CN108663123A - A kind of Hartmann's wavefront reconstruction method to match with micro scanning device - Google Patents
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Abstract
The invention discloses a kind of Hartmann's wavefront reconstruction methods to match with micro scanning device, it is related to technical field of image processing, from the basic research of Shack Hartmann Wavefront Sensing and reconfiguration technique and micro scanning technology, it is proposed a kind of novel detection method that micro scanning device being added before microlens array, the shortcomings that traditional Shack Hartmann wave front sensor is to wavefront undersampling to be measured is compensated for by way of micro scanning, the sample rate to being tested wavefront can be improved using micro scanning technology, obtain high-resolution hot spot distributed image, and then preferably restore tested wavefront.
Description
Technical field
The present invention relates to technical field of image processing, more particularly to a kind of Hartmann's wave to match with micro scanning device
Preceding reconstructing method.
Background technology
Shack-Hartmann sensor is a kind of real-time wavefront measurement instrument based on the wavefront slope for measuring incident light
Device has many advantages, such as that simple in structure, real-time is good, affected by environment smaller.It has been widely used in adaptive optics, laser light
The fields such as beam quality diagnosis, laser space communication, human eye aberration analysis, optical element quality testing and optical system alignment.
For bigbore Wave-front measurement and wavefront surface type it is more complex in the case of, merely by improve facula mass center positioning accuracy,
The improvement such as wavefront reconstruction algorithm and microlens array parameter are difficult to make up caused by lenslet dimension limits to wavefront to be measured
The shortcomings that undersampling.Sample rate of the Hartmann sensor to tested wavefront is improved using micro scanning technology, is a kind of novel
Wave-front detection method, it is particularly significant for the wavefront reconstruction method of the novel detection method.
Invention content
An embodiment of the present invention provides a kind of Hartmann's wavefront reconstruction methods to match with micro scanning device, can solve
Problems of the prior art.
The present invention provides a kind of Hartmann's wavefront reconstruction methods to match with micro scanning device, and this method includes following
Step：
The tetra- groups of facula mass centers of A, B, C, D obtained using iteration weighted mass center algorithm by the hot spot distribution map after rebuilding are sat
Mark, find out facula mass center the directions x and the directions y offset Δ x and Δ y；
Each sub-aperture is found out after rebuilding in new sub-aperture layout respectively by four groups of spot centroid shift amounts in x, the side y
Upward average wavefront slope Gx(xF,yF) and Gy(xF,yF), after obtaining and rebuilding after the spot centroid shift amount acquired is brought into
Each corresponding slope matrix of sub-aperture；
Before the slope matrix is expressed as the completed wave with distortion using Zernike polynomial extreme value expression-formsByIt can obtain the wavefront slope G of Zernike polynomial formsx(xF,yF) and Gy(xF,yF)；
By the wavefront slope G of Zernike polynomial formsx(xF,yF) and Gy(xF,yF) it is expressed as matrix form G=ZA,
New sub-aperture layout after matrix Z is rebuild by micro scanning Hartmann sensor determines to get to can acquire after slope vector G
Zernike coefficient vector A, and then Hartmann's wavefront is reconstructed.
Hartmann's wavefront reconstruction method that a kind of and micro scanning device in the embodiment of the present invention matches, from Shack-Kazakhstan
The basic research of special graceful Wavefront detecting and reconfiguration technique and micro scanning technology is set out, and proposes that one kind is added before microlens array
The novel detection method of micro scanning device is compensated for traditional Shack-Hartmann wavefront sensor by way of micro scanning and treated
The shortcomings that surveying wavefront undersampling can improve the sample rate to being tested wavefront using micro scanning technology, obtain high-resolution light
Spot distributed image, and then preferably restore tested wavefront.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
Obtain other attached drawings according to these attached drawings.
Fig. 1 is that the lack sampling hot spot distribution map behind central area is determined in the present invention；
Fig. 2 is the lack sampling hot spot distribution map after recognizing origin in the present invention；
Fig. 3 is the lack sampling hot spot distribution map after dividing in the present invention；
Fig. 4 is the hot spot distribution map after being rebuild in the present invention.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Hartmann's wavefront reconstruction method that a kind of and micro scanning device provided in the embodiment of the present invention matches, this method
Include the following steps：
Step 100, tetra- groups of hot spots of A, B, C, D that iteration weighted mass center algorithm obtains are used to the hot spot distribution map after reconstruction
Center-of-mass coordinate, you can find out facula mass center the directions x and the directions y offset Δ x and Δ y：
A group centroid offset Δs xAWith Δ yAIt can be expressed as：
Wherein, (xAcore,yAcore) be A groups facula mass center coordinate.
B group centroid offset Δs xBWith Δ yBIt can be expressed as：
Wherein, (xBcore,yBcore) be B groups facula mass center coordinate.
C group centroid offset Δs xCWith Δ yCIt can be expressed as：
Wherein, (xCcore,yCcore) be C groups facula mass center coordinate.
D group centroid offset Δs xDWith Δ yDIt can be expressed as：
Wherein, (xDcore,yDcore) be D groups facula mass center coordinate.
L indicates that the width of single lenticule, the i.e. length of sub-aperture, p indicate the pixel of ccd detector in formula (1)-(8)
Size,It represents less than and is equal toMaximum integer.
Hot spot distribution map after the reconstruction used in above-mentioned steps is rebuild especially by following methods：
Otsu threshold segmentation is carried out to the lack sampling hot spot distribution map obtained by micro scanning, to reduce ambient noise to center
The influence of identification, treated hot spot distribution map as shown in Figure 1, the micro scanning Hartmann sensor used in the present invention along light
The direction of propagation is followed successively by light path shrink beam system, wedge, microlens array and the signal transmission of CCD, CCD acquisition to host computer；
To treated, full frame image calculates spot array in the frame micro scanning image using iteration weighted mass center algorithm
Approximate centre coordinate (x0,y0), such as the cross hairs position in Fig. 1, define this coordinate x0And y03 times of plus-minus is micro- respectively
Mirror size L, i.e. (x0-3L≤x≤x0+3L,y0-3L≤y≤y0+ 3L) region be hot spot distribution map central area, such as Fig. 1
In box inner region；
Using the method based on local least squares method, subregion is divided in the central area of hot spot distribution map, wherein
Central pixel is found as origin, which is：
Treated hot spot distribution map is indicated using the matrix of M × N, the central area in Fig. 1 is m × n, if hot spot x is
Missing point deducts remaining m-1 hot spot point after x, meter to search out P consecutive points near x in hot spot point row vector
Calculate these hot spot points to x vector distance.When hot spot point vector distance is more than the vector length of central area, this hot spot point
It is exactly the hot spot rather than central point lacked on hot spot figure, when hot spot point vector distance is less than the vector length of central area, this
A hot spot point is exactly center spot, while can also obtain m-1 adjacent spots point.P obtained are with x apart from nearest hot spot point
As the closest P points of x, by it and most adjacent xs1,xs2,...,xskForm the column vector of a such as formula (9)：
Wherein, A, B indicate in P consecutive points respectively with t, rkRow constitute matrix, rkIndicate known existing hot spot
Vector Groups.Known A, B, rk, derive the hot spot point Vector Groups t of unknown missing, utilize B and rkLinear relationship, be derived by
One coefficient vector y：
Wherein, the pseudo inverse matrix of (Bk)+be Bk, expression is wherein least square method variable.
After acquiring coefficient vector y, vectorial t can be represented：
tT=(t1,t2,...,tq)T=ATY=AT·(Bk)+r (11)
After matrix B composition known to formula (11), coefficient vector y can be obtained by least square method：
The Vector Groups of hot spot point are illustrated by the linear combination of P consecutive points, but the linear combination does not use norm
It minimizes, has greater advantage on image procossing in view of norm minimum, the y that formula (12) is acquired dissolves, and increases a norm
Constraint γ | | y | |1, have：
Wherein γ indicates a scale scalar, that is, | | y | |1Shared proportion.
Vacancy point is searched out, is i.e. after vector t, is set to origin O, horizontal direction is x-axis, and vertical direction is y
Axis, as shown in Figure 2.
After the vacancy point for obtaining hot spot distribution map, i.e. origin O, carried out using the Global Information and details feature of hot spot figure
Piecemeal, the main process of piecemeal are related with each frame positioning of hot spot pixel groups.Known Hartmann sensor CCD pixel dimensions
For 7.4 μm of 7.4 μ m, it is 17 × 17 pixels to take the size of each pixel groups, centered on origin O, defines center pixel region
(- 8≤x≤8, -8≤y≤8) be hot spot distribution map pixel groups origin, as shown in the small box in Fig. 2, on this basis with
Line direction is carried out to whole picture hot spot figure centered on pixel groups origin and column direction is divided, effect is as shown in Figure 3 after segmentation.
The hot spot distribution map defined when wedge is rotated to 315 degree of positions is A group hot spot distribution maps, and wedge is rotated to 45 degree of positions
Hot spot distribution map is B group hot spot distribution maps when setting, and it is C group hot spot distribution maps that wedge, which is rotated to hot spot distribution map when 135 degree of positions,
It is D group hot spot distribution maps that wedge, which is rotated to hot spot distribution map when 225 degree of positions,.To each sub- picture after the segmentation of lack sampling hot spot distribution map
The coordinate of element group provides in the matrix form, by taking the hot spot distribution map of A groups as an example：
Wherein, M and N is respectively the line number and columns of lenticule.
The coordinate of pixel equally provides in the matrix form in each sub-pixel group, with A11For pixel groups：
M=28, N=37, p=17, q=17 can be determined according to the relevant parameter of the lenticule of use and CCD.
Image pixel after image mosaic is 4 times of lack sampling hot spot distribution map, and the pixel groups after reconstruction can be by matrix F
It indicates：
Each sub-pixel group of tetra- groups of lack sampling hot spot distribution maps of A, B, C, D is spliced using point-by-point when carrying out image mosaic,
A11The tail row pixel groups (x of group1yq,x2yq,...,xpyq)TWith B11First pixel groups (x of group1y1,x2y1,...,xpy1)TIt carries out
Point-by-point splicing, A11The tail row pixel groups (x of grouppy1,xpy2,...,xpyq) and C11First trip pixel groups (the x of group1y1,x1y2,...,
x1yq) spliced point by point, C11The tail row pixel groups (x of group1yq,x2yq,...,xpyq)TWith D11First pixel groups (x of group1y1,
x2y1,...,xpy1)TSpliced point by point, B11The tail row pixel groups (x of grouppy1,xpy2,...,xpyq) and D11The first trip pixel of group
Group (x1y1,x1y2,...,x1yq) spliced point by point.Successively to each sub-pixel of tetra- groups of lack sampling hot spot distribution maps of A, B, C, D
The hot spot distribution map after rebuilding is formed after the completion of group splicing, as shown in Figure 4.
Step 101, it can be found out respectively by four groups of spot centroid shift amounts each in sub-aperture layout new after rebuilding
Average wavefront slope G of the sub-aperture on the direction x, yx(xF,yF) and Gy(xF,yF)：
Wherein, Δ xFWith Δ yFFacula mass center of the new sub-aperture layout sub-aperture on the direction x, y after respectively rebuilding
Offset, λ are detection wavelength, and f is the focal length of lenticule.
After spot centroid shift amount is brought into, it is 2M × 2N to obtain a size corresponding with each sub-aperture after reconstruction
Slope matrix；
Step 102, before indicating the completed wave with distortion using the polynomial extreme value expression-forms of ZernikeI.e.：
Wherein akIndicate kth rank Zernike multinomial coefficients, zk(xF,yF) represent kth rank Zernike multinomials.By formula
(19) wavefront slope can be obtained：
G-bar i-th in new sub-aperture after reconstruction in (1≤i≤4MN) sub-aperture：
Wherein, SiFor the normalized area of i-th of sub-aperture.
Formula (22) and (23) are expressed as with matrix form：
Above formula is denoted as：
G=ZA (25)
It can be obtained by matrix properties：
A=Z+·G (26)
Wherein, A is Zernike mode coefficient vectors, Z+It is the generalized inverse matrix of Z, matrix Z for wavefront reconstruction matrix
New sub-aperture layout after being rebuild by micro scanning Hartmann sensor determines, after being rebuild according to micro scanning Hartmann sensor
New sub-aperture layout, which is realized to calculate, to be generated, so can acquire vectorial A after one group of slope vector G for measuring tested wavefront, most
Hartmann's wavefront is reconstructed eventually.
Description of test
In order to prove the wavefront reconstruction effect of the present invention, double 2 × 2 pattern micro scannings of wedge and monochromatic light wedge are used separately below
Wavefront is reconstructed in micro- Hartmann sensor swept.
Using 2 × 2 pattern micro scanning Hartmann sensor of double wedges and traditional Hartmann sensor wave front restoration data
As shown in table 1：
Zernike table 1 traditional Hartmann sensor and the Hartmann sensor of micro scanning is used to be obtained through wave front restoration
Coefficient
In order to evaluate tested wave front restoration situation, Hartmann sensor is incident before and after calculating separately the double wedge micro scannings of addition
Wavefront and the phase average for restoring wavefrontWith root-mean-square valve RMS：
Wherein, b indicates the number of phase sample point,For c-th point of phase value.
Wave-front phase residual error is represented by：
Wherein,For c-th point of original phase value,For c-th point of recovery phase value.
Wave-front phase residual mean square (RMS) root RMSDWith original wavefront phase root mean squareRatio be recovery to wavefront
Evaluation index is expressed as with J：
It brings the data in table 1 into above formula, is not used the Hartmann sensor wave front restoration evaluation index of micro scanning
J0=0.0892, using the Hartmann sensor wave front restoration evaluation index J of double wedge micro scannings1=0.0581, to wave front restoration
Raising percentage be：
(J0-J1)/J1=53.53% (40)
The above results demonstrate the reconstitution properties to wavefront using pair Hartmann sensor of 2 × 2 pattern micro scanning of wedge
Higher than do not use the Hartmann sensor of micro scanning device to the reconstitution properties of wavefront.
Using monochromatic light wedge micro scanning Hartmann sensor and traditional Hartmann sensor wave front restoration data such as 2 institute of table
Show：
Zernike table 2 traditional Hartmann sensor and the Hartmann sensor of micro scanning is used to be obtained through wave front restoration
Coefficient
In order to evaluate tested wave front restoration situation, calculates separately and be added before and after monochromatic light wedge micro scanning, by the data band in table 2
Enter formula (30), is not used the Hartmann sensor wave front restoration evaluation index J of micro scanning0=0.0892, using monochromatic light wedge
The Hartmann sensor wave front restoration evaluation index J of micro scanning1=0.0684, the raising percentage to wave front restoration is：
(J0-J1)/J1=30.41%
The above results, which are demonstrated, is higher than the reconstitution properties of wavefront using the Hartmann sensor of monochromatic light wedge pattern micro scanning
Do not use the Hartmann sensor of micro scanning device to the reconstitution properties of wavefront.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, the present invention can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
God and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (4)
1. a kind of Hartmann's wavefront reconstruction method to match with micro scanning device, which is characterized in that this method includes following step
Suddenly：
Tetra- groups of facula mass center coordinates of A, B, C, D that iteration weighted mass center algorithm obtains are used by the hot spot distribution map after rebuilding, are asked
Offset Δ x and Δ y of the glossing up barycenter in the directions x and the directions y；
Each sub-aperture is found out after rebuilding in new sub-aperture layout respectively by four groups of spot centroid shift amounts on the direction x, y
Average wavefront slope Gx(xF,yF) and Gy(xF,yF), obtained after the spot centroid shift amount acquired is brought into rebuild after it is each
The corresponding slope matrix of sub-aperture；
Before the slope matrix is expressed as the completed wave with distortion using Zernike polynomial extreme value expression-formsByIt can obtain the wavefront slope G of Zernike polynomial formsx(xF,yF) and Gy(xF,yF)；
By the wavefront slope G of Zernike polynomial formsx(xF,yF) and Gy(xF,yF) it is expressed as matrix form G=ZA, matrix
New sub-aperture layout after Z is rebuild by micro scanning Hartmann sensor determines to get to can acquire after slope vector G
Zernike coefficient vector A, and then Hartmann's wavefront is reconstructed.
2. the Hartmann's wavefront reconstruction method to match as described in claim 1 with micro scanning device, which is characterized in that A, B,
C, it is obtained when tetra- groups of hot spots of D are rotated by wedge to 315 degree, 45 degree, 135 degree and 225 degree of positions respectively, A group centroid offset Δs
xAWith Δ yAIt is expressed as：
Wherein, (xAcore,yAcore) be A groups facula mass center coordinate；
B group centroid offset Δs xBWith Δ yBIt is expressed as：
Wherein, (xBcore,yBcore) be B groups facula mass center coordinate；
C group centroid offset Δs xCWith Δ yCIt is expressed as：
Wherein, (xCcore,yCcore) be C groups facula mass center coordinate；
D group centroid offset Δs xDWith Δ yDIt is expressed as：
Wherein, (xDcore,yDcore) be D groups facula mass center coordinate；
L indicates that the width of single lenticule, the i.e. length of sub-aperture, p indicate the pixel dimension of ccd detector in formula (1)-(8),It represents less than and is equal toMaximum integer.
3. the Hartmann's wavefront reconstruction method to match as described in claim 1 with micro scanning device, which is characterized in that utilize
Before the slope matrix is expressed as the completed wave with distortion by the polynomial extreme value expression-forms of ZernikeFor：
Wherein akIndicate kth rank Zernike multinomial coefficients, zk(xF,yF) kth rank Zernike multinomials are represented, by
It can obtain the wavefront slope G of Zernike polynomial formsx(xF,yF) and Gy(xF,yF)：
4. the Hartmann's wavefront reconstruction method to match as claimed in claim 3 with micro scanning device, which is characterized in that rebuild
G-bar in new sub-aperture afterwards in i-th of sub-aperture is：
Wherein, SiFor the normalized area of i-th of sub-aperture；
Formula (12) and (13) are expressed as with matrix form：
Above formula is denoted as：
G=ZA (15)
It can be obtained by matrix properties：
A=Z+·G (16)
Wherein, A is Zernike mode coefficient vectors, Z+It is the generalized inverse matrix of Z for wavefront reconstruction matrix.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109741266A (en) * | 2018-12-03 | 2019-05-10 | 西北核技术研究所 | A kind of recovery display methods of array detection method representation of laser facula |
| CN111238664A (en) * | 2020-02-24 | 2020-06-05 | 中国科学院云南天文台 | Hartmann shack wavefront detection method based on region detection and reconstruction |
| CN112528514A (en) * | 2020-12-21 | 2021-03-19 | 北京机电工程研究所 | High-precision sub-pixel star spot remodeling method and device |
-
2018
- 2018-04-02 CN CN201810282741.1A patent/CN108663123A/en active Pending
Non-Patent Citations (1)
| Title |
|---|
| 马辰昊等: "《双光楔微扫描哈特曼-夏克波前探测技术》", 《红外与激光工程》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109741266A (en) * | 2018-12-03 | 2019-05-10 | 西北核技术研究所 | A kind of recovery display methods of array detection method representation of laser facula |
| CN109741266B (en) * | 2018-12-03 | 2021-04-02 | 西北核技术研究所 | Restoration display method for laser spot image by array detection method |
| CN111238664A (en) * | 2020-02-24 | 2020-06-05 | 中国科学院云南天文台 | Hartmann shack wavefront detection method based on region detection and reconstruction |
| CN111238664B (en) * | 2020-02-24 | 2021-03-30 | 中国科学院云南天文台 | Hartmann shack wavefront detection method based on region detection and reconstruction |
| CN112528514A (en) * | 2020-12-21 | 2021-03-19 | 北京机电工程研究所 | High-precision sub-pixel star spot remodeling method and device |
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