CN112393694B - Measurement method for improving precision of photoelectric autocollimator based on pixel frequency domain calibration - Google Patents
Measurement method for improving precision of photoelectric autocollimator based on pixel frequency domain calibration Download PDFInfo
- Publication number
- CN112393694B CN112393694B CN202011009398.7A CN202011009398A CN112393694B CN 112393694 B CN112393694 B CN 112393694B CN 202011009398 A CN202011009398 A CN 202011009398A CN 112393694 B CN112393694 B CN 112393694B
- Authority
- CN
- China
- Prior art keywords
- pixel
- image sensor
- frequency domain
- light field
- incident light
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000691 measurement method Methods 0.000 title claims description 5
- 238000005316 response function Methods 0.000 claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 27
- 238000004364 calculation method Methods 0.000 claims abstract description 14
- 230000003287 optical effect Effects 0.000 claims abstract description 6
- 230000008569 process Effects 0.000 claims abstract description 6
- 238000012545 processing Methods 0.000 claims description 9
- 238000005070 sampling Methods 0.000 claims description 7
- 238000012937 correction Methods 0.000 claims description 6
- 230000004044 response Effects 0.000 claims description 4
- 230000010363 phase shift Effects 0.000 claims description 3
- 230000008859 change Effects 0.000 claims description 2
- 238000006467 substitution reaction Methods 0.000 claims description 2
- 230000009466 transformation Effects 0.000 claims 1
- 238000005259 measurement Methods 0.000 description 14
- 238000005516 engineering process Methods 0.000 description 7
- 239000000835 fiber Substances 0.000 description 7
- 239000013307 optical fiber Substances 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 3
- 230000010287 polarization Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 229920000535 Tan II Polymers 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000006073 displacement reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012634 optical imaging Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
- G01B11/27—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes for testing the alignment of axes
- G01B11/272—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes for testing the alignment of axes using photoelectric detection means
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention provides a measuring method for improving the precision of a photoelectric autocollimator based on pixel frequency domain calibration. The method comprises the steps of correcting each pixel of an image sensor in the photoelectric autocollimator through dynamic Young interference, so that a frequency domain response function of each pixel is obtained, and obtaining incident optical field distribution in a frequency domain through fitting calculation. In the using process of the method, the result can be obtained only by program fitting calculation according to the calibrated parameters and the acquired image, and the model of the image sensor is not required to be changed to obtain a smaller pixel size, so that the resolution limit of the photoelectric autocollimator caused by using the image sensor is broken through, and the method is simpler in calculation and can also be applied to an embedded system.
Description
Technical Field
The invention belongs to the fields of optical imaging technology, image processing technology, signal processing technology and the like, and relates to a method for acquiring an actual incident light field image by using dynamic Young's interference, and applying the actual incident light field image to measurement and reading of a photoelectric autocollimator so as to improve measurement accuracy.
Background
The photoelectric autocollimator has been widely researched at present, and compared with the traditional autocollimator, the photoelectric autocollimator has the advantages of high measurement precision, wide measurement range and the like, and meanwhile, because the photoelectric technology is used for replacing human eyes for measurement and reading, the artificial error caused by the aiming and reading of the human eyes is avoided, and the current photoelectric autocollimator is widely applied to the fields of building, mechanical manufacturing, aerospace, metering and the like.
According to the implementation principle of the photoelectric autocollimator, the measurement accuracy is severely limited by the size of the pixel size of the image sensor, so that the image sensor with smaller pixel size is mainly considered for improving the measurement accuracy. However, the sensitivity of the image sensor such as CCD/CMOS is extremely reduced when the pixel size of the image sensor is gradually reduced, and the difficulty of the manufacturing process is increased, which is likely to cause technical barriers, and thus the measurement accuracy of the photoelectric autocollimator cannot be improved well. In view of the current situation, the method for reconstructing the CCD/CMOS by the dynamic Young's interference correction and the pixel frequency domain response function is expected to be applied to the measurement and reading of the photoelectric autocollimator.
The CCD/CMOS technology for dynamic Young's interference correction aims at calibrating pixel offset of an image sensor, and the offset of each pixel relative to the center of the pixel can be obtained by the method because the image sensor cannot ensure that all pixel centers are positioned at a preset center in actual processing and production and have slight deviation. Meanwhile, after the CCD/CMOS is subjected to dynamic Young interference in different wave vector directions, a large amount of image data is obtained, and fitting is performed on the basis, so that the corresponding frequency domain response function of each pixel is obtained.
The pixel response function represents the different response of each pixel to incident light of unit intensity and the output result. Since the image sensor cannot ensure that each pixel in the sensor has the same response function, calibration of the response function is required for each pixel. By definition, the output of each pixel of the image sensor is the product of the incident optical field distribution and the response function, and may also be the product of the incident optical field in the frequency domain and the frequency domain response function. Under the known conditions, the incident light field in the frequency domain can be obtained, and the Fourier transform is carried out on the incident light field in the frequency domain to reconstruct the actual incident light field image.
In summary, we combine the existing technologies and methods to design and provide a pixel frequency domain calibration correction CCD/CMOS based photoelectric autocollimator, which can obtain the frequency domain response function of the CCD/CMOS response and reconstruct the actual incident light field image, and the image quality can be greatly improved, and the sub-pixel points can be read and identified, thereby improving the precision of the photoelectric autocollimator.
Disclosure of Invention
The invention aims to provide a photoelectric autocollimator method with more accurate measurement precision by utilizing a pixel frequency domain response function reconstruction technology of dynamic Young interference and combining a photoelectric autocollimator.
The technical scheme adopted by the invention is as follows:
a measurement method for improving the precision of a photoelectric autocollimator based on pixel frequency domain calibration comprises the following steps: the method comprises the steps of obtaining an incident light field under a corresponding frequency domain by performing fitting calculation on an image collected by the photoelectric autocollimator, performing Fourier transform on the incident light field distribution under the frequency domain, performing up-sampling (namely increasing the number of sampling points in a single pixel) reconstruction processing, obtaining actual incident light field distribution, and calculating a reflector deflection angle according to the actual incident light field distribution. The method comprises the steps of correcting each pixel of an image sensor in the photoelectric autocollimator through dynamic Young interference, so that a frequency domain response function of each pixel is obtained, and obtaining an incident light field in a frequency domain through fitting calculation.
Further, obtaining a frequency domain response function of each pixel through pixels of an image sensor in the dynamic young interference correction photoelectric autocollimator, specifically comprising the following steps:
(1) splitting the HeNe laser beam with stable output to form two laser beams with the same phase and emitting light intensities of I1，I2(ii) a Simultaneously and respectively phase-modulating the two light beams to make the phase difference between the two light beams
The positions of the two light beams are adjusted simultaneously, so that the two light beams form dynamic interference fringes on a remote image sensor, and the corresponding wave vector direction is (k)x，ky) And the image sensor collects continuous pictures, at the moment:
incident light field of
The output gray value of each pixel of the image sensor is Imn＝∫∫S(xmn,ymn)Rmn(xmn,ymn)dxdy，
Wherein, (x, y) represents coordinates in a real space coordinate system. (m, n) represents the serial number of the pixel, S (x)mn,ymn) For incident light field, R (x)mn,ymn) As a response function, (x)mn,ymn) The coordinates of the center point of each pixel of the image sensor in a real space coordinate system are obtained.
Wherein the pixel frequency domain response function is as follows:
i is an imaginary number.
Will (x)mn,ymn) By substitution into the incident light field, thereby deducing
In the above formula
Representing the coefficients of each order of the Maxwell after the Maxwell expansion as a frequency domain response function (Deltax)mn，Δymn) The offset of each pixel from the self-center is generated in the actual image sensor processing process.
(2) For the above group (k)x，ky) After a group of continuous pictures are collected, the position of the light beam is adjusted so as to change the wave vector direction (k) in the incident light fieldx，ky) And a group of continuous pictures is collected again. Repeat the aboveAnd collecting a plurality of groups of continuous pictures in different wave vector directions. The I can be calculated by adopting a four-step phase shift method on a plurality of groups of continuous pictures collected under different wave vector directionsmnIn (1)
In parts, then using multiple sets (k)x，ky) To pair
Fitting the Melaurin expansion to calculate each order parameter q of pixel frequency domain response function Melaurin expansionmnj(j-0, 1, 2, 3, 4, 5, 6 …) and the corresponding (Δ x)mn，Δymn) So that the pixel frequency domain response function can be reconstructed therefrom and the incident optical field distribution in the actual spatial domain is obtained by fourier transform.
Further, the
The mululin expansion is:
the various order parameters of the mculing expansion are: q. q.smn0，qmn1，qmn2，qmn3，qmn4，qmn5。
Further, the specific steps of calculating the image acquired by the photoelectric autocollimator to acquire the incident light field distribution in the actual spatial domain are as follows:
the relationship of the output gray values collected by the image sensor of the photoelectric autocollimator can be known as follows:
wherein
Rounded, p represents the size of the pixel, and N represents the number of pixels in the CCD/CMOS lateral and longitudinal directions,
is an optical field in the frequency domain.
According to Imn(image sensor acquisition) and
(obtained by calibrating the image sensor) can be poured out
And then obtaining the light field distribution under the actual space domain through discrete Fourier transform:
in the above formula, S (x, y) is the light field distribution in the actual spatial domain, and (x, y) is the coordinates of any point in the spatial domain.
Further, the image sensor is a CCD or a CMOS.
The invention has the beneficial effects that:
the measurement precision of the photoelectric autocollimator is improved. Because the original incident light field distribution is calculated by correcting the offset and reconstructing the frequency domain response function of the image sensor in the photoelectric autocollimator, the sub-pixel precision of the original image sensor is indirectly obtained, and the measurement precision of the photoelectric autocollimator is greatly improved.
Convenient to use and with low costs. The method has the advantages that each photoelectric autocollimator can correct and reconstruct the original image sensor, parameters are stored in a computer, incident light field distribution under a frequency domain can be obtained only by fitting calculation according to the calibrated parameters and the acquired images in the using process, the original incident light field distribution is obtained by carrying out inverse Fourier transform, sub-pixel precision can be obtained, the model of the image sensor does not need to be changed to obtain a smaller pixel size, the resolution limit of the photoelectric autocollimator due to the use of the image sensor is broken through, and meanwhile, the photoelectric autocollimator can be applied to an embedded system due to simpler calculation complexity.
Drawings
FIG. 1 is a schematic diagram of a dynamic Young's interference calibration pixel shift and frequency domain response function reconstruction system of an image sensor;
FIG. 2 is a schematic diagram of the composition and operation of the photoelectric autocollimator;
FIG. 3 is a fiber base;
in the figure, a HeNe laser 1, a beam splitter 2, a light chopper 3, a phase modulator 4, a multichannel optical fiber base 5, an image sensor 6, a light source 7, a reticle 8, a beam splitting prism 9, a collimating lens 10, a reflecting mirror 11 and a polarization controller 12.
Detailed Description
A measurement method for improving the precision of a photoelectric autocollimator based on pixel frequency domain calibration comprises the following steps: the method comprises the steps of obtaining an incident light field under a corresponding frequency domain through fitting calculation of an image collected by the photoelectric autocollimator, carrying out Fourier transform up-sampling reconstruction processing on the incident light field to obtain actual incident light field distribution, and calculating a reflector deflection angle according to the actual incident light field distribution. The sub-pixel points which cannot be read in the image collector can be read according to the actual incident light field distribution, and the measurement result of the photoelectric autocollimator is more accurate through calculation. The method comprises the steps of calibrating each pixel of an image sensor in the photoelectric autocollimator through dynamic Young interference, obtaining a frequency domain response function of each pixel, and obtaining an incident light field under a frequency domain through fitting calculation.
The present invention will be further described with reference to the following detailed description and accompanying drawings.
The implementation mode comprises a pixel offset calibration and frequency domain response function reconstruction system and a photoelectric autocollimator. The pixel offset calibration and frequency domain response function calibration system mainly performs pixel offset correction and frequency domain response function reconstruction on an image sensor used for the photoelectric autocollimator, prepares reconstructed response data in a computer PC program, calculates the image to acquire incident light field distribution under a frequency domain after the image is acquired by the photoelectric autocollimator every time, acquires a finer image by performing Fourier transform up-sampling reconstruction processing on the image, and reads the image on the basis, so that the autocollimator can measure more accurately.
Specifically, as shown in fig. 1, a pixel offset calibration and frequency domain response function reconstruction system of an image sensor is built, which includes a HeNe laser 1 (good coherence and stable output), a beam splitter 2, a light chopper 3, 2 AOMs (or other phase modulation instruments) 4, a multi-channel fiber base 5, an image sensor 6 used in a photoelectric autocollimator, a computer for collecting image sensor data, a displacement platform, a plurality of optical fibers and other connection interfaces, and necessary signal transmission interfaces and power supplies, which are sequentially arranged. The multi-channel fiber base 5 has a structure as shown in fig. 3, and has a plurality of small holes for inserting and placing optical fibers in the transverse and longitudinal directions. When calibrating the pixel offset of the image sensor, the method comprises the following steps:
(1) open coherence good, output stable HeNe laser 1 for the laser of output passes through beam splitter 2, forms two laser beam of the same phase place, use AOM (can be other phase modulation device) 4 phase modulation to two light beam simultaneously respectively, then select two holes respectively and fix two optic fibre on optical fiber base 5, make two light beams interfere in the space, then use photochopper 3 respectively, shelter from one of them optic fibre light beam, measure the emergent light intensity of another optic fibre, the I who obtains two light beams from this1，I2. Then, the two shutters 3 are opened to form dynamic interference fringes on the image sensor 6 at a remote place, and the interference fringes are captured for a certain period of time to be recorded. When the incident light field is
The output gray value of each pixel of the image sensor is Imn＝∫∫S(xmn,ymn)Rmn(xmn,ymn)dxdy
(2) By re-selecting different holes in the base of the fibre, the relative lateral and longitudinal spacing between them, and hence the (k) in the incident light field, is changedx，ky) And (4) forming different interference fringe pairs in the wave vector direction, capturing the interference fringes within the same period of time again, and repeating the capturing process. Wherein the number of interference fringe pairs selected is greater than the parameter used in the fitting (the parameter is q)mnjAnd Δ xmn，Δymn) The sum of the numbers of (a) and (b).
Wherein the pixel frequency domain response function is as follows:
typically, maculing expands to a fifth order of:
thereby can be pushed out
All captured images and the relevant parameters of the image sensor 6 and the laser are stored in a computer program, which uses a four-step phase shift method, fitting calculations separately. Can calculate ImnIn (1)
In parts, then using multiple sets (k)x，ky) Fitting to calculate each parameter q of pixel frequency domain response functionmn0，qmn1，qmn2，qmn3，qmn4，qmn5And (Δ x)mn，Δymn) And storing the parameters in a computer for later use.
In addition, a polarization controller 12 can be arranged before the phase modulator 4 to control the polarization direction of the light beam, so that the imaging effect is better.
Reinstalling the calibrated image sensor to a photoelectric autocollimator, as shown in fig. 2, the photoelectric autocollimator comprises a light source 7, a reticle 8, a beam splitter prism 9, a collimating lens 10, a reflector 11 and an image sensor 6; when the photoelectric autocollimator is used, light emitted from the light source 7 is projected onto the image sensor 6 via the collimating lens 10, the reflecting mirror 11 and the beam splitter prism 9, and due to a slight offset angle of the reflecting mirror 11, the light will be displayed on the image sensor 6 with a certain offset center difference, and the relationship between output gray values collected by the CCD/CMOS can be known:
in the known ImnAnd
in the case of (2), can be pushed out
This is the light field distribution in the frequency domain, and the light field distribution in the actual spatial domain can be found using fourier transform, the formula is as follows:
s (x, y) is the finally obtained actual incident light field distribution and is obtained by performing inverse Fourier transform on the incident light field distribution under the frequency domain, and the image acquired by the original image sensor is the result obtained by sampling the incident light field at the right center point of each pixel point, namely, the value (x, y) in the formula is obtainedmn+Δxmn，ymn+Δymn) And obtaining that the distance between two adjacent pixels of the serial number (m, n) is approximately equal to the pixel size of the image sensor, so that the image acquired by the image sensor is actually (x, y) which respectively takes the central coordinates of each pixel, and the image is obtained by performing inverse Fourier transform on incident light field distribution under the frequency domain, so that the acquisition point is limited by the number of the actual pixels of the image sensor, and the acquisition position is limited only by the actual central coordinates of each pixelAnd (4) marking. The (x, y) coordinate position in the above formula gets rid of the original limitation, the value (sub-pixel point) can be taken at the place except the pixel center position of the original image sensor, and simultaneously, a large amount of values can be taken in the pixel of the original image sensor, so that the number of sampling points is increased in a single pixel, and a clearer picture can be recovered.
From the above, by using the corrected and reconstructed image, sub-pixel points smaller than pixels can be read, and therefore, the calculation is performed according to l ═ S tan 2 α (S is the focal length of the objective lens, α is the deviation angle of the mirror, and l is the vertical distance of the offset preset center), so that the smaller pixel precision is read, the smaller l can be obtained, and therefore, the smaller α can be calculated, the resolution is greatly improved, and the measurement precision of the photoelectric autocollimator is more accurate.
In the present invention, the image sensor may be a CCD or a CMOS.
Finally, it should be noted that the above-mentioned list is only a specific embodiment of the present invention. The present invention is not limited to the above embodiments, and many variations are possible. All modifications which can be derived or suggested by a person skilled in the art from the disclosure of the present invention are to be considered within the scope of the invention.
Claims (3)
1. A measurement method for improving the precision of a photoelectric autocollimator based on pixel frequency domain calibration is characterized by comprising the following steps: performing fitting calculation on an image acquired by the photoelectric autocollimator to obtain an incident light field under a corresponding frequency domain, performing Fourier transform up-sampling reconstruction processing on the incident light field to obtain actual incident light field distribution, and calculating a reflector deflection angle according to the actual incident light field distribution; correcting each pixel of an image sensor in the photoelectric autocollimator through dynamic Young interference so as to obtain a response function of each pixel frequency domain, and obtaining an incident light field under the frequency domain through fitting calculation;
the method comprises the following steps of obtaining a frequency domain response function of each pixel through the pixel of an image sensor in a dynamic Young interference correction photoelectric autocollimator, and specifically comprises the following steps:
(1) splitting the HeNe laser beam with stable output to form two laser beams with the same phase and emitting light intensities of I1，I2(ii) a Simultaneously and respectively phase-modulating the two light beams to make the phase difference between the two light beams
The positions of the two light beams are adjusted simultaneously, so that the two light beams form dynamic interference fringes on a remote image sensor, and the corresponding wave vector direction is (k)x，ky) And the image sensor collects continuous pictures, at the moment:
incident light field of
The output gray value of each pixel of the image sensor is Imn＝∫∫S(xmn,ymn)Rmn(xmn,ymn)dxdy
Wherein, (x, y) represents actual coordinates in an actual space coordinate system; (m, n) represents the serial number of the pixel in the image sensor, S (x)mn,ymn) For incident light field distribution, R (x)mn,ymn) (x) as a function of the response of the individual pixels of the image sensormn,ymn) Coordinates of the center point of each pixel of the image sensor under an actual space coordinate system;
wherein the pixel frequency domain response function is as follows:
i is an imaginary number;
will (x)mn,ymn) By substitution into the incident light field, thereby deducing
The upper typeIn
Representing the coefficients of each order of the Maxwell after the Maxwell expansion as a frequency domain response function (Deltax)mn，Δymn) The offset of each pixel relative to the dead center of the pixel is generated in the actual image sensor processing process;
the above-mentioned
The mululin expansion is:
the various order parameters of the mculing expansion are: q. q.smn0，qmn1，qmn2，qmn3，qmn4，qmn5；
(2) For a group (k)x，ky) After a group of continuous pictures are collected, the position of the light beam is adjusted so as to change the wave vector direction (k) in the incident light fieldx，ky) Re-collecting a group of continuous pictures; repeating the process, and collecting a plurality of groups of continuous pictures in different wave vector directions; the I can be calculated by adopting a four-step phase shift method on a plurality of groups of continuous pictures collected under different wave vector directionsmnIn (1)
In parts, then using multiple sets (k)x，ky) To pair
Fitting the Melaurin expansion to calculate each order parameter q of pixel frequency domain response function Melaurin expansionmnj(j-0, 1, 2, 3, 4, 5, 6 …) and the corresponding (Δ x)mn，Δymn) Therefore, the pixel frequency domain response function can be reconstructed, and the incident light field distribution under the actual space domain is obtained through Fourier transformation.
2. The method of claim 1, wherein the step of calculating the image collected by the photoelectric autocollimator to obtain the incident light field distribution in the actual spatial domain comprises:
the relationship of the output gray values collected by the image sensor of the photoelectric autocollimator can be known as follows:
wherein
Rounded, p represents the size of the pixel, and N represents the number of pixels in the CCD/CMOS horizontal and vertical directions,
is the optical field distribution in the frequency domain;
according to ImnAnd
can be pushed out
And then obtaining the light field distribution in the actual spatial domain through discrete Fourier transform:
in the above formula, S (x, y) is the light field distribution in the actual spatial domain, and (x, y) is the coordinates of an arbitrary point in the spatial domain.
3. The method of claim 1, wherein the image sensor is a CCD or CMOS.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011009398.7A CN112393694B (en) | 2020-09-23 | 2020-09-23 | Measurement method for improving precision of photoelectric autocollimator based on pixel frequency domain calibration |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011009398.7A CN112393694B (en) | 2020-09-23 | 2020-09-23 | Measurement method for improving precision of photoelectric autocollimator based on pixel frequency domain calibration |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112393694A CN112393694A (en) | 2021-02-23 |
| CN112393694B true CN112393694B (en) | 2021-12-17 |
Family
ID=74596220
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011009398.7A Active CN112393694B (en) | 2020-09-23 | 2020-09-23 | Measurement method for improving precision of photoelectric autocollimator based on pixel frequency domain calibration |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112393694B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113971722B (en) * | 2021-12-23 | 2022-05-17 | 清华大学 | Fourier domain optical field deconvolution method and device |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104320598A (en) * | 2014-11-06 | 2015-01-28 | 中国科学院光电研究院 | Aberration-free image reconstruction method based on CCD array pixel response function frequency domain calibration |
| WO2018034905A1 (en) * | 2016-08-15 | 2018-02-22 | Canon U.S.A. Inc. | Spectrally encoded endoscopic image process |
| CN111174733A (en) * | 2020-01-16 | 2020-05-19 | 西安中科微星光电科技有限公司 | Micro-angle detection device and method based on autocollimator |
| CN111664870A (en) * | 2020-06-04 | 2020-09-15 | 北京控制工程研究所 | Dynamic Young laser interference fringe calibration system and detector pixel geometric position deviation calibration method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7177029B2 (en) * | 2003-07-10 | 2007-02-13 | Zygo Corporation | Stroboscopic interferometry with frequency domain analysis |
-
2020
- 2020-09-23 CN CN202011009398.7A patent/CN112393694B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104320598A (en) * | 2014-11-06 | 2015-01-28 | 中国科学院光电研究院 | Aberration-free image reconstruction method based on CCD array pixel response function frequency domain calibration |
| WO2018034905A1 (en) * | 2016-08-15 | 2018-02-22 | Canon U.S.A. Inc. | Spectrally encoded endoscopic image process |
| CN111174733A (en) * | 2020-01-16 | 2020-05-19 | 西安中科微星光电科技有限公司 | Micro-angle detection device and method based on autocollimator |
| CN111664870A (en) * | 2020-06-04 | 2020-09-15 | 北京控制工程研究所 | Dynamic Young laser interference fringe calibration system and detector pixel geometric position deviation calibration method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112393694A (en) | 2021-02-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11950981B2 (en) | Scanning system and calibration thereof | |
| CN104320598B (en) | A kind of aberration free image reconstructing method demarcated based on ccd array pixel response function frequency domain | |
| CN111366557B (en) | Phase imaging method based on thin scattering medium | |
| KR20020060151A (en) | Method and system for measuring the relief of an object | |
| CN115775303B (en) | Three-dimensional reconstruction method for high-reflection object based on deep learning and illumination model | |
| JP2014512242A (en) | Method for calibrating and correcting scanning distortion in an optical coherence tomography system | |
| WO2012018568A2 (en) | Method and apparatus for imaging | |
| CN106768890B (en) | Gray scale cosine distribution optical target simulator for modulation transfer function detection | |
| CN112393694B (en) | Measurement method for improving precision of photoelectric autocollimator based on pixel frequency domain calibration | |
| Tang et al. | Calibration of an arbitrarily arranged projection moiré system for 3D shape measurement | |
| CN108760056B (en) | A kind of laser complex amplitude measurement method and system based on coherent diffraction imaging | |
| CN115598147B (en) | Device and method for detecting defects of inner and outer surfaces of microsphere based on white light microscopic interference | |
| Bergues et al. | External visual interface for a Nikon 6D autocollimator | |
| JPH05306916A (en) | Method and device for analyzing distribution of fringe phase | |
| Liu et al. | Three-dimensional reconstruction based on three-dimensional phase mapping using single-pixel imaging | |
| JP4390957B2 (en) | Method for determining fringe phase in fringe analysis | |
| CN116222802B (en) | Measuring method and measuring device for central wavelength of light source | |
| Kagawa et al. | A compact shape-measurement module based on a thin compound-eye camera with multiwavelength diffractive pattern projection for intraoral diagnosis | |
| Li et al. | Design and validation of a linear wavenumber spectrometer for SD-OCT using freeform optics | |
| JP2024111983A (en) | Three-dimensional shape measurement device and three-dimensional shape measurement method | |
| Muñoz | NEW OPTICAL SETUPS FOCUSED ON THE MEASUREMENT OF THE SHAPE AND DISPLACEMENT FIELDS | |
| CN115791100A (en) | Global phase calibration device and calibration method of phase type spatial light modulator | |
| Kim et al. | Fingerprint biometry applications of digital holography and low-coherence interference microscopy | |
| Francis et al. | Measurement of surface strain using multi-component pulsed laser shearography with coherent fibre-optic bundles | |
| JP2001349705A (en) | Error correction method in frequency analysis by using wavelength scanning laser interferometer |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |