (%). .

The parameter control means 113 changes the value of MTF by controlling parameters for adjusting the degree of modulation performed by the signal processing means 10 .
Here, the parameter control means 113 changes the parameters by external adjustment so that the MTF value at a predetermined spatial frequency becomes a predetermined value. For general HD cameras, it is recommended that the MTF be 35% or more at a spatial frequency of 800 TV lines, and more generally, as shown in FIG. , an MTF value of 35% or more is recommended. This value serves as a standard for determining the MTF of general broadcast HD cameras and 4K/8K cameras. Therefore, in the present embodiment, an MTF value of 35% will be described as a predetermined value as an example.

The measurer confirms the MTF on the display device 3. For example, as shown in FIG. 8, if the spatial frequency is 0.37 (cycles/pixel) and the MTF value is less than 35%, the parameter α Adjust in the direction of increasing the value. As a result, as shown in FIG. 9, the MTF value is pushed up as a whole, and the MTF curve is adjusted to meet the criteria.
On the other hand, when the spatial frequency is 0.37 (cycles/pixel) and the MTF value is greater than 35%, the operator adjusts the value of the parameter α to be smaller.
The parameter control means 113 outputs the parameter .alpha. Here, the filter used in the signal processing means 10 has been described with the above formula (1), formula (2) or formula (3) as an example, but the above formula (4), formula (5) or formula ( In the filter of 6), the adjustment direction of the parameter α is reversed.

Thus, the measurer can adjust the MTF value of the video signal to a predetermined value by adjusting the parameters so that the spatial frequency is 0.37 (cycles/pixel) and the MTF value is 35%. can.
This α can be adjusted, for example, by a volume knob (not shown) or the like.
Here, α is adjusted by the measurer, but the parameter control means 113 may PID-control the value of α so that the MTF value becomes a predetermined value (35%). Moreover, the parameter control means 113 does not necessarily have to be provided inside the MTF measurement means 11 , and may be configured independently of the MTF measurement means 11 .

The SNR measuring means 12 measures the signal-to-noise ratio (SNR) of the video signal whose modulation degree has been adjusted by the signal processing means 10 .
The SNR measuring means 12 comprises an SNR calculating means 120 as shown in FIG.

The SNR calculator 120 calculates the SNR of the video signal whose modulation degree has been adjusted by the signal processor 10 .
After the MTF measurement means 11 adjusts the MTF value at a predetermined spatial frequency to a predetermined value, the SNR calculation means 120 is instructed to be activated by the measuring person. By reducing the MTF value, the noise is reduced and the SNR value is increased. Also, by increasing the MTF value, the noise is emphasized and the SNR value is decreased.

A general method may be used for the SNR calculation method in the SNR calculation means 120 . For example, if the camera 2 is a broadcast camera, the SNR calculation means 120 measures the signal strength with the shutter (not shown) of the camera 2 closed (dark), and calculates the signal strength within a predetermined measurement area. and the ratio of the standard deviation of the signal intensity in that area. To close the shutter of the camera 2 , the subject may manually operate the camera 2 , or the SNR measuring means 12 may send a control signal for closing the shutter to the camera 2 .
Also, if the camera 2 is a general digital camera, the SNR calculation means 120 calculates the SNR by the method defined by ISO 15739.
The SNR calculation method displays the calculated SNR measurement result on the display device 3 .

Note that the camera evaluation value measurement device 1 can also measure the MTF and SNR of the camera 2 independently. In that case, the value of the parameter α output from the parameter control means 113 to the signal processing means 10 should be set to "0".

By configuring the camera evaluation value measurement device 1 as described above, the camera evaluation value measurement device 1 can measure the SNR after adjusting the MTF value to a predetermined value as the camera evaluation value.
Accordingly, the camera evaluation value measurement device 1 can centrally evaluate the superiority or inferiority of the camera 2 by measuring the SNR of the camera 2 with the MTF values aligned.
Note that the camera evaluation value measurement device 1 can be operated by a program (camera evaluation value measurement program) for causing a computer to function as each means described above.

[Operation of camera evaluation value measuring device]
Next, operation of the camera evaluation value measuring device 1 according to the embodiment of the present invention will be described. It should be noted that the camera 2 to be measured is in a state of outputting a video signal obtained by imaging the chart CH to the camera evaluation value measuring device 1 . Further, the video signal input from the camera 2 is sequentially adjusted in degree of modulation according to the parameter α by the signal processing means 10 .

In step S1, the ROI setting means 110 of the MTF measuring means 11 sets the ROI area (position, size, etc.) as ROI information. For example, the ROI setting means 110 sets the ROI information by specifying a rectangular area in the chart image displayed by the display device 3 with a pointing device (not shown) operated by the subject.

In step S2, the ROI image extracting means 111 extracts an image of the ROI area (position, size, etc.) indicated by the ROI information set in step S1 as an ROI image from the video signal.

At step S3, the MTF calculation means 112 calculates the MTF from the ROI image extracted at step S2. Specifically, the MTF calculator 112 generates an edge profile from the ROI image, differentiates the edge profile to obtain a line spread function (LSF), and Fourier transforms the LSF to calculate the MTF.

In step S<b>4 , the MTF calculation means 112 graphs the MTF and displays it on the display device 3 .
In step S5, the measurer judges from the graph whether or not the MTF value is a predetermined value (eg, 35%) at a predetermined spatial frequency (eg, 0.37 [cycles/pixel]).

Here, if the MTF is not the predetermined value (No in step S5), in step S6, the parameter control means 113 controls the parameter α so that the MTF becomes the predetermined value according to the instruction of the measurer.
Then, in step S7, the signal processing means 10 adjusts the degree of modulation of the video signal with the parameter α controlled in step S6.
After that, the camera evaluation value measuring device 1 returns to step S2 and measures the MTF from a new ROI image.
In this manner, the camera evaluation value measurement device 1 adjusts the MTF to a predetermined value by sequentially repeating parameter control.

On the other hand, when the MTF reaches the predetermined value (Yes in step S5), the measurer closes the shutter of the camera 2 in step S8.
Then, in step S9, the SNR calculating means 120 of the SNR measuring means 12 adjusts the MTF value at a predetermined spatial frequency (for example, 0.37 [cycles/pixel]) to a predetermined value (for example, 35%). Then, the SNR of the resulting video signal is calculated.
Then, in step S10, the SNR calculator 120 displays the calculated SNR on the display device 3. FIG.

By the above operation, the camera evaluation value measuring device 1 can measure the SNR after adjusting the MTF value to the predetermined value.
In this case, the measurement person determines whether the MTF value is a predetermined value and controls the parameters. However, the camera evaluation value measurement device 1 may automatically control the parameters without intervention of the measurer.
In that case, step S4 is omitted, and in step S5, the parameter control means 113 determines whether the MTF value calculated in step S3 is a predetermined value, and in step S6, the MTF value becomes a predetermined value. It is sufficient to control the parameter α in the direction.

Further, step S8 does not necessarily have to be performed manually by the measurement person, and when the MTF value reaches a predetermined value (Yes in step S5), the MTF measuring means 11 instructs the SNR measuring means 12 to measure the SNR. , the SNR measuring means 12 may send a control signal to the camera 2 to close the shutter.

Although the embodiment of the present invention has been described above, the present invention is not limited to this embodiment.
For example, here, the parameter control means 113 controls the parameters so that the MTF value at a predetermined spatial frequency becomes a predetermined value (predetermined level).
However, the parameter control means 113, for example, the MTF curve (see FIG. 7) where the sum of the MTF values for each spatial frequency calculated (measured) by the MTF calculation means 112 (the MTF measurement means 11) satisfies a predetermined standard The parameters may be controlled so as to match the sum of the MTF values for each spatial frequency in , within a predetermined error.

Also, here, the camera evaluation value measurement device 1 measured the SNR by aligning the MTF (the MTF value at a predetermined spatial frequency and the sum of the MTF values for each spatial frequency).
However, the camera evaluation value measurement device 1 may measure the MTF in a state where the SNR is adjusted to a predetermined level.
In this case, the camera evaluation value measuring device 1 first measures the SNR by the SNR measuring means 12, and the parameter control means 113 controls the external The parameters are controlled by instructions from or PID control. Then, the camera evaluation value measurement device 1 may measure the MTF by the MTF measurement means 11 after the SNR reaches a predetermined value (predetermined level).
Accordingly, the camera evaluation value measurement device 1 can centrally evaluate the superiority or inferiority of the camera 2 by measuring the MTF of the camera 2 with the SNRs uniformed.

1 Camera Evaluation Value Measuring Device 10 Signal Processing Means 11 MTF Measuring Means 110 ROI Setting Means 111 ROI Image Extracting Means 112 MTF Calculating Means 113 Parameter Control Means 12 SNR Measuring Means 120 SNR Calculating Means 2 Camera 3 Display Device CH Chart Image

Claims (8)

A camera evaluation value measuring device for adjusting an MTF representing a spatial frequency characteristic of a camera to a predetermined level and measuring an SNR representing a ratio of a video signal and noise captured by the camera,
signal processing means for adjusting the degree of modulation of the video signal based on a parameter;
MTF measuring means for measuring the MTF in the video signal whose modulation degree has been adjusted by the signal processing means;
parameter control means for controlling the parameter so that the MTF is at the predetermined level;
and SNR measuring means for measuring the SNR of the video signal whose modulation degree is adjusted by the signal processing means based on the parameter. 2. The camera evaluation value measuring device according to claim 1, wherein the predetermined level is a predetermined MTF value at a predetermined spatial frequency. The predetermined level is the sum of MTF values for each spatial frequency in an MTF curve that satisfies a predetermined criterion, and the parameter control means controls the sum of MTF values for each spatial frequency measured by the MTF measuring means to be the predetermined level. 2. The camera evaluation value measuring device according to claim 1, wherein said parameter is controlled so as to match the level within a predetermined error. 4. The camera evaluation value measuring apparatus according to claim 1, wherein the parameter control means uses coefficients specifying a 3-tap one-dimensional or two-dimensional filter as the parameters. . The filter has the parameter α

or,

5. The camera evaluation value measuring device according to claim 4, wherein: A camera evaluation value measuring method for adjusting an MTF representing a spatial frequency characteristic of a camera to a predetermined level and measuring an SNR representing a ratio of a video signal and noise captured by the camera,
an MTF measuring step of measuring the MTF in a video signal photographed by the camera and having the degree of modulation adjusted by the signal processing means, by the MTF measuring means;
a parameter control step of controlling a parameter used by the signal processing means so that the MTF becomes the predetermined level by the parameter control means;
sequentially repeating a signal processing step of adjusting the degree of modulation of the video signal based on the parameter by the signal processing means;
and an SNR measurement step of measuring the SNR in the video signal whose modulation degree is adjusted by the signal processing means by the SNR measurement means after the MTF is adjusted to the predetermined level. value measurement method. A camera evaluation value measuring device for measuring an MTF representing a spatial frequency characteristic of a camera by adjusting an SNR representing a ratio of a video signal captured by a camera and noise to a predetermined level,
signal processing means for adjusting the degree of modulation of the video signal based on a parameter;
SNR measuring means for measuring the SNR in the video signal whose modulation degree has been adjusted by the signal processing means;
parameter control means for controlling the parameter so that the SNR becomes the predetermined level;
A camera evaluation value measuring device, comprising: MTF measuring means for measuring the MTF in the video signal whose degree of modulation is adjusted by the signal processing means based on the parameter. A camera evaluation value measuring method for measuring an MTF representing a spatial frequency characteristic of a camera by adjusting an SNR representing a ratio of a video signal captured by a camera and noise to a predetermined level, comprising:
an SNR measuring step of measuring the SNR of a video signal captured by the camera and having the degree of modulation adjusted by the signal processing means, by the SNR measuring means;
a parameter control step of controlling parameters used by the signal processing means so that the SNR becomes the predetermined level by the parameter control means;
sequentially repeating a signal processing step of adjusting the degree of modulation of the video signal based on the parameter by the signal processing means;
and an MTF measuring step of measuring the MTF in the video signal whose modulation degree is adjusted by the signal processing means by the MTF measuring means after the SNR is adjusted to the predetermined level. value measurement method.

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