JPH11177996A - Image processing device and method and camera - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image processing device and method which surely discriminates vertical or horizontal correlation that is more intensive than the other and which can reproduce an image with no breaking. SOLUTION: This device processes output signals of an ACCD area sensor which has a color filter of a primary color RGB Bayer array on its light receiving surface. At the same time, an fs/2 detection part 16 detects the presence of a frequency component that is multiplied by 1/2 of the spatial sampling frequency (fs) of an input image. When an fs/2 frequency component is detected, a multiplier 102 multiplies the R/G/B signals passed through an fs/2 tap circuit 101 by an interpolation coefficient G2Gain that is outputted from the part 16. Meanwhile, a multiplier 104 multiplies the interpolation outputs RIP/GIP/BIP by the inures of the coefficient G2Gain. These multiplication results are mixed together by an adder 103 and then outputted.

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, an image processing method, and a camera, and more particularly, to an image processing apparatus for processing an output signal of a solid-state imaging device having a color filter on a light receiving surface, and a processing method thereof. The present invention relates to a camera using these.

[0002]

2. Description of the Related Art Conventionally, to remove a half of the spatial sampling frequency fs for the purpose of removing aliasing noise before image information enters a solid-state imaging device,
Band limitation was performed using an optical LPF (Low Pass Filter). As described above, by performing the band limitation using the optical LPF, the output signal of the solid-state imaging device does not include a frequency component near 1/2 of the spatial sampling frequency fs. The sense of image will be impaired. On the other hand, in order not to impair the sense of resolution of the captured image, the optical L
Instead of using PF, the spatial sampling frequency fs
The response at a point higher than half the frequency of?

[0003]

However, fs /
If the response at a point higher than the frequency 2 is set to 0, not only a false signal is generated but also the color
When signal processing by correlation detection is performed in a solid-state imaging device having a color filter of a primary color Bayer array of (red), G (green), and B (blue), fs / fs If there is a spatial frequency of 2, it becomes impossible to determine whether the vertical correlation is strong or the horizontal correlation is strong, which causes image quality deterioration.

That is, in FIG. 16, a signal of a horizontal fs / 2 image (b) or a vertical fs / 2 signal is applied to a pixel array of a solid-state image sensor corresponding to a primary color RGB Bayer array (a).
When the signal of the image (c) of s / 2 is input, the output signal (d) in the case where attention is paid only to the pixel of G becomes the horizontal fs
The same holds true for / 2 (b) and vertical fs / 2 (c). Therefore, only by looking at the G output signal, the vertical correlation is strong (horizontal fs / 2) or the horizontal correlation is strong (vertical fs /
2) cannot be determined.

In FIG. 16A, Gr / Gb
Indicates G pixels in the R row / G pixels in the B row, respectively.
Also, in FIG. 3D, R / G pixels are displayed in black, and attention should be paid to gray (scattered) pixels and white pixels.

SUMMARY OF THE INVENTION The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to reliably determine whether a vertical correlation or a horizontal correlation is strong, and reproduce an image without failure. It is an object of the present invention to provide an image processing apparatus and an image processing method which enable the above.

[0007]

An image processing apparatus according to the present invention is an image processing apparatus for processing an output signal of a solid-state imaging device having a color filter having a predetermined color arrangement on a light receiving surface, and comprising: 1 / Sampling frequency
A frequency detection circuit for detecting the presence of the doubled frequency component and a correction processing circuit for performing a correction process on the input image based on the detection result of the frequency detection circuit are provided.

Further, an image processing method according to the present invention is an image processing method for processing an output signal of a solid-state imaging device having a color filter having a predetermined color array on a light receiving surface. Then, the presence of a frequency component that is halved is detected, and correction processing for the input image is performed based on the detection result.

In the image processing apparatus and the processing method having the above-described configuration, for example, when signal processing by correlation detection is performed, one signal for the spatial sampling frequency of the input image is used.
If there is a frequency component of / 2, it cannot be determined whether the vertical correlation is strong or the horizontal correlation is strong. Therefore, first, the presence of a half frequency component of the spatial sampling frequency is detected. Then, a correction process according to the presence or absence of the frequency component is performed. Specifically, when a frequency component that is １ ／ of the spatial sampling frequency exists, R /
G / B signals are output.

[0010]

Embodiments of the present invention will be described below in detail with reference to the drawings. FIG. 1 is a block diagram showing a basic configuration of an image processing apparatus according to the present invention. Here, the color solid-state imaging device to be processed by the image processing apparatus has, for example, R (red) G shown in FIG.
(Green) B (blue) primary color Bayer array color filter 11
On the light-receiving surface.

The color arrangement is not limited to the primary color Bayer arrangement, and the color filters are not limited to the RGB primary color arrangement. Even in the case of other primary color arrangements, complementary colors are used. Color array (for example, Ye / Cy
/ Mg / G) is also applicable. Also,
As the solid-state imaging device 12, a so-called all-pixel readout type CCD (Charge) that independently reads out signal charges of all pixels is used.
Coupled Device) Although a solid-state image sensor (hereinafter, referred to as a CCD area sensor) is used, the present invention is also applicable to a CCD solid-state image sensor that is not an all-pixel readout method.

R output from the CCD area sensor 12
The GB point sequential data is supplied to the detection unit 14 and the interpolation unit 15 after signal processing such as black level clamping and white balance is performed in the signal processing unit 13. The detection unit 14 detects an optimal interpolation method from the input RGB point sequential data, and sends the interpolation information to the interpolation unit 15. The interpolation unit 15 calculates R based on the interpolation information input from the detection unit 14.
Interpolation processing is performed on the GB point sequential data, and the data is output.

As shown in FIG. 3, a detecting unit 14 detects an fs / 2 detecting unit 16 for detecting a half frequency component of the spatial sampling frequency fs and a pixel to be interpolated (hereinafter referred to as an interpolated pixel). A total of 4 directions, ie, four directions at an angle that is an integral multiple of 90 ° with respect to the top, bottom, left and right, ie, two opposite directions in the vertical (V) direction and two opposite directions in the horizontal (H) direction
VH correlation detector 17 for detecting the degree of correlation in the direction, and the degree of correlation in the four directions forming an oblique direction of the upper right, upper left, lower left, and lower right with respect to the interpolated pixel, that is, forming an angle of 45 ° with the above four directions And an oblique correlation detection unit 18 for detecting the correlation.

In this example, in addition to the four directions of up, down, left and right,
Although a configuration for detecting the degree of correlation in a total of eight directions of four diagonal directions is taken as an example, a configuration for detecting the degree of correlation only in four directions of up, down, left, and right may be used. However, in the following description, the case of eight directions will be described as an example.

On the other hand, as shown in FIG.
An R interpolation unit 19 that performs an interpolation process on R pixel information based on interpolation information given from the detection unit 14, a G interpolation unit 20 that performs an interpolation process on G pixel information, and a B pixel information A B interpolation unit 21 that performs interpolation processing on fs / fs / based on detection information of the detection unit 14 and performs a correction processing that suppresses generation of noise on a hatch at fs / 2.
And a two-correction processing unit 22.

The fs / 2 detector 16, the VH correlation detector 17, and the oblique correlation detector 18 in the detector 14 will be described below.
Each configuration example will be described.

FIG. 5 is a block diagram showing an example of a specific configuration of the fs / 2 detector 16 in the detector 14.
FIG. 6 shows the spatial frequency-response characteristics of the pass filter in the fs / 2 detector 16.

The fs / 2 detector 16 has a filter characteristic in which the maximum value of the response of the passing frequency is a spatial frequency which is 1/2 of the spatial sampling frequency fs of the input image.
That is, the fs / 2 pass filter 23 having the characteristic A of FIG.
A filter characteristic in which the maximum value of the response of the passing frequency is a quarter frequency of the spatial sampling frequency fs of the input image, that is, an fs / 4 pass filter 24 having the characteristic B of FIG. 6, and these pass filters 23 and 24 Which detects a frequency component of fs / 2 based on each pass frequency component of f
An s / 2 detection circuit 25 is provided.

The fs / 2 detector 16 further has a luminance correction circuit 26 for correcting the level of the luminance Y0 by multiplying the level by a predetermined correction coefficient. Then, the luminance level corrected by the luminance correction circuit 26 is supplied to the fs / 2 detection circuit 25. The fs / 2 detection circuit 25 outputs fs /
Each of the pass frequency components of the 2,2 and fs / 4 pass filters 23 and 24 is compared, and the presence or absence of the fs / 2 frequency component is detected from the comparison result.

More specifically, if the difference between the pass frequency components of the fs / 2 and fs / 4 pass filters 23 and 24 is obtained, and the difference obtained by subtracting the brightness level corrected by the brightness correction circuit 26 from the difference is positive. For example, it is assumed that a frequency component of fs / 2 exists. Here, the reason why the luminance level is subtracted from the difference between the pass frequency components of the fs / 2 and fs / 4 pass filters 23 and 24 is to suppress the threshold from fluctuating due to the luminance. FIG. 7 is a conceptual diagram of the detection of the luminance Y0.

FIG. 8 shows fs / 2 in the fs / 2 detection circuit 25.
It is a conceptual diagram of s / 2 detection. In FIG. 8, the horizontal fs / 2 component and the vertical fs / 2 component that have passed through the fs / 2 pass filter 23 are converted into an absolute value (ABS; absolute) circuit 2.
After being converted into absolute values by 7, 28, they are added by an adder 29. Similarly, the horizontal fs / 4 component and the vertical fs / 4 component that have passed through the fs / 4 pass filter 24 are converted into absolute values by the absolute value conversion circuits 30 and 31, and then added by the adder 32. In the brightness correction circuit 26, the multiplier 3
In step 3, a process of multiplying the level of the luminance Y0 by a predetermined correction coefficient α is performed.

The addition output of the adder 29 becomes one input A of a subtractor 35 after being multiplied by a predetermined correction coefficient β in a multiplier 34. The addition output of the adder 32 is
6, a value obtained by multiplying the level of the luminance Y0 by a predetermined correction coefficient α is added, and an adder 37 adds a predetermined offset value γ
, Is the other input B of the subtractor 35. Here, the correction coefficient β and the offset value γ are parameters for determining the threshold.

The subtractor 35 subtracts one input A from the other input B. That is, in the subtractor 35, fs /
The two components (A) and the fs / 4 component (B) were compared (A-
B), the difference (A−B) is positive, that is, fs / 2 component> f
If the component is the s / 4 component, a determination result indicating that the frequency component of fs / 2 exists is issued. Then, the difference (A−B) is obtained through the look-up table (LUT) 38 to obtain the interpolation coefficient G.
Output as 2Gain. That is, the detected f
As the frequency component of s / 2 increases, the look-up table 38 outputs a larger value of the interpolation coefficient G2Gain.

FIG. 9 is a block diagram showing an example of a specific configuration of the VH correlation detecting section 17 and the oblique correlation detecting section 18. As shown in FIG.

The VH correlation detector 17 calculates a correlation value indicating the degree of correlation based on the pixel information of the pixel on the right side of the interpolation pixel. A left correlation value calculation circuit 42 that calculates a correlation value based on the pixel information, an upper correlation value calculation circuit 43 that calculates a correlation value based on pixel information of a pixel above the interpolation pixel, and pixel information of a pixel below the interpolation pixel. A lower correlation value calculation circuit 44 for calculating a correlation value based on
It is composed of a correlation value → interpolation gain conversion circuit 45 which converts each correlation value calculated in 1 to 44 into an interpolation gain and outputs the result.

In the VH correlation detector 17 having the above configuration,
From the correlation value → interpolation gain conversion circuit 45, gains for horizontal and vertical interpolation RGain, LGane, TGain, BGa
in and gain RGainD, L for horizontal / vertical RG interpolation
GainD, TGainD, and BGainD are output as interpolation coefficients.

The oblique correlation detector 18 calculates an upper correlation value calculation circuit 46 for calculating a correlation value based on the pixel information of the pixel on the upper right side of the interpolation pixel, and calculates the correlation value on the basis of the pixel information of the upper left pixel of the interpolation pixel. Upper left correlation value calculation circuit 4 for calculating a correlation value
7, a lower left correlation value calculation circuit 48 for calculating a correlation value based on pixel information of a pixel on the lower left side of the interpolation pixel, and a right side for calculating a correlation value based on pixel information of a pixel on the lower right side of the interpolation pixel. Lower correlation value calculation circuit 49 and these correlation value calculation circuits 4
The respective correlation values calculated in 6 to 49 are converted into interpolation gains, and oblique interpolation gains D1Gain to D4Ga are used as interpolation coefficients.
It is composed of a correlation value → interpolation gain conversion circuit 50 that outputs in.

Further, since the four horizontal and vertical directions and the four diagonal directions are not orthogonal to each other, the VH-diagonal comparison circuit 40 compares the horizontal and vertical correlation values with the diagonal correlation values to obtain a diagonal interpolation correction gain. VHGAIN, DGai
n is calculated as an interpolation coefficient.

Next, an example of the configuration of each of the R / G / B interpolation units and the fs correction processing unit 22 in the interpolation unit 15 will be described.

FIG. 10 is a block diagram showing an example of a specific configuration of the G interpolation unit 20. In FIG. 10, the G data after color separation is supplied to four horizontal and vertical directions, that is, right, left, upper, and lower correlation processing circuits 51, 52, 53, and 54, respectively. , 52,
At 53 and 54, the interpolation data Gr, Gl, G in four directions
t and Gb are generated. These interpolation data Gr, Gl,
Gt and Gb are generated by passing the LPF in the direction of interpolation.

The interpolation data Gr, Gl, Gt, Gb are supplied to multipliers 55, 56, 57, 58, respectively, to obtain interpolation coefficients determined by the VH correlation detecting section 17 shown in FIG. LGane, TGai
n and BGain, respectively. Then, the addition is performed by the adders 59 to 61, whereby the G interpolation processing is performed. The G image data after the interpolation processing is expressed by equation (1). G = Gr × RGain + Gl × LGain + Gt × TGain + Gb × BGain (1)

Similarly, for the four oblique directions, the upper right, upper left, lower left, and lower right correlation processing circuits 62, 63,
At 64 and 65, interpolation data in each direction of D1 / D2 / D3 / D4 is generated, and the multipliers 66, 67, 68, and 6 are generated.
9, the oblique interpolation gains D1Gain, D2Gain, D3 determined by the oblique correlation detector 18 shown in FIG.
After each of the gains is multiplied by Gain and D4Gain, the sum is added by adders 70 to 72 to perform an interpolation process.

Further, the G image data Gvh obtained by the horizontal / vertical four-direction correlation detection / interpolation and the G image data Gd obtained by the diagonal four-direction correlation detection / interpolation are mixed according to the situation as shown in equation (2) Is changed and added. The adjustment of the mixture ratio is performed by oblique interpolation correction gains VHGin and DGain calculated by the VH-oblique comparison circuit 40 shown in FIG. G = Gvh × VHGain + Gd × DGain (2)

FIG. 11 is a block diagram showing an example of a specific configuration of the R and B interpolation units 19 and 21. The configurations of the R and B interpolation units 19 and 21 are basically the same as the configuration of the G interpolation unit 20 shown in FIG. Therefore, FIG.
1, the same parts as those in FIG. 10 are denoted by the same reference numerals. However, the method of generating the interpolation data in the right, left, upper and lower correlation processing circuits 51 ', 52', 53 'and 54' is more complicated than in the case of G. There are two reasons for this: to perform correlation detection for RB interpolation and to add a G / 2 component to RB.

For this reason, the correlation detection for RG interpolation is performed separately for horizontal (right, left) interpolation data and vertical (up, down) interpolation data. Specifically, R pixel and B pixel
When interpolating the R signal / B signal from the pixel signal, the above-described horizontal and vertical RB interpolation gains RGainD and LGain are used.
D, TGainD, and BGainD are calculated and used as interpolation coefficients dedicated to R / B. Since this is not the gist of the present invention, its detailed description is omitted here.

FIG. 12 is a block diagram showing an example of a specific configuration of the fs / 2 correction processing section 22.

In FIG. 12, the RGB signal is fs / 2
The signal is input to the trap circuit 101. As shown in the characteristic diagram of FIG. 13, the fs / 2 trap circuit 101 is configured by a filter having a characteristic that a response of a frequency component of a half of a spatial sampling frequency fs of an input image is 0. The trap output of the fs / 2 trap circuit 101 is multiplied by the interpolation coefficient G2Gain from the fs / 2 detector 16 by the multiplier 102, and then becomes one input of the adder 103.

The R / G / B interpolation units 19, 20,
Each interpolation output RIP / GIP / BIP supplied from 21
Is multiplied by the interpolation coefficient G2Gain ′ calculated from the interpolation coefficient G2Gain from the fs / 2 detector 16 by the multiplier 104, and then becomes the other input of the adder 103. The interpolation coefficient G2Gain 'is calculated, for example, by subtracting the interpolation coefficient G2Gain from a constant. FIG.
5 is a conceptual diagram of a correction process in the fs / 2 correction processing unit 22. As is evident from this conceptual diagram, the correction process is R
/ G / B for each signal.

In the fs / 2 correction processing section 22 having the above configuration, the R / G / B signals passed through the fs / 2 trap circuit 101 and the R / G / B interpolation sections 19, 20, and 21 supply the signals. The respective interpolation outputs RIP / GIP / BIP are mixed in the adder 103, and the mixing ratio is determined by the interpolation coefficient G2Gai provided from the fs / 2 detector 16.
n.

Specifically, the fs / 2 detector 16
When the frequency component of fs / 2 is detected, the interpolation coefficient G2Gain having a larger value is output as the frequency component increases,
The interpolation coefficient G2Gain is multiplied by the R / G / B signals passed through the fs / 2 trap circuit 101 by the multiplier 102, and the interpolation coefficient G2Gain 'calculated from the interpolation coefficient G2Gain is interpolated by the multiplier 104 to the interpolation output RIP /
Multiplied by GIP / BIP. Then, the multiplier 102,
Each of the multiplication outputs 104 is added (mixed) by the adder 103 and output.

In other words, in the fs / 2 correction processing unit 22, when the fs / 2 detection unit 16 detects the presence of the fs / 2 frequency component, the fs / 2 detection unit 16 extracts the fs / 2 signal from each of the R / G / B signals.
Is mainly output after removing the frequency component of fs /
When the 2 detector 16 does not detect the presence of the frequency component of fs / 2, the interpolation output RIP / GIP / BIP interpolated by the R / G / B interpolation units 19, 20, and 21 is output. Then, as the value of the interpolation coefficient G2Gain increases, the mixing ratio of the R / G / B signal from which the frequency component of fs / 2 has been removed to the interpolation output RIP / GIP / BIP increases. .

As described above, the presence of the fs / 2 frequency component is detected, and when the presence is detected, the R / G /
Instead of using the interpolation output RIP / GIP / BIP interpolated by each of the B interpolation units 19, 20, and 21, the R / G / B signals from which the frequency component of fs / 2 has been removed are used. Accordingly, when signal processing by correlation detection is performed, even if there is a spatial frequency of fs / 2, erroneous detection of correlation detection near fs / 2 can be prevented, so that an image without failure can be reproduced. Become.

FIG. 15 is a schematic configuration diagram showing an example of the camera according to the present invention. In FIG. 15, incident light from a subject is imaged on a light receiving surface (imaging surface) of the CCD area sensor 112 by an optical system including a lens 111 and the like.
On the light receiving surface of the CCD area sensor 112, a color filter 113 having a color array of, for example, a primary color Bayer array is provided. The CCD area sensor 112 is driven and controlled by the CCD driving circuit 114 such as exposure, reading out and transferring signal charges, and the like.

The output signal of the CCD area sensor 112 is supplied to an image processing device 115, where various signal processing is performed. The image processing device 115 detects correlations in eight directions, that is, horizontal, vertical, and diagonal directions, performs adaptive interpolation processing based on the detection results, and removes the frequency components when fs / 2 is detected. The image processing apparatus according to the above-described embodiment having a configuration using the signal is used.

As described above, for example, in a camera using the CCD area sensor 112 having the color filters 113 of the primary color Bayer array as an imaging device, when performing signal processing by correlation detection, a spatial frequency component of fs / 2 exists. However, it is possible to prevent erroneous detection of the correlation detection near fs / 2, to enable reproduction of an image without failure, and to eliminate the need to set the response near fs / 2 to 0 using an optical LPF. Since the spatial frequency that becomes 0 can be increased, the resolution / resolution of the reproduced image can be improved.

[0046]

As described above, according to the present invention,
When processing an output signal of a solid-state imaging device having a color filter on a light receiving surface, the presence of a frequency component of fs / 2 is detected, and when the presence is detected, the frequency component of fs / 2 is removed. By using each signal of / G / B, erroneous detection of correlation detection near fs / 2 can be prevented, so that an image without failure can be reproduced. Moreover, since there is no need to limit the band using the optical LPF, the resolution / resolution of the reproduced image is not impaired.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a basic configuration of an image processing apparatus according to the present invention.

FIG. 2 is a primary color Bayer array diagram of a color filter.

FIG. 3 is a block diagram illustrating an example of a configuration of a detection unit.

FIG. 4 is a block diagram illustrating an example of a configuration of an interpolation unit.

FIG. 5 is a block diagram illustrating an example of a specific configuration of an fs / 2 detection unit.

FIG. 6 is a characteristic diagram of a spatial frequency-response of a pass filter in an fs / 2 detection unit.

FIG. 7 is a conceptual diagram of detection of luminance Y0.

FIG. 8 is a conceptual diagram of fs / 2 detection.

FIG. 9 is a block diagram illustrating an example of a specific configuration of a VH correlation detection unit and an oblique correlation detection unit.

FIG. 10 is a block diagram illustrating an example of a specific configuration of a G interpolation unit.

FIG. 11 is a block diagram illustrating an example of a specific configuration of an R and B interpolation unit.

FIG. 12 is a block diagram illustrating an example of a specific configuration of an fs / 2 correction processing unit.

FIG. 13 is a characteristic diagram of the fs / 2 trap circuit.

FIG. 14 is a conceptual diagram of an fs / 2 correction process.

FIG. 15 is a schematic configuration diagram illustrating an example of a camera according to the present invention.

FIG. 16 is a diagram for explaining a problem.

[Explanation of symbols]

11, 113: color filter, 12, 112: CCD
Area sensor, 14 ... detector, 15 ... interpolator, 16 ... f
s / 2 detection section, 17 VH correlation detection section, 18 diagonal correlation detection section, 19 R interpolation section, 20 G interpolation section, 21 B interpolation section, 22 fs / 2 correction processing section, 23 fs / 2 pass filter, 24 ... fs / 4 pass filter, 25 ... fs /
2 detection circuit, 26: luminance correction circuit

Claims (12)

[Claims] 1. An image processing apparatus for processing an output signal of a solid-state imaging device having a color filter having a predetermined color array on a light receiving surface, comprising a frequency component that is １ ／ times a spatial sampling frequency of an input image. An image processing apparatus, comprising: a frequency detection circuit that detects the presence of an image; and a correction processing circuit that performs a correction process on an input image based on a detection result of the frequency detection circuit. 2. The frequency detection circuit according to claim 1, wherein a maximum value of a response of a passing frequency is a first filter whose spatial frequency is a half of a spatial sampling frequency of the input image, and a maximum value of a response of a passing frequency is By comparing a second filter having a spatial frequency of 1/4 of the spatial sampling frequency of the input image with each pass frequency component of the first and second filters, a frequency component of 1/2 of the spatial sampling frequency is obtained. The image processing apparatus according to claim 1, further comprising: a detection unit configured to detect an image. 3. The image according to claim 2, wherein said frequency detection circuit has means for subtracting an average signal level of a pixel near a pixel to be interpolated from a passing frequency component of said first filter. Processing equipment. 4. The correction processing circuit adds the first and second signals that have passed through at least two systems of the first and second signal processing systems at a mixing ratio according to a detection output of the frequency detection circuit. The image processing apparatus according to claim 1, wherein: 5. The signal processing system according to claim 1, wherein the first signal processing system includes a third filter having a response of a frequency component of a half of a spatial sampling frequency of the input image being 0, and a pass frequency component of the third filter. 5. The image processing apparatus according to claim 4, wherein the second signal processing system outputs, as the second signal, a result of performing an interpolation process on the input image. 6. . 6. The image processing apparatus according to claim 5, wherein the correction processing circuit increases a mixing ratio of the first signal in accordance with an increase in a detection output of the frequency detection circuit. 7. An image processing method for processing an output signal of a solid-state imaging device having a color filter having a predetermined color array on a light receiving surface, comprising a frequency component that is １ ／ times a spatial sampling frequency of an input image. An image processing method comprising: detecting the presence of an image; and performing an interpolation process on the input image based on the detection result. 8. In the correction processing, at least two
The system according to claim 1, wherein the first and second signals passed through the first and second signal processing systems of the system are added at a mixing ratio according to a detection result of a frequency component that is 1/2 of the spatial sampling frequency. 7. The image processing method according to 7. 9. The first signal is a signal obtained by removing a half frequency component with respect to the spatial sampling frequency from an input image, and the second signal is obtained by performing an interpolation process on an input image. 9. The image processing method according to claim 8, wherein the signal is a processed signal. 10. A solid-state imaging device having a color filter having a predetermined color arrangement on a light-receiving surface, an optical system for forming an incident light from a subject on a light-receiving surface of the solid-state imaging device, and a solid-state imaging device. A camera comprising: an image processing device that processes an output signal, wherein the image processing device detects the presence of a frequency component that is 倍 times the spatial sampling frequency of an input image; A correction processing circuit for performing correction processing on the input image based on a detection result of the frequency detection circuit. 11. The correction processing circuit adds a first signal and a second signal that have passed through at least two systems of first and second signal processing systems at a mixing ratio according to a detection output of the frequency detection circuit. The camera according to claim 10, wherein: 12. The first signal processing system includes a third filter having a response of a frequency component of の of a spatial sampling frequency of an input image being 0, and a pass frequency component of the third filter. 12. The camera according to claim 11, wherein the second signal processing system outputs a result obtained by performing an interpolation process on an input image as the second signal.