CN112903121B - Wavefront detection method based on cross iterative automatic focusing - Google Patents

Wavefront detection method based on cross iterative automatic focusing Download PDF

Info

Publication number
CN112903121B
CN112903121B CN202110274702.9A CN202110274702A CN112903121B CN 112903121 B CN112903121 B CN 112903121B CN 202110274702 A CN202110274702 A CN 202110274702A CN 112903121 B CN112903121 B CN 112903121B
Authority
CN
China
Prior art keywords
wavefront
diffraction
defocus
amplitude
phase
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
Application number
CN202110274702.9A
Other languages
Chinese (zh)
Other versions
CN112903121A (en
Inventor
白剑
赵磊
汪凯巍
侯晶
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhejiang University ZJU
Original Assignee
Zhejiang University ZJU
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Zhejiang University ZJU filed Critical Zhejiang University ZJU
Priority to CN202110274702.9A priority Critical patent/CN112903121B/en
Publication of CN112903121A publication Critical patent/CN112903121A/en
Application granted granted Critical
Publication of CN112903121B publication Critical patent/CN112903121B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J9/00—Measuring optical phase difference; Determining degree of coherence; Measuring optical wavelength
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J9/00—Measuring optical phase difference; Determining degree of coherence; Measuring optical wavelength
    • G01J2009/002—Wavefront phase distribution

Landscapes

  • Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • General Physics & Mathematics (AREA)
  • Testing Of Optical Devices Or Fibers (AREA)

Abstract

The invention discloses a wavefront detection method based on cross iterative automatic focusing. The method optimizes the defocus distance by using an analytic gradient formula to automatically determine the defocus position, overcomes the problems of inaccurate defocus position determination caused by inaccurate wavefront and inaccurate wavefront reconstruction caused by uncertain defocus position by using a cross iteration method, and optimizes the defocus distance, wavefront amplitude and phase of the same target function to accurately reconstruct the defocus position and wavefront error. The method realizes the accurate determination of the large defocus errors of the multiple images, and realizes the accurate reconstruction of the wavefront under the condition of uncertain defocus positions without additionally constructing a target function.

Description

Wavefront detection method based on cross iterative automatic focusing
Technical Field
The invention relates to the technical field of optical measurement and imaging, in particular to a wavefront detection method based on cross iterative automatic focusing.
Background
The computed imaging greatly changes the mode seen in the traditional imaging, overcomes the defect of incomplete imaging of the traditional imaging system through the post-processing of a computer, and reduces the size and the weight of the imaging system. Coherent diffraction imaging is one implementation of computational imaging. Coherent diffraction imaging is a quantitative phase imaging mode based on an iterative method; collecting a diffraction image on a focal plane or a defocusing plane by using an image sensor; repeatedly and iteratively calculating by using Fourier transform and inverse Fourier transform to obtain the amplitude and the phase of the wavefront or the image to be detected; the processing of the amplitude or the support domain in the iteration process is similar to the mapping to the acquisition surface or the surface to be detected, and when the condition of the intensity acquisition surface and the condition of the surface to be detected are both satisfied, the wave front reconstruction is completed. Coherent diffraction imaging is further generally referred to as phase recovery. The phase recovery is a method for realizing wavefront phase reconstruction by using diffraction intensity based on Fourier transform and inverse Fourier transform, the device is very simple, and under the simplest condition, the phase recovery wavefront detection device based on the phase recovery can realize the wavefront reconstruction only by a light source, an element to be detected and an image sensor. The phase recovery can be divided into a transverse phase difference method (sub-aperture splicing) and an axial phase difference method according to different positions of the used diffraction spot, and the axial phase difference method is simple to operate and can meet the requirements of a common imaging system, so that the method is widely applied to the aspects of optical imaging, detection, adaptive optics and the like. The axial phase difference method is to collect a plurality of images on a focal plane and a defocusing plane, then sequentially use light intensity images collected at different positions in a phase recovery algorithm, and iterate repeatedly until the algorithm converges to realize wavefront reconstruction.
However, the axial phase difference method is very sensitive to the determination of the defocus position, especially to the relative position between different defocus planes, and generally a precise guide rail with high precision is selected to move the image sensor to collect diffraction spots, which causes the whole device to be very expensive, and in some application situations, such as in-situ detection, it is difficult to place the precise guide rail, which causes the defocus position to be very difficult to determine.
Disclosure of Invention
The invention aims to provide a wavefront detection method based on cross iterative auto-focusing aiming at the defects of the prior art, so as to solve the wavefront reconstruction error caused by the inaccuracy of the defocusing position in the axial phase difference method, reduce the cost of the whole set of device and replace an expensive precision displacement device with an algorithm.
The purpose of the invention is realized by the following technical scheme:
a wavefront detection method based on cross iterative auto-focusing is provided, wherein a beam expander, a flat plate to be detected, a convergent lens and an image sensor are sequentially arranged on an emergent light path of a laser, and the method comprises the following steps:
s1: moving the image sensor, and collecting n defocused light spots containing the wavefront error of the flat plate to be detected at different defocused distances;
s2: respectively setting the focal length s, the caliber D and the nominal defocusing position z of each defocusing light spot of the converging lenskStep for optimizing defocusing positionzStep of phase optimizationphaseAmplitude optimization stepampThe total iteration number N of wave-front detection, the total defocusing optimization iteration number N _ z, an iteration judgment threshold value M and the initial iteration number of wave-front detection1 as a generation count i and g as an initial estimation value of the wavefront to be measured1(x, y), wherein (x, y) is the coordinate of the flat plate to be detected;
s3: using the diffraction propagation calculation value U of the defocused light spot and the estimated value of the wavefront to be measuredkConstructing an optimized objective function
Figure BDA0002976132190000021
Where u, v are the coordinates at the off-focus spot position, IkIs at an out-of-focus position zkOut-of-focus spot, U, of the spotkIs the wavefront to be measured at the out-of-focus position zkThe integral of diffraction at (d); wk(u, v) is weight distribution, which is used to remove pixel points and dead pixels with low signal-to-noise ratio on the image sensor;
s4, when i is equal to 1, optimizing the out-of-focus position for the diffraction spots at all positions by using an out-of-focus position optimization algorithm, and when i is equal to 1, optimizing the out-of-focus position for the kth diffraction spot by using an out-of-focus position optimization algorithm; the defocus position optimization algorithm is realized by the following substeps:
s4.1: setting the initial iteration count j of the defocusing position to be 1, and inputting the defocusing position zk；
S4.2: calculating the optimized gradient of the defocus position
Figure BDA0002976132190000022
Figure BDA0002976132190000023
Figure BDA0002976132190000024
Wherein the content of the first and second substances,
Figure BDA0002976132190000025
and
Figure BDA0002976132190000026
respectively representing a diffraction calculation operator and an inverse diffraction calculation operator,
Figure BDA0002976132190000027
representing the complex amplitude of the diffraction calculation from the plane to be measured to the image acquisition plane,
Figure BDA0002976132190000028
representing the complex amplitude calculated from the image acquisition surface inverse diffraction to the surface to be measured, representing taking complex conjugate, k 2 pi/lambda is wave number, Im () represents taking imaginary part, delta zkRepresenting the gradient of defocus positions;
s4.3: updating the defocus position using the following equation
zk＝zk+stepzΔzk
S4.4: if j is less than N _ z, j is made to be j +1, and S4.2 is returned, otherwise, the iteration is ended, and the optimal out-of-focus position z is obtainedk；
S5: calculating wavefront optimized phase and amplitude gradients using the following equations
Figure BDA0002976132190000031
Figure BDA0002976132190000032
Figure BDA0002976132190000033
Figure BDA0002976132190000034
Where Re () stands for imaginary part, deltaa for amplitude gradient,
Figure BDA0002976132190000035
representing the phase gradient.
S6: updating the amplitude and the phase of the wavefront to be detected, and obtaining the complex amplitude distribution of the flat plate to be detected by using a gradient optimization method;
s7: if mod ((i +1)/M) ═ k, return to S4;
s8: if i is less than N _ iter, let k be mod ((i +1)/N), i be i +1, and return to S5, otherwise end iteration, obtain the wavefront to be measured that satisfies all out-of-focus light spot constraints;
s9: and removing noise influence on the wavefront to be detected obtained in the step S8 by using polynomial fitting, so as to obtain real wavefront error distribution.
Further, to facilitate flexible sampling, the diffraction calculation operators in S4.2 and S5 preferentially use two-step fresnel diffraction.
Further, the gradient optimization method in S6 adopts a gradient descent method, and the calculation formula is as follows:
Figure BDA0002976132190000036
a and herein
Figure BDA0002976132190000037
Representing amplitude and phase, respectively.
The invention has the following beneficial effects:
the method optimizes the defocusing position by using an analytic gradient method, and realizes the accurate determination of high-speed large defocusing errors. The nonlinear optimization method is utilized to realize the accurate reconstruction of the amplitude and the phase of the surface to be detected, the application range is expanded, and the axial phase difference method can be used for not only wavefront detection but also image reconstruction. The cross iterative optimization solves the problem of inaccurate reconstruction of the defocus error and the wavefront error caused by mutual influence.
Drawings
FIG. 1 is a schematic diagram of an apparatus for wavefront measurement based on cross-iterative auto-focusing according to the present invention.
FIG. 2 is a flow chart of a wavefront sensing method based on cross-iterative auto-focusing of the present invention.
FIG. 3 is a flow chart of the auto-focus optimization method of the present invention.
FIG. 4 is a diagram of the results of the wavefront sensing method based on cross-iterative auto-focusing of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and preferred embodiments, and the objects and effects of the present invention will become more apparent, it being understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.
As shown in fig. 1 to 3, in the wavefront detection method based on cross iterative auto-focusing of the present invention, a beam expander 2, a flat plate 3 to be measured, a converging lens 4, and an image sensor 5 are sequentially arranged on an emergent light path of a laser 1, and the method includes the following steps:
s1: moving the image sensor 5, and acquiring n defocused light spots containing the wavefront error of the flat plate to be detected at different defocused distances;
s2: respectively setting the focal length s, the caliber D and the nominal defocusing position z of each defocusing light spot of the convergent lenskStep for optimizing defocusing positionzStep of phase optimizationphaseAmplitude optimization stepampThe total iteration number N of wavefront detection, the total defocusing optimization iteration number N _ z, an iteration judgment threshold value M, the initial iteration count i of wavefront detection being 1, and the initial estimated value g of wavefront to be detected1(x, y), wherein (x, y) is the coordinate of the flat plate to be detected;
s3: calculating value U of diffraction propagation by using estimated values of defocused light spots and wavefront to be measuredkConstructing an optimized objective function
Figure BDA0002976132190000041
Where u, v are the coordinates at the off-focus spot position, IkIs at an out-of-focus position zkOut-of-focus spot, U, of the spotkIs the wavefront to be measured at the out-of-focus position zkThe integral of diffraction at (d); wk(u, v) is a weight distribution for removing the imagePixel points and dead pixels on the sensor with low signal-to-noise ratio;
s4, when i is equal to 1, optimizing the out-of-focus position for the diffraction spots at all positions by using an out-of-focus position optimization algorithm, and when i is equal to 1, optimizing the out-of-focus position for the kth diffraction spot by using an out-of-focus position optimization algorithm; the defocus position optimization algorithm is realized by the following substeps:
s4.1: setting the initial iteration count j of the defocusing position to be 1, and inputting the defocusing position zk；
S4.2: calculating the optimized gradient of the defocus position
Figure BDA0002976132190000042
Figure BDA0002976132190000043
Figure BDA0002976132190000044
Wherein the content of the first and second substances,
Figure BDA0002976132190000045
and
Figure BDA0002976132190000046
respectively representing a diffraction calculation operator and an inverse diffraction calculation operator,
Figure BDA0002976132190000047
representing the complex amplitude of the diffraction calculation from the plane to be measured to the image acquisition plane,
Figure BDA0002976132190000051
representing the complex amplitude calculated from the image acquisition surface inverse diffraction to the surface to be measured, representing taking complex conjugate, k 2 pi/lambda is wave number, Im () represents taking imaginary part, delta zkRepresenting the gradient of defocus positions.
S4.3: updating the defocus position using the following equation
zk＝zk+stepzΔzk
S4.4: if j is less than N _ z, j is made to be j +1, and S4.2 is returned, otherwise, the iteration is ended, and the optimal out-of-focus position z is obtainedk；
S5: calculating wavefront optimized phase and amplitude gradients using the following equations
Figure BDA0002976132190000052
Figure BDA0002976132190000053
Figure BDA0002976132190000054
Figure BDA0002976132190000055
Where Re () stands for imaginary part, deltaa for amplitude gradient,
Figure BDA0002976132190000056
representing the phase gradient.
S6: updating the amplitude and the phase of the wavefront to be detected, and obtaining the complex amplitude distribution of the flat plate to be detected by using a gradient optimization method;
s7: if mod ((i +1)/M) ═ k, return to S4;
s8: if i is less than N _ iter, let k be mod ((i +1)/N), i be i +1, and return to S5, otherwise end iteration, obtain the wavefront to be measured that satisfies all out-of-focus light spot constraints;
s9: and removing noise influence on the wavefront to be detected obtained in the step S8 by using polynomial fitting, so as to obtain real wavefront error distribution.
To facilitate flexible sampling, the diffraction calculation operators in S4.2 and S5 preferably use two-step fresnel diffraction.
The gradient optimization method in S6 adopts a gradient descent method, and the calculation formula is as follows:
Figure BDA0002976132190000057
a and herein
Figure BDA0002976132190000058
Representing amplitude and phase, respectively.
A specific example of the method of the present invention is given below to illustrate the technical effect of the method
Here, s is 1079.41mm, z is selected as the focal length1,z2,z3＝[-10,-15,20]mm, the caliber D is 22.9mm, and the defocusing position optimization step lengthz-0.00004, step of phase optimizationphaseAmplitude optimization step-0.4 ═ 0.4ampThe total iteration number N of wavefront detection is 5000, the total defocus optimization iteration number N _ z is 300, and the iteration judgment threshold M is 50.
In the embodiment, three defocusing diffraction images are collected to carry out wave front phase and amplitude reconstruction, the defocusing errors of the three defocusing light spots are respectively +3, + 3-3 mm, the selected diffraction calculation model is a two-step Fresnel diffraction model, and fig. 4 is a recovery result graph of the method provided by the invention. It can be seen from the figure that under the condition of defocusing error, the amplitude and the phase of the wavefront can be accurately recovered, and the recovery result is consistent with the morphology profile of the true value.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and although the invention has been described in detail with reference to the foregoing examples, it will be apparent to those skilled in the art that various changes in the form and details of the embodiments may be made and equivalents may be substituted for elements thereof. All modifications, equivalents and the like which come within the spirit and principle of the invention are intended to be included within the scope of the invention.

Claims (3)

1. A wave-front detection method based on cross iterative auto focusing is provided, a beam expander, a flat plate to be measured, a convergent lens and an image sensor are arranged on an emergent light path of a laser in sequence, and the method is characterized by comprising the following steps:
s1: moving the image sensor, and collecting n defocused light spots containing the wavefront error of the flat plate to be detected at different defocused distances;
s2: respectively setting the focal length s, the caliber D and the nominal defocusing position z of each defocusing light spot of the converging lenskStep for optimizing defocusing positionzStep of phase optimizationphaseAmplitude optimization stepampThe total iteration number N of wavefront detection, the total defocusing optimization iteration number N _ z, an iteration judgment threshold value M, the initial iteration count i of wavefront detection being 1, and the initial estimated value g of wavefront to be detected1(x, y), wherein (x, y) is the coordinate of the flat plate to be detected;
s3: using the diffraction propagation calculation value U of the defocused light spot and the estimated value of the wavefront to be measuredkConstructing an optimized objective function
Figure FDA0003419259390000011
Where u, v are the coordinates at the off-focus spot position, IkIs at an out-of-focus position zkOut-of-focus spot, U, of the spotkIs the wavefront to be measured at the out-of-focus position zkThe integral of diffraction at (d); wk(u, v) is weight distribution, which is used to remove pixel points and dead pixels with low signal-to-noise ratio on the image sensor;
s4, when i is equal to 1, optimizing the out-of-focus position for the diffraction spots at all positions by using an out-of-focus position optimization algorithm, and when i is equal to 1, optimizing the out-of-focus position for the kth diffraction spot by using an out-of-focus position optimization algorithm; the defocus position optimization algorithm is realized by the following substeps:
s4.1: setting the initial iteration count j of the defocusing position to be 1, and inputting the defocusing position zk；
S4.2: calculating the optimized gradient of the defocus position
Figure FDA0003419259390000012
Figure FDA0003419259390000013
Figure FDA0003419259390000014
Wherein the content of the first and second substances,
Figure FDA0003419259390000015
and
Figure FDA0003419259390000016
respectively representing a diffraction calculation operator and an inverse diffraction calculation operator,
Figure FDA0003419259390000017
representing the complex amplitude of the diffraction calculation from the plane to be measured to the image acquisition plane,
Figure FDA0003419259390000018
representing the complex amplitude calculated from the image acquisition surface inverse diffraction to the surface to be measured, representing taking complex conjugate, k 2 pi/lambda is wave number, Im () represents taking imaginary part, delta zkRepresenting the gradient of defocus positions;
s4.3: updating the defocus position using the following equation
zk＝zk+stepzΔzk
S4.4: if j is<N _ z, making j equal to j +1, and returning to S4.2, otherwise ending iteration to obtain the optimal out-of-focus position zk；
S5: calculating wavefront optimized phase and amplitude gradients using the following equations
Figure FDA0003419259390000021
Figure FDA0003419259390000022
Figure FDA0003419259390000023
Figure FDA0003419259390000024
Where Re () stands for imaginary part, deltaa for amplitude gradient,
Figure FDA0003419259390000025
represents a phase gradient;
s6: updating the amplitude and the phase of the wavefront to be detected, and obtaining the complex amplitude distribution of the flat plate to be detected by using a gradient optimization method;
s7: if mod ((i +1)/M) ═ k, return to S4;
s8: if i is less than N, making k equal to mod ((i +1)/N), i equal to i +1, and returning to S5, otherwise, ending iteration, and obtaining the wavefront to be measured which meets all the defocused light spot constraints;
s9: and removing noise influence on the wavefront to be detected obtained in the step S8 by using polynomial fitting, so as to obtain real wavefront error distribution.
2. The wavefront sensing method based on cross-iterative auto-focusing of claim 1, wherein for flexible sampling, the diffraction calculation operators in S4.2 and S5 use two-step fresnel diffraction preferentially.
3. The wavefront sensing method of claim 1, wherein the gradient optimization method in S6 is a gradient descent method, and the calculation formula is as follows:
Figure FDA0003419259390000026
a and herein
Figure FDA0003419259390000027
Representing amplitude and phase, respectively.
CN202110274702.9A 2021-03-15 2021-03-15 Wavefront detection method based on cross iterative automatic focusing Active CN112903121B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110274702.9A CN112903121B (en) 2021-03-15 2021-03-15 Wavefront detection method based on cross iterative automatic focusing

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110274702.9A CN112903121B (en) 2021-03-15 2021-03-15 Wavefront detection method based on cross iterative automatic focusing

Publications (2)

Publication Number Publication Date
CN112903121A CN112903121A (en) 2021-06-04
CN112903121B true CN112903121B (en) 2022-04-19

Family

ID=76106607

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110274702.9A Active CN112903121B (en) 2021-03-15 2021-03-15 Wavefront detection method based on cross iterative automatic focusing

Country Status (1)

Country Link
CN (1) CN112903121B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115031930B (en) * 2022-06-13 2023-03-28 浙江大学 Phase recovery wavefront detection device and method with adjustable measurement frequency

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102721477A (en) * 2012-06-04 2012-10-10 中国科学院光电技术研究所 Off-focus value measuring method for phase diversity wavefront sensor
CN110375964A (en) * 2019-07-18 2019-10-25 浙江大学 It is a kind of based on extension how the wavefront error detection device and detection method of bohr-Zernike polynominal optimization phase recovery

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102721477A (en) * 2012-06-04 2012-10-10 中国科学院光电技术研究所 Off-focus value measuring method for phase diversity wavefront sensor
CN110375964A (en) * 2019-07-18 2019-10-25 浙江大学 It is a kind of based on extension how the wavefront error detection device and detection method of bohr-Zernike polynominal optimization phase recovery

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
"离焦量误差对相位差法波前重构的影响";杨磊 等;《天文研究与技术》;20090331;第6卷(第1期);43-50页 *
"Optimized Phase Retrieval Method Base on Multi-focus Property of Zone Plate";Binjie Lu et al.;《SPIE》;20201010;115481W1-10 *

Also Published As

Publication number Publication date
CN112903121A (en) 2021-06-04

Similar Documents

Publication Publication Date Title
CN110160751B (en) Wide-band wavefront error detection device and detection method based on phase recovery
EP2702556A1 (en) A method and apparatus for providing image data for constructing an image of a region of a target object
CN107516324B (en) Target boundary extraction method based on geometric characteristic mutation of light bars
CN112629677B (en) Rapid large-dynamic-range wavefront detection device and detection method based on mode recovery
CN112019751B (en) Calibration information based automatic focusing method
CN112903121B (en) Wavefront detection method based on cross iterative automatic focusing
JP7277101B2 (en) Aberration estimation method, aberration estimation device, program and storage medium
CN110108230B (en) Binary grating projection defocus degree evaluation method based on image difference and LM iteration
CN112629678A (en) Rapid phase recovery method for general shape diffraction-free iterative computation
CN108007382A (en) Surface shape measurement apparatus and method based on Structured Illumination
KR101166961B1 (en) Wavefront aberration retrieval method by 3D beam measurement
JP2021051038A (en) Aberration estimation method, aberration estimation device, program, and recording medium
CN113188671A (en) Wavefront detection method based on cross iteration automatic position correction
CN106502074B (en) A kind of auto focusing method for image planes digital holographic micro-measuring
KR102129069B1 (en) Method and apparatus of automatic optical inspection using scanning holography
CN113359403A (en) Automatic focusing method for lens-free digital holographic imaging
CN113189101B (en) Lens-free imaging method with negative feedback adjustment
JP2021060353A (en) Method for estimating internal error of optical system and measurement device
Lozano-Cancelas et al. Quantification of canting errors: Technique combining camera vision with theoretical imaging
CN114371549B (en) Quantitative phase imaging method and system based on multi-focus multiplexing lens
CN115031929B (en) Fast large-aperture laser wavefront on-site detection method based on Legendre diffraction integration
CN115014545A (en) Phase recovery wavefront detection method without support domain constraint
CN115131233A (en) Intensity background light suppression method for computational imaging
CN115128762B (en) Automatic focusing measurement method based on light intensity gradient number
CN113655610B (en) Automatic focusing method and control device for photothermal reflection microscopic thermal imaging

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