JP2006295807A - Imaging apparatus, image processing method, program, and storage medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To obtain a high quality image by reducing image deterioration caused by a characteristic unique to a lens.
An imaging device that converts light from a subject into a video signal, imaging lens information acquisition means that acquires information related to the imaging lens, and image quality degradation that occurs in the video signal based on the information related to the imaging lens. A correction unit, a noise reduction processing unit that performs noise reduction processing on the output signal of the correction unit, and a region that includes a pixel of interest that performs the noise reduction processing from the output signal of the correction unit have predetermined characteristics. A discriminating means for discriminating whether or not the area has
And when the region including the target pixel is determined to be a region having a predetermined characteristic by the determination unit, the noise is determined according to the position in the screen based on the correction amount of the correction unit. Change the noise suppression level in the reduction process.
[Selection] Figure 1

Description

  The present invention relates to an image pickup apparatus, and more particularly to an image pickup apparatus and an image processing method in which distortion due to characteristics of an optical lens and image quality deterioration due to a decrease in peripheral light amount are corrected by image processing.

  In an imaging device that captures subject image information via an optical system or imaging device, and performs various signal processing and outputs a video signal, the pixel position on the imaging surface depends on the optical characteristics of the lens as the pixel position moves away from the center of the optical axis. Adversely affects the image quality.

  Specifically, there are an “optical distortion” phenomenon in which the geometric shape is distorted toward the peripheral portion of the image, and a “peripheral light amount drop” (shading) phenomenon in which the light amount decreases toward the peripheral portion of the image.

  Conventionally, in order to correct “optical distortion” caused by a lens, an imaging apparatus that converts a video signal into a digital signal, writes it in an image memory, reads out it according to distortion characteristics, and performs interpolation processing has been proposed (for example, (See Patent Document 1).

In addition, in order to correct the “peripheral light loss” caused by the lens, a digital camera that multiplies the correction value according to the distance from the center so that the peripheral part where the light intensity decreases becomes the same amount as the central part is proposed. (For example, see Patent Document 2).
JP-A-2-252375 JP 2001-275029 A

  However, in the above conventional example, by correcting image quality deterioration (optical distortion, peripheral light loss) caused by the optical characteristics of the lens by increasing the gain, the S / N varies within the screen, and the image quality is adversely affected. That was not taken into account.

  For example, in Patent Document 1, by performing optical distortion correction, interpolation processing is also applied to noise generated on the image sensor regardless of the optical characteristics of the lens. Due to the difference in size, there is a problem that the degree of modulation with respect to noise changes, the graininess of noise varies, and image quality deteriorates.

  Further, in Patent Document 2, there is a problem that the noise level is increased by increasing the gain of the peripheral portion where the amount of light has dropped, and the noise level varies between the central portion and the peripheral portion of the screen.

  In either case, the S / N deteriorated from the center of the screen to the periphery depending on the degree of correction of the image quality deterioration phenomenon caused by the optical characteristics of the lens.

An imaging device of the present invention includes an imaging device that converts light from a subject into a video signal;
Imaging lens information acquisition means for acquiring information about the imaging lens;
Correction means for correcting image quality degradation that occurs in the video signal based on information about the imaging lens;
Noise reduction processing means for performing noise reduction processing on the output signal of the correction means;
Discriminating means for discriminating whether or not an area including the target pixel for performing the noise reduction processing is an area having a predetermined characteristic from an output signal of the correcting means;
Have
When it is determined in the determining means that the region including the target pixel is a region having a predetermined characteristic,
The noise suppression level in the noise reduction processing is changed according to the position in the screen based on the correction amount in the correction means.

Further, the image processing method of the present invention includes an imaging lens information acquisition step of acquiring information related to the imaging lens,
A correction step of correcting image quality degradation that occurs in a video signal obtained from an image sensor based on information about the imaging lens;
A noise reduction processing step of performing noise reduction processing on the output signal of the correction step;
A determination step of determining whether or not the region including the target pixel for performing noise reduction processing is a region having a predetermined characteristic from the output signal of the correction step;
When it is determined in the determination step that the region including the target pixel is a region having a predetermined characteristic,
The noise suppression level in the noise reduction processing is changed according to the position in the screen based on the correction amount in the correction step.

  According to the image pickup apparatus of the present invention, for example, due to lens-specific characteristics, for example, optical distortion correction and peripheral light loss correction are corrected by image processing. It is possible to reduce image degradation and obtain a high-quality image.

  Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

(First Embodiment 1)
FIG. 1 shows a schematic block diagram of an imaging apparatus according to the first embodiment of the present invention. The present embodiment is a configuration for reducing S / N degradation at the periphery of the screen, which occurs due to optical distortion correction of the lens.

  In FIG. 1, 001 is an optical lens, 002 is an image sensor, 003 is an A / D conversion processing unit, and 004 is an image sensor driving unit. An image signal is read from the image sensor at a predetermined timing by a control signal from the image sensor driving unit, and A / D conversion is performed to obtain a digital image signal including optical distortion. Reference numeral 006 denotes a microcomputer that controls lens position control (focus and shift control), optical distortion correction processing, and noise reduction processing.

  Reference numeral 007 denotes an optical distortion correction processing unit as correction means, which includes a memory circuit 014 and an interpolation circuit 015 for holding an image for one frame.

  008 is a discriminating means for discriminating whether or not the subject region including the target pixel to be corrected is a region having a predetermined characteristic, that is, a flat portion with respect to the image signal after the optical distortion correction processing. The subject area determination processing unit. Reference numeral 009 denotes a noise reduction processing unit that performs noise reduction processing on the video signal after the optical distortion correction processing as noise reduction processing means.

  Reference numeral 010 denotes a camera signal processing unit that performs luminance / chrominance signal generation processing, aperture processing, gamma processing, and the like (not shown), and outputs a final video signal from the video signal output terminal 011.

  Next, processing in the optical distortion correction processing unit 007 will be described with reference to the flowcharts of FIGS.

  In the optical distortion correction processing unit 007, first, an image including optical distortion after A / D conversion is held in the memory circuit 014 (S151). For example, when a subject as shown in FIG. 2A is photographed, an image of the subject distorted like a pincushion as shown in FIG. 2B due to the aberration of the imaging lens is taken into the memory circuit 014 as a digital image. It is. In FIG. 2B, x and y are coordinate axes indicating the position of each pixel in the image.

  Next, until reading of all pixels is completed in order from the first pixel (S152), the memory circuit 014 reads pixel values in a predetermined area necessary for optical distortion correction in accordance with distortion characteristic sampling information input from the microcomputer (S152). S153).

  Here, the distortion characteristic sampling information is two-dimensional address map data for sampling an image including optical distortion stored in the memory circuit 014 along the distortion characteristic peculiar to the lens, and is information regarding the imaging lens. It is calculated by a microcomputer as an imaging lens information acquisition unit using the lens-specific distortion correction characteristic data stored in a certain 005 and position information by lens control (focus, shift).

  FIG. 3A shows an example in which a part of the optical distortion image shown in FIG. 2B is sampled along the distortion characteristic sampling information. In FIG. 3A, a white circle represents a sampling point of the distorted image along the distortion characteristic sampling information, and one square of the mesh corresponds to one pixel of the image.

  The memory circuit 014 reads a plurality of neighboring pixels for the sampling point indicated by the distortion characteristic sampling information. For example, in FIG. 3A, when a point 3a is designated as distortion characteristic sampling information, four pixels 31, 32, 33, and 34 near the point 3a are read from the memory circuit.

  Next, the optical distortion correction amount is obtained by calculating the optical distortion correction amount from the distortion characteristics of the lens 005, the lens control position information, and the distance information from the optical axis in the screen by the microcomputer (S154).

  Next, in the interpolation circuit 015, interpolation processing for optical distortion correction is performed using the pixel read from the memory circuit in S153 and the optical distortion correction amount calculated by the microcomputer in S154 (S155).

  FIG. 5 shows an example of the relationship between the optical distortion correction amount and the distance from the optical axis. Reference numerals 5a and 5b indicate characteristics when the distance between the lens and the imaging surface is short and when the distance is long.

  As shown in FIG. 5, the optical distortion correction amount increases as the distance from the optical axis increases. Further, the size of the area that requires optical distortion in the entire screen changes depending on the distance between the lens and the imaging surface.

  FIGS. 2C and 3B are images after optical distortion correction, and FIG. 3B is an enlarged view of a region surrounded by a broken line in FIG. 2C. The pixel 3b is a pixel after optical distortion correction corresponding to the point 3a on the optical distortion image of FIG. 3A, and is calculated by the four pixels 31, 32, 33, and 34 around the point 3a and by a microcomputer. It is generated by an interpolation process using an optical distortion correction amount.

  By performing the above processing on all the pixels (S152), the distortion is corrected as shown in FIG. 2C from the pincushioned image shown in FIG. 2B. An image can be obtained.

  In the present embodiment, the pincushion type optical distortion has been described as an example. However, even in the case of a barrel type optical distortion, the optical distortion correction can be performed by the same method.

  By the way, the image signal input to the optical distortion correction processing unit is superimposed with noise generated in a processing system subsequent to the imaging lens, such as an imaging element or A / D conversion. This noise itself has no optical distortion due to the aberration of the imaging lens, and is uniformly distributed on the screen as shown in FIG. However, since it is superimposed on the image data of the subject that receives optical distortion, the optical distortion correction process as described above is applied to noise.

  For example, when pincushion type optical distortion correction is performed, interpolation processing is performed in the direction indicated by the arrow in FIG. 4B according to the pixel position, so that the noise shape is identified by interpolation. As if stretched in the direction of. Furthermore, since the distortion correction amount differs depending on the pixel position, the noise shape after interpolation in the screen varies.

  Such noise shape variations degrade the quality of the entire image. In the present embodiment, in the noise reduction processing unit 9 shown in FIG. 1, the noise reduction processing level for each pixel is based on the optical distortion correction amount. Control to change (degree) is performed.

  Next, processing in the noise reduction processing unit 9 in FIG. 1 will be described in detail using the flow in FIG.

  The noise reduction processing unit 9 first calculates a coefficient indicating the noise suppression level using the optical distortion correction amount as a parameter.

In the present embodiment, as shown in FIG. 6, the noise suppression level is calculated by the following equation, where D is the optical distortion correction amount and N is the coefficient indicating the noise suppression level (S161).
i) When 0 ≦ D <D1, N = n0 + {(n1-n0) / D1} * D
ii) When D1 ≦ D <D2, N = n1 + {(n2-n1) / (D2-D1)} * (D-D1)
iii) When D2 ≦ D <D3 N = n2 + {(n3-n2) / (D3-D2)} * (D-D2)
iv) When D3 ≦ D, N = n3

  FIG. 7 is a diagram in which the noise suppression level N based on the optical distortion correction amount D is mapped on the screen. As shown in FIG. 7, the noise reduction level increases as it goes to the periphery of the screen. When the position of the lens in the optical axis direction is changed by focus control, the concentric noise suppression level distribution shown in FIG. 7 is changed. When the lens is translated with respect to the imaging surface by shift control, FIG. The center position of the concentric circle indicated by 7 changes.

  Specific examples of the noise reduction process include a method of suppressing a high frequency component of noise by a low-pass filter and a method of base clipping by regarding a small amplitude signal as noise.

  In the former method, as the distance from the optical axis increases, noise suppression is performed more strongly. Therefore, control is performed to narrow the band of the low-pass filter using the above-described noise suppression level as a parameter.

  In the latter method, noise suppression is more strongly performed as the distance from the optical axis increases. Therefore, the threshold of the amplitude level of a signal regarded as noise is increased using the above-described noise suppression level as a parameter, and the base Control to clip.

  In either case, the greater the noise suppression level, the stronger the degree of processing that blurs the image, so paying attention only to noise and performing such noise reduction processing control ignoring subject information, depending on the subject, The greater the distance from the optical axis, the lower the resolution. Therefore, in the present embodiment, the subject region determination processing unit 8 in FIG. 1 determines whether or not the subject region including the pixel of interest is a flat portion where noise shape variation is conspicuous, and according to the determination result, The noise reduction processing based on the distortion correction amount is adaptively controlled.

  Here, with reference to FIG. 8 and FIG. 9, the operation of the subject region discrimination processing unit 8 in S162 will be described.

  FIG. 8 is a schematic diagram illustrating the arrangement of pixels in a part of an image input to the subject area determination processing unit. The subject area discrimination processing unit 008 detects the correlation in the vertical, horizontal, diagonal 45 °, and diagonal 135 ° directions for the pixel of interest and the peripheral pixels, respectively, and if the correlation is low in any direction, a flat region It is determined that

For example, when P4 shown in FIG. 8 is the pixel of interest, first, the following calculation is performed on the surrounding eight pixels. Here, Vdiff, Hdiff, D1diff, and D2diff are correlation values in the vertical, horizontal, diagonal 45 °, and diagonal 135 ° directions, respectively.
Vdiff = | P1-P7 |
Hdiff = | P3-P5 |
D1diff = | P2-P6 |
D2diff = | P0−P8 |

Next, the following threshold determination is performed on the correlation value Max_diff having the largest value among Vdiff, Hdiff, D1diff, and D2diff, and the flatness fl indicating how flat the subject region including the target pixel is calculated. To do.
i) When 0 ≦ Max_diff <Th1, fl = 1.0
ii) When Th1 ≦ Max_diff <Th2, fl = (Th1−Max_diff) / (Th2−Th1) +1
iii) Th2 ≦ Max_diff
fl = 0.0
The relationship between the correlation value Max_diff and the flatness fl is as shown in FIG. 9. When fl = 1.0, the relationship is completely flat, and when fl = 0.0, the subject includes an edge. I reckon.

  The noise discrimination processing unit 9 in FIG. 1 controls the final noise suppression level using a value obtained by multiplying the above-described noise suppression level N by the flatness fl output from the subject region discrimination unit as a parameter.

  Therefore, the optical distortion correction amount is referred to only when the flatness fl = 1.0, that is, when it is estimated that the pixel of interest is included in a flat portion where noise shape variation is conspicuous, and the optical axis and the pixel of interest The noise reduction processing is performed so that the level (degree) of noise suppression increases as the distance between and increases (S163).

  Further, when the flatness fl = 0.0, that is, the subject area including the target pixel is an edge portion of the image, noise reduction processing based on the optical distortion correction amount is performed with priority on resolution. Can not be.

  At this time, when the flatness fl takes a value between 0.0 and 1.0, the degree of application of the noise discrimination processing based on the optical distortion correction amount may be varied according to the flatness. .

  As described above, for the image after the optical distortion correction processing due to the aberration of the lens, the resolution for the edge portion is maintained, while the flat portion is adapted to reduce the noise shape variation due to the optical distortion correction processing. Noise reduction processing can be performed. The image after the noise reduction processing is output from the video signal output terminal as a final video signal through camera signal processing (S164).

(Second Embodiment)
FIG. 10 shows a schematic block diagram of an imaging apparatus according to the second embodiment of the present invention.

  The present embodiment is configured to reduce S / N degradation in the peripheral portion of the screen, which is caused by correction of the peripheral light amount of the lens.

  In FIG. 10, 101 is an imaging lens, 102 is an imaging device, 103 is an A / D conversion processing unit, and 104 is an imaging device driving unit. An image signal is read from the image sensor at a predetermined timing by a control signal from the image sensor driving unit, and A / D conversion is performed to obtain a digital image signal including optical distortion. Reference numeral 106 denotes a microcomputer that controls lens position control (focus and shift control), peripheral light amount drop correction processing, and noise reduction processing.

  Reference numeral 107 denotes a peripheral light amount drop correction processing unit as correction means, and includes a memory circuit 114 for holding an image for one frame and an amplifier circuit 115 therein.

  Reference numeral 108 denotes a subject area determination process as a determination unit that determines whether or not the subject area including the target pixel is a region having a predetermined characteristic, that is, a flat portion, with respect to the image signal after the peripheral light amount drop correction process. Part. Reference numeral 109 denotes a noise reduction processing unit as noise reduction processing means for performing noise reduction processing on the video signal after the peripheral light amount drop correction processing.

  A camera signal processing unit 110 performs luminance / chrominance signal generation processing, aperture processing, gamma processing, and the like (not shown), and a final video signal is output from the video signal output terminal 111.

  Next, processing in the peripheral light amount drop correction processing unit 107 will be described. The processing is the same as the flow of FIG. 15 except that the optical distortion correction of the first embodiment is changed to the peripheral light amount drop correction, and is omitted.

  First, the internal memory circuit 114 captures an image with a reduced light amount level around the image as shown in FIG. In FIG. 11, x and y are coordinate axes indicating the position of each pixel in the image.

  Next, in the memory circuit 114, the pixel data designated by the pixel address information from the microcomputer 106 is read from the memory and sent to the amplifier circuit 115 in the subsequent stage.

  In the microcomputer 106 as the imaging lens information acquisition means, the peripheral light amount drop correction amount corresponding to the distance from the optical axis is calculated using the characteristics of the imaging lens, which is information about the imaging lens, and the positional information of the imaging lens and the imaging element. Calculate for each pixel. The peripheral light amount drop correction amount has characteristics as shown in FIG. 13 with respect to the distance from the optical axis. Reference numerals 13a and 13b denote characteristics when the distance between the lens and the imaging surface is short and when the distance is long.

  As the distance from the optical axis in the screen increases, the peripheral light amount drop correction amount also increases. In addition, the size of the area in the screen that needs to be corrected for the decrease in peripheral light amount varies depending on the positional relationship between the lens and the image sensor.

  Next, the amplification circuit 115 reads the corresponding peripheral light amount drop correction amount from the microcomputer for the pixel input from the memory circuit 114, and gains the pixel value of the pixel of interest with an amplification factor according to the peripheral light amount drop correction amount. Call. As a result, as shown in FIG. 11B, the peripheral light amount drop caused by the lens is corrected, and the brightness of the entire screen becomes substantially uniform.

  By the way, the image signal that is input to the peripheral light amount drop correction processing unit is also superimposed with noise that does not depend on the light amount in the subsequent processing system of the imaging lens, such as an image sensor or A / D conversion. Yes. When the peripheral light amount drop correction process as described above is applied to noise that exists uniformly on the entire screen as shown in FIG. 12A regardless of the peripheral light amount drop of the imaging lens, As in 12 (b), noise is amplified in the peripheral portion of the screen, and the S / N becomes worse.

  Since such noise level variations degrade the quality of the entire image, in this embodiment, the noise reduction processing unit 109 shown in FIG. 10 suppresses noise reduction processing for each pixel based on the peripheral light amount drop correction amount. Control to change the level (degree).

  Next, processing in the noise reduction processing unit 109 will be described in detail. The processing is the same as the flow of FIG. 16 except that the optical distortion correction of the first embodiment is changed to the peripheral light amount drop correction, and the description thereof is omitted.

  First, the noise reduction processing unit 109 calculates a coefficient indicating a noise suppression level using the above-described peripheral light amount drop correction amount as a parameter.

In the present embodiment, the noise suppression level N is calculated by the following equation using the peripheral light amount drop correction amount L.
i) When 0 ≦ L <L1, N = n0 + {(n1-n0) / L1} * L
ii) When L1 ≦ L <L2, N = n1 + {(n2−n1) / (L2−L1)} * (L−L1)
iii) When L2 ≦ L <L3 N = n2 + {(n3−n2) / (L3−L2)} * (L−L2)
iv) When L3 ≦ L, N = n3
The relationship between the noise suppression level N calculated by the above series of expressions and the peripheral light amount drop correction amount L is as shown in the graph of FIG.

  Further, when the noise suppression level N based on the peripheral light amount drop correction amount L is mapped on the screen, as shown in FIG. 7, the noise suppression level increases in the peripheral portion of the image. Here, when the position of the lens in the optical axis direction is changed by focus control, the distribution of concentric noise suppression levels shown in FIG. 7 is changed, and when the lens is moved parallel to the imaging surface by shift control, The center position of the concentric circle shown in FIG. 7 changes.

  Specific examples of the noise reduction processing performed by the noise reduction processing unit 109 include a suppression method using a low-pass filter, a base clip of a small amplitude signal, and the like, as in the first embodiment.

  In either case, the greater the noise suppression level, the stronger the degree of processing that blurs the image, so paying attention only to noise and performing such noise reduction processing control ignoring subject information, depending on the subject, The greater the distance from the optical axis, the lower the resolution. Therefore, in the present embodiment, the subject region determination processing unit 108 in FIG. 10 estimates whether or not the subject region including the target pixel is a flat portion in which noise shape variation is conspicuous. The noise reduction processing based on the light amount drop correction amount is adaptively controlled.

Here, the operation of the subject area discrimination processing unit 8 will be described. FIG. 8 is a schematic diagram illustrating the arrangement of pixels in a part of an image input to the subject area determination processing unit 108. In the subject area discrimination processing unit 8, when P4 shown in FIG. 8 is the target pixel, first, the following calculation is performed on the surrounding eight pixels. Here, Vdiff, Hdiff, D1diff, and D2diff represent correlation values in the vertical, horizontal, diagonal 45 °, and diagonal 135 ° directions, respectively.
Vdiff = | P1-P7 |
Hdiff = | P3-P5 |
D1diff = | P2-P6 |
D2diff = | P0−P8 |

By the way, the image after the peripheral light amount drop correction process is gained up and the noise amplitude level is increased as the pixels in the peripheral part of the screen, so the correlation values Vdiff, Hdiff, D1diff, and D2diff in four directions are large. With this alone, it is difficult to distinguish between noise with a large amplitude level superimposed on a flat portion and edges that are continuous in a specific direction. Therefore, in the present embodiment, the following determination is performed using the difference value HV_diff = | Vdiff−Hdiff |, D12diff = D1diff = D1diff−D2diff | A flatness fl indicating how flat the region is is calculated.
i) When (HV_diff> Th_edg and D12_diff> Th_edg) or (HV_diff ≦ Th_edg and D12_diff ≦ Th_edg),
Since it is unlikely that the edges are continuous in a specific direction,
fl = 1.0
ii) When (HV_diff> Th_edg and D12_diff ≦ Th_edg) or (HV_diff ≦ Th_edg and D12_diff> Th_edg),
Since there is a high possibility that the edges are continuous in a specific direction, the following determination is made as the correlation value Max_diff having the largest value among Vdiff, Hdiff, D1diff, and D2diff, and the flatness fl is calculated.
a) When 0 ≦ Max_diff <Th1, fl = 1.0
b) When Th1 ≦ Max_diff <Th2 fl = (Th1−Max_diff) / (Th2−Th1) +1
c) Th2 ≦ Max_diff
fl = 0.0
Here, the relationship between the correlation value Max_diff and the flatness fl is as shown in FIG. 9. When fl = 1.0, the relationship is completely flat, and when fl = 0.0, the subject includes an edge. It is considered.

  The noise reduction processing unit 109 in FIG. 10 controls the final noise suppression level using a value obtained by multiplying the above-described noise suppression level N by the flatness fl output from the subject region estimation unit.

  Accordingly, only when it is estimated that the flatness fl = 1.0, that is, the pixel of interest is included in a flat portion where noise with a large amplitude level is conspicuous, the peripheral light amount drop correction amount is referred to and the optical axis and Noise reduction processing can be performed so that the level (degree) of noise suppression increases as the distance from the pixel of interest increases.

  Further, when the flatness fl = 0.0, that is, when the subject area including the target pixel is highly likely to be an edge portion of the image, the resolution is given priority and the amount of peripheral light loss is corrected. It is possible not to perform noise reduction processing.

  When the flatness fl takes a value between 0.0 and 1.0, the degree of application of the noise reduction processing based on the peripheral light amount drop correction amount can be varied according to the flatness.

  As described above, with respect to the image after the peripheral light amount drop correction processing due to the characteristics of the imaging lens, the resolution of the edge portion is maintained, and the noise level variation due to the peripheral light amount drop correction processing is reduced in the flat portion. Therefore, adaptive noise reduction processing can be performed. The image after the noise suppression processing is output from the video signal output terminal as a final video signal through camera signal processing.

(Other embodiments)
In the above-described first and second embodiments, the optical distortion correction amount and the peripheral light amount drop correction amount are respectively set by the microcomputer 006 using the lens-specific distortion characteristic data and the peripheral light amount drop characteristic data lens position information. The configuration is such that it is calculated and stored in the memories 014 and 114. This correction amount may be stored in advance in a table in a ROM memory (not shown) as a correction amount for lens position information. As a result, each correction processing unit can easily and more quickly perform the correction process of acquiring the correction amount by referring to the table without performing a calculation.

  Further, the present invention is not limited to an imaging device in which an imaging unit and an optical lens are integrated, and can also be applied to an imaging device in which a lens can be attached and detached. In that case, each interchangeable lens may hold a chip storing distortion characteristic data unique to the lens, peripheral light amount drop characteristic data, or a correction amount table corresponding to lens position information.

  Further, the optical distortion correction of the first embodiment and the peripheral light amount drop correction of the second embodiment can be performed in combination. In that case, an optimal noise suppression level coefficient may be set for both correction amounts.

  Another object of the present invention is to supply a storage medium storing software program codes for realizing the functions of the above-described embodiments to, for example, an imaging apparatus, and store the system or apparatus computer (or CPU or MPU). Needless to say, this can also be achieved by reading and executing the program code stored in the medium by remote operation from the system or apparatus.

  In this case, the program code itself read from the storage medium realizes the functions of the above-described embodiments, and the storage medium storing the program code constitutes the present invention.

  As a storage medium for supplying the program code, for example, a floppy (registered trademark) disk, a hard disk, an optical disk, a magneto-optical disk, a CD-ROM, a CD-R, a magnetic tape, a nonvolatile memory card, a ROM, or the like is used. I can do it.

  Further, by executing the program code read by the computer, not only the functions of the above-described embodiments are realized, but also an OS (operating system) operating on the computer based on the instruction of the program code. It goes without saying that a case where the function of the above-described embodiment is realized by performing part or all of the actual processing and the processing is included.

  Furthermore, for example, when performing noise reduction processing when processing a captured image with an information processing apparatus such as a personal computer after imaging, the program code read from the storage medium is a function expansion board inserted into the computer, After being written in the memory provided in the function expansion unit connected to the computer, based on the instructions of the program code, the CPU provided in the function expansion board or function expansion unit performs part or all of the actual processing, Needless to say, the process includes the case where the functions of the above-described embodiments are realized.

  When the present invention is applied to the above-described storage medium, program codes corresponding to the flowcharts described above are stored in the storage medium.

The block diagram which shows the structure of 1st Embodiment. Examples of images before and after optical distortion correction processing Enlarged view corresponding to FIG. Diagram showing the effect of optical distortion correction processing on noise The figure showing the characteristic which shows the relation between the distance from the optical axis and the optical distortion correction amount The figure showing the characteristic which shows the relationship between the optical distortion correction amount and the noise suppression level Distribution map of noise suppression level on screen Schematic diagram showing the pixel arrangement of a partial area of the image input to the subject area discrimination processing unit The figure showing the characteristic of flatness determination in a subject area discrimination processing unit The block diagram which shows the structure of 2nd Embodiment. The figure which shows the image before and after the peripheral light quantity drop correction processing The figure which shows the influence of the peripheral light quantity drop correction processing with respect to noise The figure showing the characteristic which shows the relation between the distance from the optical axis and the peripheral light amount drop correction amount The figure showing the characteristic which shows the relation between the peripheral light quantity drop correction amount and the noise suppression level The figure which shows the flow of the optical distortion correction process in 1st Embodiment. The figure which shows the flow of the noise reduction process in 1st Embodiment.

Explanation of symbols

001, 101 Imaging lens 002, 102 Imaging device 003, 103 A / D conversion processing unit 004, 104 Imaging device driving unit 005, 105 Lens characteristic value 006, 106 Microcomputer 007 Optical distortion correction processing unit 014, 114 Memory circuit 015 Interpolation circuit 107 Ambient light amount drop correction processing unit 105 Amplifying circuit 008, 108 Subject area estimation processing unit 009, 109 Noise reduction processing unit 010, 101 Camera signal processing means 011, 111 Video signal output terminal D Optical distortion correction amount L Peripheral light amount drop correction amount N Noise suppression level fl Flatness x, y Position of each pixel in the image R Distance from optical axis

Claims (12)

An image sensor that converts light from the subject into a video signal;
Imaging lens information acquisition means for acquiring information about the imaging lens;
Correction means for correcting image quality degradation that occurs in the video signal based on information about the imaging lens;
Noise reduction processing means for performing noise reduction processing on the output signal of the correction means;
Discriminating means for discriminating whether or not an area including the target pixel for performing the noise reduction processing is an area having a predetermined characteristic from an output signal of the correcting means;
Have
When it is determined in the determining means that the region including the target pixel is a region having a predetermined characteristic,
An image pickup apparatus that changes a noise suppression level in the noise reduction processing according to a position in a screen based on a correction amount in the correction unit.   The imaging apparatus according to claim 1, wherein the region having the predetermined characteristic of the determination unit is a flat portion.   The noise reduction processing unit performs control to increase the suppression level in the noise reduction processing as the distance between the position of the optical axis and the pixel of interest increases in the screen. The imaging device described.   4. The imaging according to claim 1, wherein the correction unit corrects optical distortion caused by a characteristic of the imaging lens and a positional relationship between the imaging lens and the imaging element based on information about the imaging lens. 5. apparatus.   The correction means corrects a peripheral light amount drop caused by a characteristic of the imaging lens and a positional relationship between the imaging lens and the imaging element based on information on the imaging lens. Imaging device. An imaging lens information acquisition step of acquiring information about the imaging lens;
A correction step of correcting image quality degradation that occurs in a video signal obtained from an image sensor based on information about the imaging lens;
A noise reduction processing step of performing noise reduction processing on the output signal of the correction step;
A determination step of determining whether or not the region including the target pixel for performing noise reduction processing is a region having a predetermined characteristic from the output signal of the correction step;
When it is determined in the determination step that the region including the target pixel is a region having a predetermined characteristic,
An image processing method comprising: changing a noise suppression level in the noise reduction process according to a position in a screen based on a correction amount in the correction step.   The image processing method according to claim 6, wherein the region having the predetermined characteristic of the determination unit is a flat portion.   8. The image processing according to claim 6, further comprising a control step of performing control so that the suppression level in the noise reduction processing is increased as the distance between the position of the optical axis and the pixel of interest increases in the screen. Method.   9. The correction unit according to claim 6, wherein the correction unit corrects optical distortion caused by characteristics of the imaging lens and a positional relationship between the imaging lens and the imaging element based on information on the imaging lens. Image processing method.   9. The image processing according to claim 6, wherein the correction unit corrects a peripheral light amount drop caused by a characteristic of the lens and a positional relationship between the lens and the image pickup device based on information on the lens. Method.   A program executable by an information processing apparatus, comprising program code for implementing the image processing method according to claim 6.   12. A storage medium readable by an information processing apparatus, wherein the program according to claim 11 is stored.

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