CN112115411B - Position drift compensation method, terminal device and readable storage medium - Google Patents
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Abstract
The invention provides a position drift compensation method, terminal equipment and a readable storage medium, wherein the method comprises the following steps: s101: collecting a first frame image P of a piece to be detected 1 The method comprises the steps of carrying out a first treatment on the surface of the Setting the acquisition frame number of the image to be measured as N, the current acquisition frame as k, the acquisition image as P and the accumulated convolution kernel as H, so that k=2 and P=P 1 H=0; s102: collecting a kth frame image P of a piece to be detected k And calculates a convolution kernel h corresponding to the translation transformation from the first frame image to the kth frame image k The method comprises the steps of carrying out a first treatment on the surface of the S103: let k=k+1, p=p+p k 、H＝H+h k If k is less than or equal to N, returning to the step S102; if k>And N, deconvoluting the acquired image P based on the accumulated convolution kernel H to obtain a compensation image of the piece to be detected. The position drift compensation method, the terminal equipment and the readable storage medium provided by the invention can reduce the real-time operation amount and the operation cost.
Description
Technical Field
The invention belongs to the technical field of microscopic imaging, and particularly relates to a position drift compensation method, terminal equipment and a readable storage medium.
Background
In order to achieve high spatial resolution microscopic thermal imaging, microscopic light reflection thermal imaging devices are generally built based on a high-performance optical microscope, probe light is provided by an illumination system of the optical microscope, microscopic imaging is recorded using a high-performance camera, and the output camera reading is taken as a measurement value. In the measurement process, since the measured value is usually low, in order to ensure the measurement accuracy, the measurement is usually required to be performed multiple times when the measured value is acquired, and the average value of multiple frames of images is acquired. However, in the process of multiple measurement, accurate alignment of all images cannot be ensured, and position drift exists, which can cause blurring of the averaged images and affect measurement accuracy.
In the prior art, the method for solving the position drift is to estimate the generated translation amount by utilizing an algorithm while multi-frame image acquisition is carried out, and to compensate the position drift in real time by utilizing image processing modes such as interpolation and the like.
Disclosure of Invention
The invention aims to provide a position drift compensation method, terminal equipment and a readable storage medium, which are used for solving the problems of large operation amount and high operation cost when position drift compensation is carried out in the prior art.
In a first aspect of an embodiment of the present invention, a position drift compensation method is provided, including:
s101: collecting a first frame image P of a piece to be detected 1 The method comprises the steps of carrying out a first treatment on the surface of the Setting the acquisition frame number of the image to be measured as N, the current acquisition frame as k, the acquisition image as P and the accumulated convolution kernel as H, so that k=2 and P=P 1 、H＝0；
S102: collecting a kth frame image P of a piece to be detected k And calculates a convolution kernel h corresponding to the translation transformation from the first frame image to the kth frame image k ；
S103: let k=k+1, p=p+p k 、H＝H+h k If k is less than or equal to N, returning to the step S102; if k>And N, deconvoluting the acquired image P based on the accumulated convolution kernel H to obtain a compensation image of the piece to be detected.
In a second aspect of the embodiment of the present invention, another position drift compensation method is provided, including:
s201: setting the current acquisition times as n, the total acquisition times as Nmax and the accumulated compensation image as P1, and enabling n=0 and P1=0;
s202: collecting the n+1 th frame to the n+d th frame of the part to be measured, and calculating a basic compensation image P of the d frame image according to the method of step Sa n ；
S203: let n=n+1, p1=p1+p n If n is less than or equal to Nmax, returning to step S202; if n>Nmax, determining a compensation image of the part to be measured based on the accumulated compensation image P1;
the step Sa comprises the following steps:
for a certain d frame image, selecting a first frame image in the d frame image as a reference image; calculating convolution kernels of the reference image translation conversion to other frame images, and deconvolving the d frame image based on the convolution kernels of the reference image translation conversion to other frame images to obtain a basic compensation image of the d frame image; wherein, the other frame images are other images except the reference image in the d frame image.
In a third aspect of the embodiment of the present invention, there is provided a position drift compensation method, including:
s301: setting the current acquisition times as n and the total acquisition times as Nmax, wherein n=0;
s302: collecting the n+1 th frame to the n+d th frame of the part to be measured, and calculating a basic compensation image P of the d frame image according to the method of the step Sc n And the base compensation image P of the d frame image is used for n Adding the image to a preset compensation image set;
s303: let n=n+1, if n+.nmax, return to execute step S302; if n is greater than Nmax, determining a compensation image of the piece to be detected based on the compensation image set;
wherein, the step Sc comprises the following steps:
for a certain d frame image, selecting a first frame image in the d frame image as a first reference image; calculating convolution kernels of the first reference image in translation and transformation to other frame images, and deconvolving the d frame image based on the convolution kernels of the first reference image in translation and transformation to other frame images to obtain a basic compensation image of the d frame image; wherein the other frame images are other images except the first reference image in the d frame image.
In a fourth aspect of the embodiments of the present invention, there is provided a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the above-mentioned position drift compensation method when executing the computer program.
In a fifth aspect of the embodiments of the present invention, there is provided a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the position drift compensation method described above.
The position drift compensation method, the terminal equipment and the readable storage medium provided by the embodiment of the invention have the beneficial effects that: compared with the prior art, the position drift compensation method provided by the invention does not need to compensate the image of the to-be-measured piece in real time in implementation, and only needs to carry out deconvolution on the image of the to-be-measured piece by utilizing the obtained convolution check after obtaining the convolution kernel of a fixed number, namely, the position drift compensation method provided by the invention effectively reduces the real-time operand, thereby reducing the operation cost.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a position drift compensation method according to an embodiment of the invention;
FIG. 2 is a flowchart illustrating a position drift compensation method according to another embodiment of the present invention;
FIG. 3 is a flowchart illustrating a position drift compensation method according to another embodiment of the present invention;
fig. 4 is a schematic block diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In order to make the technical problems, technical schemes and beneficial effects to be solved more clear, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a flowchart of a position drift compensation method according to an embodiment of the invention, where the method includes:
s101: collecting a first frame image P of a piece to be detected 1 Setting the acquisition frame number of the image to be measured as N, the current acquisition frame as k, the acquisition image as P and the accumulated convolution kernel as H, so that k=2 and P=P 1 、H＝0。
S102: collecting a kth frame image P of a piece to be detected k And calculates a convolution kernel h corresponding to the translation transformation from the first frame image to the kth frame image k 。
S103: let k=k+1, p=p+p k 、H＝H+h k If k is less than or equal to N, the process returns to step S102. If k>And N, deconvoluting the acquired image P based on the accumulated convolution kernel H to obtain a compensation image of the piece to be detected.
In this embodiment, N is an integer greater than zero, and the value thereof may be set according to actual requirements, which is not limited herein.
In this embodiment, the first frame image of the to-be-measured piece is used as the reference image, only the convolution kernel of the translation transformation of the first frame image to other frame images needs to be calculated in the real-time calculation part, the convolution kernel is continuously accumulated, and finally the deconvolution is performed on the to-be-measured piece image according to the accumulated convolution kernel, so that the compensation image can be obtained. That is, the position drift compensation method provided by the embodiment of the invention does not need to compensate the image of the to-be-measured piece in real time.
In this embodiment, the principle of the embodiment of the present invention is explained from the following:
let the total acquisition of N frames of images, the kth frame is P k The average image of all frame images isI.e.
Taking the first frame image as a reference image, in the case of translational transformation, all frame images can be expressed as follows
P k ＝(s+n k )*h k
Wherein s is an imaginary displacement-free "in-situ" ideal image, n k Is noise, h k Is the convolution kernel of the translation transform.
Wherein,can be converted into:
from the above formula:
wherein,noise corresponding to translation transform of all frame images, h k Corresponding to the translation amount of each frame image relative to the reference image, namely, the translation conversion of the reference image to the convolution kernel of each frame image, the embodiment of the invention can obtain h by estimating the translation amount of each frame image relative to the reference image in real time k Then the average convolution kernel g can be obtained by accumulating the last divided frames frame by frame, and finally the average convolution kernel g is utilized to carry out the +.>Deconvolution yields the desired ideal image (i.e., compensation image) s.
The convolution kernel h and the average convolution kernel g may also be processed in the frequency domain: the Fourier transforms of g and h are set as G, H, respectively, and the summation is linear operation, so the method still meets the requirement
That is, the method of accumulating the last divided frame number frame by frame can be used to obtain G. The translation amount estimation can adopt a related phase method, H can be conveniently obtained at the moment, and deconvolution methods such as wiener filtering and the like also need to be processed in a frequency domain, and the accumulation amount (comprising an image and an estimated convolution kernel) in the frequency domain form is simpler and more convenient at the moment.
In this embodiment, if the compensation of the position drift is performed in the frequency domain, the method may be:
setting the acquired k frame image as P k Fourier transform thereof into P fk The convolution kernel is denoted as h k The convolution kernel accumulated value is noted as H and the image accumulated value is noted as P.
First, when k=1, the acquired image is P 1 Fourier transform to P f1 ，h k And H are all 0, p=p f1 。
For each subsequent frame, calculate P k Fourier transform P of (2) fk And estimate h k Here, a correlation phase method may be used to calculate the convolution kernel h for the translational transformation of the first frame image to the kth frame image k Other methods may be used to estimate the amount of sub-pixel shift, and are not limited in this regard.
Translation estimation/convolution kernel calculation:
updating the accumulated value:
H＝H+h k
P＝P+P fk
after all frames are collected and P and H are calculated, deconvolution processing is carried out in a frequency domain to obtain S:
and carrying out inverse Fourier transform on the S to obtain the S, namely the compensation image.
In this embodiment, if the compensation of the position drift is performed in the airspace, the method may be:
setting the acquired k frame image as P k The convolution kernel is denoted as h k The convolution kernel accumulated value is noted as H and the image accumulated value is noted as P. The spatial processing needs to determine the size of the convolution kernel, and the maximum value of the position drift can be estimated, and the maximum value is taken as the size of the convolution kernel, and in this embodiment, the convolution kernel can contain a possible drift range.
First, when k=1, the acquired image is P 1 ，h k And H are all 0, p=p 1 。
For each subsequent frame, with P 1 The sub-pixel translation amount estimation is performed for the reference image, wherein the sub-pixel translation amount estimation can be realized by using the existing methods based on interpolation calculation and the like, and the details are not repeated here;
in the process of calculating h k Post-update accumulated value:
H＝H+h k
P＝P+P k
after all N frames are acquired and P and H are calculated, an average convolution kernel g and an average image are calculated
For g anddeconvolution is performed to obtain s, namely the compensation image.
It can be obtained from the above that, compared with the prior art, the position drift compensation method provided by the invention does not need to compensate the image of the to-be-measured member in real time in implementation, but only needs to deconvolute the obtained image of the to-be-measured member by utilizing the obtained convolution check after obtaining a fixed number of convolution kernels, that is, the position drift compensation method provided by the invention effectively reduces the real-time operand, thereby reducing the operation cost.
Optionally, as a specific implementation manner of the position drift compensation method provided by the embodiment of the present invention, calculating a convolution kernel corresponding to a translation transformation from a first frame image to a kth frame image includes:
and carrying out sub-pixel translation amount estimation on the kth frame image by taking the first frame image as a reference, and determining a convolution kernel corresponding to the first frame image through translation conversion to the kth frame image according to the estimated translation amount.
In this embodiment, the estimation of the sub-pixel shift amount may be implemented by using a correlation phase method, an interpolation method, or the like, and in this embodiment, the estimated shift amount is used as a convolution kernel corresponding to the first frame image and shifted to the kth frame image.
Optionally, as a specific implementation manner of the position drift compensation method provided by the embodiment of the present invention, deconvoluting the acquired image P based on the accumulated convolution kernel H to obtain a compensated image of the to-be-measured member, including:
and carrying out averaging treatment on the acquired images to obtain average images.
And carrying out averaging treatment on the accumulated convolution kernel to obtain an average convolution kernel.
And deconvoluting the average image based on the average convolution check to obtain a compensation image of the piece to be detected.
In this embodiment, the average image is obtained by dividing the total frame number of the image by the acquired image, and the average convolution kernel is obtained by dividing the total frame number of the image by the cumulative convolution kernel.
Referring to fig. 2 together, fig. 2 is a flow chart of a position drift compensation method according to another embodiment of the present disclosure. The method comprises the following steps:
s201: setting the current acquisition times as n, the total acquisition times as Nmax and the accumulated compensation image as P1, and enabling n=0 and p1=0.
S202: collecting the n+1 th frame to the n+d th frame of the part to be measured, and calculating a basic compensation image P of the d frame image according to the method of step Sa n 。
S203: let n=n+1, p1=p1+p n If n is less than or equal to Nmax, the process returns to step S202, if n>Nmax, a compensation image of the part to be measured is determined based on the accumulated compensation image P1.
The step Sa comprises the following steps:
for a certain d-frame image, selecting a first frame image in the d-frame image as a reference image. And calculating convolution kernels of the reference image translational transformation to other frame images, and deconvolving the d frame image based on the convolution kernels of the reference image translational transformation to other frame images to obtain a basic compensation image of the d frame image. Wherein, other frame images are other images except the reference image in the d frame image.
In this embodiment, d frame images may be acquired each time, the d frame images are used as a compensation period, the compensation images of the d frame images are calculated according to the method of steps S101-S103, and finally all the obtained compensation images are averaged to obtain the final compensation image of the workpiece to be measured. Compared with the prior art, the method also reduces the real-time operation amount and the operation cost.
Optionally, as a specific implementation manner of the position drift compensation method provided by the embodiment of the present invention, determining the compensation image of the to-be-measured piece based on the accumulated compensation image P1 includes:
and carrying out averaging treatment on the accumulated compensation image, and taking the image after the averaging treatment as a compensation image of the to-be-detected piece.
In this embodiment, the average image of the accumulated compensation image, that is, the compensation image, can be obtained by dividing the accumulated compensation image by the total number of acquisitions.
Optionally, as a specific implementation manner of the position drift compensation method provided by the embodiment of the present invention, deconvoluting the d-frame image based on a convolution of the reference image shifted to other frame images to obtain a basic compensation image of the d-frame image, including:
and carrying out averaging treatment on the d-frame image to obtain a d-frame average image.
And carrying out averaging treatment on convolution kernels of the reference image shifted to other images of each frame to obtain d-frame average convolution kernels.
And deconvolving the d-frame average image based on the d-frame average convolution check to obtain a basic compensation image of the d-frame image.
In this embodiment, the process is the same as the implementation method of "deconvolving the acquired image P based on the accumulated convolution kernel H" in step S103, and will not be described here again.
Referring to fig. 3 together, fig. 3 is a flowchart illustrating a position drift compensation method according to another embodiment of the present disclosure. The method comprises the following steps:
s301: the current collection times are set to be n, the total collection times are set to be Nmax, and n=0.
S302: collecting the n+1 th frame to the n+d th frame of the part to be measured, and calculating a basic compensation image P of the d frame image according to the method of the step Sc n And the base compensation image P of the d frame image is used for n To a preset set of compensated images.
S303: let n=n+1, and if n+.nmax, return to step S302. And if n > Nmax, determining a compensation image of the to-be-measured piece based on the compensation image set.
Wherein, the step Sc comprises the following steps:
for a certain d-frame image, a first frame image in the d-frame image is selected as a first reference image. And calculating convolution kernels of the first reference image translational transformation to other frame images, and deconvolving the d frame image based on the convolution kernels of the first reference image translational transformation to other frame images to obtain a basic compensation image of the d frame image. Wherein, other frame images are other images except the first reference image in the d frame image.
In this embodiment, d frame images may be acquired each time, the d frame images are used as a compensation period, the compensation images of the d frame images are calculated according to the method of steps S101-S103, multiple compensation images may be acquired multiple times, and finally the multiple compensation images are processed for a second time according to the method of steps S101-S103, and finally the compensation images of the piece to be measured are obtained. The method not only can reduce the real-time operation amount and the operation cost, but also has higher fault tolerance.
Optionally, as a specific implementation manner of the position drift compensation method provided by the embodiment of the present invention, determining a compensation image of the to-be-measured piece based on the compensation image set includes:
and selecting the first frame image in the compensation image set as a second reference image.
A convolution kernel is computed for the translational transformation of the second reference image to the other compensated image.
And performing deconvolution on the compensation data set based on the convolution check of the translation transformation of the second reference image to other compensation images to obtain the compensation image of the piece to be detected.
Wherein the other compensation image is other image than the second reference image in the compensation image set.
In this embodiment, the process is the same as steps S101-S103, and will not be described here again.
Referring to fig. 4, fig. 4 is a schematic block diagram of a terminal device according to an embodiment of the present invention. The terminal 400 in the present embodiment as shown in fig. 4 may include: one or more processors 401, one or more input devices 402, one or more output devices 403, and one or more memories 404. The processor 401, the input device 402, the output device 403, and the memory 404 communicate with each other via a communication bus 405. The memory 404 is used to store a computer program comprising program instructions. The processor 401 is arranged to execute program instructions stored in the memory 404. Wherein the processor 401 is configured to invoke program instructions to perform the steps of the method embodiments described above.
It should be appreciated that in embodiments of the present invention, the processor 401 may be a central processing unit (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The input device 402 may include a touch pad, a fingerprint sensor (for collecting fingerprint information of a user and direction information of a fingerprint), a microphone, etc., and the output device 403 may include a display (LCD, etc.), a speaker, etc.
The memory 404 may include read only memory and random access memory and provide instructions and data to the processor 401. A portion of memory 404 may also include non-volatile random access memory. For example, memory 404 may also store information of device type.
In a specific implementation, the processor 401, the input device 402, and the output device 403 described in the embodiments of the present invention may execute the implementation described in the first embodiment and the second embodiment of the position drift compensation method provided in the embodiments of the present invention, and may also execute the implementation of the terminal described in the embodiments of the present invention, which is not described herein again.
In another embodiment of the present invention, a computer readable storage medium is provided, where the computer readable storage medium stores a computer program, where the computer program includes program instructions, where the program instructions, when executed by a processor, implement all or part of the procedures in the method embodiments described above, or may be implemented by instructing related hardware by the computer program, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by the processor, implements the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
The computer readable storage medium may be an internal storage unit of the terminal of any of the foregoing embodiments, such as a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit of the terminal and an external storage device. The computer-readable storage medium is used to store a computer program and other programs and data required for the terminal. The computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working procedures of the terminal and the unit described above may refer to the corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In several embodiments provided in the present application, it should be understood that the disclosed terminal and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via some interfaces or units, or may be an electrical, mechanical, or other form of connection.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present invention.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The present invention is not limited to the above embodiments, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the present invention, and these modifications and substitutions are intended to be included in the scope of the present invention. Therefore, the protection scope of the invention is subject to the protection scope of the claims.
Claims (8)
1. A method of compensating for position drift, comprising:
s101: collecting a first frame image P of a piece to be detected 1 The method comprises the steps of carrying out a first treatment on the surface of the Setting the acquisition frame number of the image to be measured as N, the current acquisition frame as k, the acquisition image as P and the accumulated convolution kernel as H, so that k=2 and P=P 1 、H＝0；
S102: collecting a kth frame image P of a piece to be detected k And calculates a convolution kernel h corresponding to the translation transformation from the first frame image to the kth frame image k ；
S103: let k=k+1, p=p+p k 、H＝H+h k If k is less than or equal to N, returning to the step S102; if k>N, deconvoluting the acquired image P based on the accumulated convolution kernel H to obtain a compensation image of the piece to be detected;
the calculation of the convolution kernel corresponding to the translation transformation of the first frame image to the kth frame image comprises the following steps:
carrying out sub-pixel translation amount estimation on a kth frame image by taking the first frame image as a reference, and carrying out translation transformation on the estimated translation amount as a convolution kernel corresponding to the first frame image;
deconvolution is carried out on the acquired image P based on the accumulated convolution kernel H to obtain a compensation image of the piece to be detected, and the deconvolution method comprises the following steps:
averaging the acquired images to obtain average images;
averaging the accumulated convolution kernels to obtain average convolution kernels;
and deconvoluting the average image based on the average convolution check to obtain a compensation image of the piece to be detected.
2. A method of compensating for position drift, comprising:
s201: setting the current acquisition times as n, the total acquisition times as Nmax and the accumulated compensation image as P1, and enabling n=0 and P1=0;
s202: collecting the n+1 th frame to the n+d th frame of the part to be measured, and calculating a basic compensation image P of the d frame image according to the method of step Sa n ；
S203: let n=n+1, p1=p1+p n If n is less than or equal to Nmax, returning to step S202; if n>Nmax, determining a compensation image of the part to be measured based on the accumulated compensation image P1;
the step Sa comprises the following steps:
for a certain d frame image, selecting a first frame image in the d frame image as a reference image; calculating convolution kernels of the reference image translation conversion to other frame images, and deconvolving the d frame image based on the convolution kernels of the reference image translation conversion to other frame images to obtain a basic compensation image of the d frame image; wherein, the other frame images are other images except the reference image in the d frame image.
3. The positional drift compensation method according to claim 2, wherein the determining the compensation image of the part to be measured based on the accumulated compensation image P1 includes:
and carrying out averaging treatment on the accumulated compensation image, and taking the image after the averaging treatment as a compensation image of the to-be-detected piece.
4. The position drift compensation method of claim 2, wherein the deconvolution of the d-frame image based on the convolution of the reference image shift to other frame images, to obtain a base compensation image of the d-frame image, comprises:
carrying out averaging treatment on the d-frame image to obtain a d-frame average image;
carrying out averaging treatment on convolution kernels of the reference image which are shifted to other frames of images in a translation way to obtain d-frame average convolution kernels;
and deconvolving the d-frame average image based on the d-frame average convolution check to obtain a basic compensation image of the d-frame image.
5. A method of compensating for position drift, comprising:
s301: setting the current acquisition times as n and the total acquisition times as Nmax, wherein n=0;
s302: collecting the n+1 th frame to the n+d th frame of the part to be measured, and calculating a basic compensation image P of the d frame image according to the method of the step Sc n And the base compensation image P of the d frame image is used for n Adding the image to a preset compensation image set;
s303: let n=n+1, if n+.nmax, return to execute step S302; if n is greater than Nmax, determining a compensation image of the piece to be detected based on the compensation image set;
wherein, the step Sc comprises the following steps:
for a certain d frame image, selecting a first frame image in the d frame image as a first reference image; calculating convolution kernels of the first reference image in translation and transformation to other frame images, and deconvolving the d frame image based on the convolution kernels of the first reference image in translation and transformation to other frame images to obtain a basic compensation image of the d frame image; wherein the other frame images are other images except the first reference image in the d frame image.
6. The positional drift compensation method of claim 5, wherein the determining a compensation image of the part under test based on the set of compensation images comprises:
selecting a first frame image in the compensation image set as a second reference image;
calculating convolution kernels for translating the second reference image into other compensation images;
performing deconvolution on the compensation data set based on the convolution check of the second reference image translation conversion to other compensation images to obtain a compensation image of the piece to be detected;
wherein the other compensation image is other image than the second reference image in the compensation image set.
7. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 6 when the computer program is executed.
8. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 6.
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