CN115201110B - Laminated diffraction calculation imaging method and device for real-time noise separation - Google Patents
Laminated diffraction calculation imaging method and device for real-time noise separation Download PDFInfo
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Abstract
The invention discloses a laminated diffraction calculation imaging method and device with real-time noise separation, and belongs to the field of coherent diffraction imaging. According to the invention, a virtual probe model for bearing noise energy is provided for the first time, the coupled noise error is iteratively separated into the noise probe through a reconstruction algorithm, and the robustness of the reconstruction algorithm, the resolution and the contrast of a sample to be detected and an illumination wave front are greatly improved; meanwhile, the signal-to-noise ratio requirement of diffraction signals in a diffraction imaging system is greatly reduced, and the hardware condition limitations on the luminous flux of a coherent light source, the sampling noise of a detector, the dynamic range and the like are relaxed. The invention provides a laminated diffraction imaging method for noise separation, which can synchronously and parallelly calculate and reconstruct a sample to be detected and an illumination wave front by computer when a detector records diffraction field signals at different scanning positions, can separate dynamic changes of noise signals in a laminated diffraction scanning process in real time on line, has more accurate error separation, is adaptive to different calculation imaging systems, and has simpler operation flow.
Description
Technical Field
The invention belongs to the technical field of coherent diffraction imaging, and particularly relates to a laminated diffraction calculation imaging method and device for real-time noise separation.
Background
Because of the manufacturing bottlenecks of high imaging quality, large numerical aperture optical lenses, conventional optical microscopes have been difficult to meet the imaging characterization requirements of the emerging materials science and biology fields. The coherent diffraction imaging technology is used as a calculation imaging technology, and the amplitude and phase information of the sample is reconstructed in a calculation iteration mode through the diffraction field of interaction of the illumination light spot and the sample to be measured. Because it does not require high performance imaging optics, it is widely used in deep extreme ultraviolet, X-ray, and electron beam sources.
The traditional coherent diffraction imaging technology only calculates the amplitude and phase information of the sample to be detected in the illumination spot area through a single coherent diffraction field, and the algorithm is greatly limited in the aspects of convergence speed, noise robustness, imaging field of view, resolution and the like. In recent years, a new coherent diffraction imaging calculation method is developed, a series of coherent diffraction fields overlapped by a real space probe are obtained by translating an illumination probe or a sample to be detected, a CCD or CMOS detector records diffraction field intensity information in a reciprocal space, and finally lost phase information is solved through an iterative algorithm, namely, a stacked diffraction imaging method (ePIE, see Ultramicroscope 2009,109 (4): 338-343), and the method has great improvement in the aspects of convergence speed, imaging field of view, resolution, robustness and the like.
However, in the stacked diffraction imaging system, when a detector such as a CCD or a CMOS records a coherent diffraction field signal, photon shot noise, dark current noise, readout noise and the like introduced by hardware such as a photoelectric sensor greatly influence the resolution of computed imaging of a sample to be detected, and even cause an iterative algorithm to fall into a locally optimal or iterative unconverged state. The traditional laminated diffraction imaging method utilizes an iterative calculation method to decompose noise energy into complex amplitude fields of a sample to be detected and a probe, and the amplitude and phase information of the sample to be detected and the illumination probe can be reconstructed within a certain noise intensity range (the peak signal-to-noise ratio SNR is more than or equal to 40 dB). A least square stacked diffraction imaging method (LSQ-ML) of maximum likelihood estimation is proposed, which adopts maximum likelihood estimation iteration to reconstruct complex amplitude distribution of a sample to be measured and an illumination probe by establishing a mathematical model for noise error probability distribution. Compared with the traditional laminated diffraction calculation imaging method, the method has further improvement on noise robustness and calculation imaging resolution, but the method does not fundamentally separate noise errors from diffraction signals, the noise errors are still coupled in the illumination probe and the sample to be detected, and noise robustness and imaging resolution of the method are greatly limited. Therefore, for the existing stacked diffraction calculation imaging method, offline preprocessing is needed to be performed on the diffraction original signals before reconstruction, namely, a constant background dark field is subtracted from each detected diffraction signal to calibrate noise errors offline. The noise separation method does not consider real-time change in the signal acquisition process, and has great influence on the resolution, convergence speed and algorithm robustness of the laminated diffraction calculation imaging.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a laminated diffraction calculation imaging method and device for separating noise in real time, and aims to solve the problems that in the existing offline noise separation method, real-time change in the signal acquisition process is not considered, so that the clarity of a sample to be detected of laminated diffraction calculation imaging is degraded, the convergence speed of an iterative algorithm is slow, and even the iterative algorithm is in local optimum or is not converged due to noise.
To achieve the above object, in a first aspect, the present invention provides a method for stacked diffraction calculation imaging with real-time noise separation, which is applied to a stacked diffraction calculation imaging system, including:
s1, initializing an illumination probe, a sample to be tested and at least one noise probe, wherein the dimensions of the illumination probe, the sample to be tested and the noise probes are the same, and the wavelengths of all the probes are different;
s2, calculating the product of the illumination probe and the sample to be tested so as to simulate the illumination probe to act with the sample to be tested according to a scanning path to form emergent light; each noise probe is directly used as corresponding noise emergent light;
s3, inputting emergent light with different wavelengths into a light field propagation model to obtain a simulated diffraction light field with corresponding wavelengths so as to simulate the emergent light to propagate to a detector plane;
s4, superposing the simulated diffraction light field intensities of different wavelengths, replacing the amplitude of the simulated diffraction light field of each wavelength with the diffraction light field intensity measured in real time, and keeping the phase unchanged to obtain the simulated diffraction light field updated by each wavelength;
s5, inputting the diffraction light field updated by each wavelength into a light field reverse propagation model to obtain emergent light updated by each wavelength so as to simulate light propagation and reverse propagation to a sample to be tested;
s6, updating the front and rear emergent light according to each wavelength, and simultaneously updating the sample to be tested, the illumination probe and each noise probe;
s7, repeating the steps S2-S6 until simulation of all scanning positions on the scanning path is completed;
s8, calculating root mean square error of the composite diffraction light field intensity of all the wavelengths which are simulated and measured in an iteration mode, outputting complex amplitude information of the illumination probe and the sample to be tested after the iteration when the root mean square error is smaller than a preset threshold value, otherwise, turning to the step S2.
Preferably, in step S4, the simulated diffraction light field after each wavelength update is as follows:
wherein phi is m (q，λ i )，Φ′ m (q，λ i ) The wavelength lambda respectively representing the mth scanning position i I=1 corresponds to the illumination probe, i=2, … corresponds to the i-1 noise probe when n is the same, q represents the frequency domain coordinate, and n represents the number of probes with different wavelengths; i m (q) represents the intensity of the diffracted light field measured in real time at the mth scanning position.
The signal actually collected by the detector in the invention is a coupling signal of a noise signal and a diffraction signal. In order to replace the amplitudes of the diffraction light field signals with different wavelengths, the diffraction light field update (comprising an illumination probe diffraction field and a noise probe diffraction field) with different wavelengths before and after the amplitude constraint is calculated, and the diffraction light intensities generated by the probes with different wavelengths are required to be summed.
Preferably, in step S6, the sample to be tested, the illumination probe and each noise probe are updated simultaneously, specifically as follows:
wherein alpha, beta, gamma represent iterative search step length, and the value is 0,1]Between them; o (r), O' (r) represents the sample to be measured before and after updating, P m (r，λ 1 )，P m ′(r，λ 1 ) Respectively the illumination probes before and after updating at the mth scanning position,respectively representing the emergent light before and after the amplitude of the illumination probe at the mth scanning position is replaced, r represents real space coordinates and lambda 1 Indicating the wavelength of the illuminating probe, P m (r，λ i )，P m ′(r，λ i ) Respectively representing the i-1 th noise probe before and after updating at the mth scanning position lambda i Indicating the wavelength of the i-1 st noise probe,emergent light before and after replacement of the ith-1 noise probe amplitude respectively representing the mth scanning position, |representing conjugate operation of complex matrix, | max The maximum value of the amplitude of each element in the matrix is represented, and n represents the number of probes with different wavelengths.
It should be noted that, the present invention updates the complex amplitude distribution of the sample to be measured, the illumination probe and each noise probe synchronously in real time, the illumination probe interacts with the sample to be measured to generate a diffraction light field, the sample to be measured and the illumination probe are iteratively updated by adopting the direction of steepest gradient descent, the noise probe does not interact with any sample to be measured in the actual propagation model, and the iteration update direction is fixed.
Preferably, in step S8, the root mean square error of the iteratively simulated and measured composite diffracted light field intensities is as follows:
wherein m represents the number of scanning positions, n represents the number of probes with different wavelengths, phi m (q，λ n ) The wavelength of the mth scanning position is lambda n Complex amplitude function of simulated diffraction light field before probe updating, q represents frequency domain coordinates, I m (q) represents the intensity of the diffracted light field measured in real time at the mth scanning position.
It should be noted that the root mean square error of the intensity of the composite diffraction light field measured by fitting is smaller than the set threshold value as a criterion, and the mode guess value and the actual measured value are judged to be small enough, if the root mean square error is smaller than the set threshold value, the mode guess value and the actual measured value can be output, if the mode guess value and the actual measured value are larger than the set threshold value, iteration is continued according to the steepest gradient descent direction until the difference value of the mode guess value and the actual measured value is smaller than the threshold value, convergence is achieved, and a final result is output.
Preferably, the number of noise probes is [1,5].
It should be noted that, in order to achieve the purpose of separating noise errors, so that noise energy can be transferred into noise probes, the invention preferably uses 1 as the lower limit of the number of noise probes, in order to avoid that when the number of probes is too small and the noise energy is large, the number of noise probes is too small and is not completely separated, and meanwhile, the number of noise probes is too large to cause the increase of iteration speed, the calculation time and the calculation memory are obviously increased, and the invention preferably uses 5 as the upper limit of the number of noise probes.
Preferably, the stacked diffraction imaging system is a transmissive imaging system or a reflective imaging system.
It should be noted that the present invention is applicable to different kinds of computing imaging systems, and has strong applicability. The invention aims to solve the problem of real-time noise in the signal acquisition process, and detectors are used in all of stacked diffraction calculation imaging (reflection transmission type), fourier stacked diffraction imaging systems and coherence tomography systems, so that detector hardware errors exist, and the method is applicable.
To achieve the above object, in a second aspect, the present invention provides a laminated diffraction calculation imaging apparatus for noise real-time separation, comprising: a processor and a memory;
the memory is used for storing a computer program or instructions;
the processor is configured to execute the computer program or instructions in memory to cause the method of the first aspect to be performed.
In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:
(1) The invention provides a virtual probe model for bearing noise energy for the first time, based on the idea of error separation, the coupled noise error is iteratively separated into the noise probe through a reconstruction algorithm, and compared with the traditional laminated diffraction algorithm (ePIE) and the least squares laminated diffraction algorithm (LSQ-ML) of maximum likelihood estimation, the noise error can only be decomposed into complex amplitude distribution of a sample to be detected and an illumination wavefront, and the noise coupling error can not be separated from the diffraction signal; meanwhile, the signal-to-noise ratio requirement of diffraction signals in the stacked diffraction imaging system is greatly reduced, and the method has the prominent advantages in terms of relaxing hardware limitations on the luminous flux of a coherent light source, sampling noise of a detector, dynamic range and the like, which cannot be solved by the existing PIE and LSQ-ML stacked diffraction imaging method.
(2) The laminated diffraction calculation imaging algorithm for noise separation can synchronously and parallelly calculate and reconstruct a sample to be detected and an illumination wave front when the detector records diffraction field signals of different scanning positions, and compared with the calibration method for off-line pretreatment of the traditional laminated diffraction noise dark field, the method provided by the invention can separate dynamic changes of signal noise in the laminated diffraction scanning process in real time and on line, has more accurate error separation, can further improve reconstruction resolution and contrast of the sample to be detected and the illumination wave front, is adaptive to different calculation imaging systems, and has simpler operation flow.
Drawings
FIG. 1 is a schematic diagram of an optical path of a stacked diffraction computational imaging system provided by an embodiment of the present invention;
FIG. 2 is a flow chart of a method for stacked diffraction calculation imaging with real-time noise separation provided by an embodiment of the present invention;
FIG. 3 is a diagram showing the amplitude and phase patterns of a sample to be tested and an illumination probe used in a simulation process according to an embodiment of the present invention;
FIG. 4 is a two-dimensional motion plane trace of a sample to be measured of a stacked diffraction computed imaging system provided by an embodiment of the present invention;
FIG. 5 is a graph showing diffraction field intensity profiles collected by an illumination probe and a detector under different noise for a stacked diffraction imaging system provided by an embodiment of the present invention;
FIG. 6 shows the amplitude pattern and the phase pattern of a sample to be measured and an illumination probe reconstructed by different stacked diffraction calculation imaging algorithms by adding 0.01 times (40 dB) Gaussian random noise;
FIG. 7 shows the amplitude pattern and the phase pattern of a sample to be measured and an illumination probe reconstructed by different stacked diffraction calculation imaging algorithms by adding 0.1 times (20 dB) Gaussian random noise;
FIG. 8 shows the amplitude pattern and the phase pattern of a sample to be measured and an illumination probe reconstructed by different stacked diffraction calculation imaging algorithms by adding 10 times (-20 dB) Gaussian random noise provided by the embodiment of the invention;
the same reference numbers are used throughout the drawings to reference like elements or structures, wherein:
1-helium-neon laser, 2-beam expander, 3-adjustable diaphragm, 4-focusing lens/reflector, 5-sample to be measured and 6-camera.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. 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.
The invention provides a laminated diffraction calculation imaging method for real-time noise separation, which is applied to a laminated diffraction calculation imaging system and comprises the following steps:
step S1: laminated diffraction imaging systems are built, including but not limited to transmissive imaging systems and reflective imaging systems.
Fig. 1 is a schematic diagram of an optical path of a stacked diffraction computational imaging system according to an embodiment of the present invention. (a) Is a transmissive stacked diffraction computed imaging system and (b) is a reflective stacked diffraction computed imaging system. The laminated diffraction system is sequentially arranged as follows: a helium-neon laser 1, a beam expander 2, a tunable aperture 3, a focusing lens/focusing mirror 4, a sample 5 to be measured and a camera 6.
Step S2: the optical path system was adjusted to have an operating wavelength of 632.8nm and a beam diameter (1/e) 2 ) The output beam of the helium-neon laser 1 with the thickness of 0.54mm is expanded by 10 times through the beam expander 2, the ideal spot diameter is adjusted to be 2mm through the aperture of the adjustable diaphragm 3, the collimated parallel beam irradiates the sample 5 to be detected after passing through the focusing lens/focusing reflector 4 with the effective focal length of 10cm, and the sample is positioned at the position about 1.5mm away from the back focal plane of the focusing lens.
Step S3: the precise motion platform drives the sample 5 to be measured to perform two-dimensional plane motion (including but not limited to grating curves, concentric circle curves, fermat curves and the like) according to a specific track, and meanwhile, the overlapping area of adjacent illumination light spots is ensured to be not less than 60%, namely airspace overlapping constraint.
Step S4: the camera 6 at a distance of 10cm from the sample 5 to be measured records the intensity information I of a series of diffracted light fields m (q), m is the number of scanning positions in the plane, and q is the frequency domain coordinate.
Step S5: intensity information I of the light field measured in step S4 m (q) is carried into a noise real-time separation laminated diffraction calculation imaging algorithm, and simultaneously, a complex amplitude function O (r) of a sample to be detected is reconstructed, and a complex amplitude function P (r, lambda) of an illumination probe 1 ) High noiseComplex amplitude function P (r, lambda) n ) Wherein r is airspace coordinate, lambda n Is a probe with different wavelengths, wherein n is more than or equal to 2. The number of noise probes is in the range of [1,5]]. In the following, n=2 is taken as an explanation, i.e. a noise probe.
Fig. 2 is a flowchart of a stacked diffraction calculation imaging method for noise real-time separation provided by an embodiment of the present invention. As shown in fig. 2, the detailed steps of step S5 are as follows:
s5.1: first for the complex amplitude function P (r, lambda) of the illuminated probe 1 ) Complex amplitude function of noise probe P (r, lambda n ) And the complex amplitude function O (r) of the sample to be tested is used for initial guess, the working wavelength of the illumination probe which is helium-neon laser is 632.8nm, and the noise probe wavelength is 543.5nm.
S5.2: according to the scanning path preset in step S4, the illumination probe P (r, lambda) with the wavelength of 632.8nm is used for 1 ) The noise probe with the wavelength of 543.5nm is formed by interaction with the sample O (r) to be detected, and the emission wave function is a complex amplitude function of the noise probe, so that the emission wave functions with different wavelengths are respectively obtained according to the formulas (1) and (2):
wherein,for the complex amplitude function of the outgoing wave of the illuminated probe, < >>As a complex amplitude function of the outgoing wave of the noise probe, O m (r) represents the complex amplitude function of the sample to be measured in the probe at the mth scanning position.
S5.3: the different wavelength exit wave functions guessed in step S5.2 aboveThe diffraction light fields with different wavelengths of the detection plane of the camera 6 are obtained by spreading the light field propagation model to the reciprocal space;
wherein phi is m (q，λ 1 ) Diffraction light field of illumination probe in reciprocal space for mth scanning position, phi m (q，λ n ) N=2 is the diffraction light field of the reciprocal space at the mth scanning position of the noise probe, and prop is the propagation mode of the light field free space (including but not limited to angular spectrum propagation, fresnel propagation, fraunhofer propagation, etc.).
S5.4: superposing the intensities of the coherent diffraction light fields with different wavelengths, which are guessed in the step S5.3; preserving the phase information of the complex amplitudes of the diffraction fields with different wavelengths guessed in the step S5.3, and replacing the intensity information of the complex amplitudes of the guessed composite diffraction field with the intensity information I of the diffraction field measured by the detector in the step S4 m (q), namely amplitude constraint of reciprocal space, to obtain updated diffraction light fields of different probes as follows:
wherein phi' m (q，λ 1 ) Updating diffraction light field after diffraction light field amplitude constraint of camera detection plane at mth scanning position for illumination probe' m (q，λ n ) And updating the diffraction light field after the diffraction light field amplitude constraint of the camera detection plane at the mth scanning position of the noise probe.
S5.5: performing a light field space back propagation model corresponding to the step S5.3 on the diffraction light field complex amplitude updating functions after the different wavelength amplitude constraint obtained in the step S5.4, and calculating the complex amplitude updating functions of the emergent waves with different wavelengths according to a formula (6) to respectively:
wherein,updating the function for the diffracted light field exit wave of the illumination probe in real space, < >>n=2 is the diffraction light field emergent wave updating function of the noise probe in real space, iprop is the back propagation model of light field free space.
S5.6: obtaining complex amplitude functions of emergent waves with different wavelengths before and after amplitude constraint according to S5.2 and S5.5, and simultaneously updating the illumination probe and the complex amplitude function of the sample to be detected by applying an updating function of a laminated diffraction iterative reconstruction algorithm, wherein the complex amplitude functions are as follows:
meanwhile, the complex amplitude updating functions of the noise probe are respectively as follows:
wherein, alpha, beta and gamma in formulas (7) - (9) belong to iterative search step length, the value is between [0,1], and the convergence speed and the convergence precision of the iterative algorithm are determined.
S5.7: and repeating the steps S5.2-S5.6 until all positions of the sample to be detected are traversed (spatial domain overlapping constraint), and replacing the diffraction light field amplitude (frequency domain amplitude constraint), wherein an iteration is calculated at the moment. Repeating the loop iteration of steps S5.2-S5.7, calculating the root mean square error of the composite diffracted light field intensities guessed and measured by S4 and S5.4 according to equation (10):
when the root mean square error is less than the set threshold, the algorithm reaches a convergence state.
S5.8: and after the algorithm is converged, outputting complex amplitude information of the illumination probe and the sample to be detected, wherein the complex amplitude information of the noise probe is the separated noise error.
Examples
FIG. 3 shows the amplitude and phase patterns of a sample to be tested and an illumination probe used in the simulation process according to an embodiment of the present invention. Amplitude information of a sample to be detected used in the simulation experiment is shown as (a), phase information is shown as (b), the size of the sample to be detected is 256×256pixel, the wavelength of an illumination probe is 632.8nm, the beam diameter is a Gaussian beam of 64×64pixel, the amplitude information is shown as (c), and the phase information is shown as (d).
Fig. 4 is a two-dimensional motion plane trace of a sample to be measured of a stacked diffraction calculation imaging system provided by an embodiment of the present invention. The precise movement table drives the sample to be measured to perform two-dimensional plane movement, and as shown in fig. 4, the movement step length in the XY direction is 16pixel, and the sample to be measured scans the 11X 11 area. Thus, the COMS camera collects 121 coherent diffraction fields in total. FIG. 5 is a graph of diffraction field intensity profiles acquired by an illumination probe and different noise signal detectors of a stacked diffraction imaging system provided in an embodiment of the present invention. As shown in (a), the diffraction field without any noise is not added, at this time, due to the interference of photon shot noise, dark current noise and readout noise in the signal acquisition process, coupled diffraction field signals with different noise levels are acquired in the coherent diffraction signal, (b) corresponds to 0.01 times (40 dB) gaussian random noise, (c) corresponds to 0.1 times (20 dB) gaussian random noise, and (d) corresponds to 10 times (-20 dB) gaussian random noise. At this time, after the camera 6 collects the coupled diffraction field signals containing different noise levels, the above proposed laminated diffraction reconstruction algorithm with real-time noise separation is adopted, and meanwhile, random guessing is used for the initial guessing illumination probe, and the sample to be tested and the noise probe are subjected to multiple loop iteration, so that the simulation experiment results are as follows:
in the first group of simulation experiments, 0.01 times (40 dB) Gaussian random noise is added to diffraction field signals, simulation comparison verification is carried out by using a traditional laminated diffraction calculation imaging ePIE algorithm and a laminated diffraction calculation imaging algorithm with real-time noise separation provided by the invention, and FIG. 6 is an amplitude pattern and a phase pattern of a sample to be tested and an illumination probe reconstructed by different laminated diffraction calculation imaging algorithms with 0.01 times (40 dB) Gaussian random noise. (a) - (d) respectively represents the amplitude and phase information of the sample to be tested and the coherence probe which are reconstructed by the ePIE algorithm after 100 iterations, and the experimental result shows that the reconstruction result of the amplitude and phase information of the sample to be tested is relatively clear, but the definition and the contrast ratio are not very high in the reconstructed image. The amplitude and phase information reconstruction result of the illumination probe is worse than the sample to be measured, obvious noise points exist in amplitude and phase reconstruction, and simulation experiment results show that the traditional ePIE algorithm can not separate noise errors, but only decompose noise energy in complex amplitude distribution of the sample to be measured and the illumination probe, and the calculation reconstruction algorithm has certain robustness to noise, has higher requirements on signal to noise ratio and is extremely sensitive to the intensity of noise. (e) - (h) respectively represents the amplitude and phase information of the sample to be detected and the illumination probe which are reconstructed by the imaging algorithm for real-time noise separation in the invention in 20 times. As shown by simulation experiment results, compared with the traditional laminated diffraction method, the amplitude and phase information of the reconstructed sample to be detected and the illumination probe are greatly improved in resolution, contrast and the like.
In the second group of simulation experiments, 0.1 times (20 dB) Gaussian random noise is added to diffraction field signals, simulation comparison verification is carried out by using a laminated diffraction calculation imaging ePIE algorithm and a laminated diffraction reconstruction algorithm with real-time noise separation provided by the invention, and FIG. 7 is an amplitude pattern and a phase pattern of a sample to be tested and an illumination probe reconstructed by different laminated diffraction calculation imaging algorithms with 0.1 times (20 dB) Gaussian random noise. (a) - (d) respectively represents the amplitude and phase information of the sample to be tested and the coherent probe reconstructed by the conventional ePIE algorithm, and the result shows that under the condition that the signal-to-noise ratio is reduced to 20dB, the conventional ePIE algorithm has the condition of non-convergence because the noise energy cannot be separated from the sample to be tested and the illumination probe. At this time, the imaging results of the noise real-time separation algorithm shown in (e) - (h) can show that the reconstruction resolution and contrast of the sample to be detected and the illumination probe which are calculated and reconstructed are the same as those of the first group of simulation implementation results, namely, under the condition of increasing the noise intensity by 10 times, the method still has stronger robustness to noise, and meanwhile, noise errors are well separated, so that the reconstruction precision of the sample to be detected and the illumination probe is not affected. The conventional laminated diffraction reconstruction algorithm loses robustness to noise under the same condition.
Further, 10 times (-20 dB) Gaussian random noise is added to the diffraction field signal in a third group of simulation experiments, the conventional laminated diffraction reconstruction ePIE algorithm cannot solve the problem of calculation imaging under the noise intensity, the simulation experiments only verify the noise intensity robustness of the noise error real-time separation algorithm, and FIG. 8 is the amplitude pattern and the phase pattern of a sample to be tested and an illumination probe reconstructed by different laminated diffraction calculation imaging algorithms with 10 times (-20 dB) Gaussian random noise provided by the embodiment of the invention. The reconstruction results of the conventional laminated diffraction ePIE algorithm shown in the amplitude and phase information (a) - (d) of the sample to be detected and the illumination probe are similar, and under the condition of 10 times (-20 dB) Gaussian random noise diffraction field signal, the method still has robustness to noise, namely, the signal to noise ratio is reduced by 1000 times or less, the method still can reach the result of the conventional laminated diffraction imaging method, but the problems of blurring and degradation still exist in the reconstructed image, probably because the signal to noise ratio is too low, the noise field energy intensity is too high, the noise probe quantity is too small, and the noise signal is not completely separated, and at the moment, part of energy is still coupled on the sample and the probe, so that the degradation of image definition and contrast is caused. Therefore, more noise probes are added to further separate out the energy of noise.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (7)
1. A method for imaging a stack of diffraction calculations with real-time separation of noise, the method being applied to a stack of diffraction calculation imaging systems, comprising:
s1, initializing an illumination probe, a sample to be tested and at least one noise probe, wherein the dimensions of the illumination probe, the sample to be tested and the noise probes are the same, and the wavelengths of all the probes are different;
s2, calculating the product of the illumination probe and the sample to be tested so as to simulate the illumination probe to act with the sample to be tested according to a scanning path to form emergent light; each noise probe is directly used as corresponding noise emergent light;
s3, inputting emergent light with different wavelengths into a light field propagation model to obtain a simulated diffraction light field with corresponding wavelengths so as to simulate the emergent light to propagate to a detector plane;
s4, superposing the simulated diffraction light field intensities of different wavelengths, replacing the amplitude of the simulated diffraction light field of each wavelength with the diffraction light field intensity measured in real time, and keeping the phase unchanged to obtain the simulated diffraction light field updated by each wavelength;
s5, inputting the diffraction light field updated by each wavelength into a light field reverse propagation model to obtain emergent light updated by each wavelength so as to simulate light to reversely propagate to a sample to be tested;
s6, updating the front and rear emergent light according to each wavelength, and simultaneously updating the sample to be tested, the illumination probe and each noise probe;
s7, repeating the steps S2-S6 until simulation of all scanning positions on the scanning path is completed;
s8, calculating root mean square error of the composite diffraction light field intensity of all the wavelengths which are simulated and measured in an iteration mode, outputting complex amplitude information of the illumination probe and the sample to be tested after the iteration when the root mean square error is smaller than a preset threshold value, otherwise, turning to the step S2.
2. The method of claim 1, wherein in step S4, the updated simulated diffraction light field for each wavelength is as follows:
wherein phi is m (q，λ i )，Φ′ m (q，λ i ) The wavelength lambda respectively representing the mth scanning position i I=1 corresponds to the illumination probe, i=2, … corresponds to the i-1 noise probe when n is used, q represents the frequency domain coordinates, and n represents the number of probes with different wavelengths; i m (q) represents the intensity of the diffracted light field measured in real time at the mth scanning position.
3. The method of claim 1, wherein in step S6, the sample to be tested, the illumination probe and each noise probe are updated simultaneously, specifically as follows:
wherein alpha, beta, gamma represent iterative search step length, and the value is 0,1]Between them; o (r), O' (r) represents the sample to be measured before and after updating, P m (r，λ 1 )，P m ' and (r, λ1) denote the illumination probes before and after updating at the mth scanning position,respectively representing the emergent light before and after the amplitude of the illumination probe at the mth scanning position is replaced, r represents real space coordinates and lambda 1 Indicating the wavelength of the illuminating probe, P m (r，λ i )，P m ′(r，λ i ) Respectively representing i-1 noise probes before and after updating at the mth scanning position lambda i Indicating the wavelength of the i 1 st noise probe,emergent light before and after replacement of the ith-1 noise probe amplitude respectively representing the mth scanning position, |representing conjugate operation of complex matrix, | max The maximum value of the amplitude of each element in the matrix is represented, and n represents the number of probes with different wavelengths.
4. The method of claim 1, wherein in step S8, the root mean square error of the iteratively simulated and measured composite diffracted light field intensities is as follows:
wherein m represents the number of scanning positions, n represents the number of probes with different wavelengths, phi m (q，λ n ) The wavelength of the mth scanning position is lambda n Complex amplitude function of simulated diffraction light field before probe updating, q represents frequency domain coordinates, I m (q) represents the intensity of the diffracted light field measured in real time at the mth scanning position.
5. The method of any one of claims 1 to 4, wherein the number of noise probes is [1,5].
6. The method of any one of claims 1 to 4, wherein the stacked diffraction imaging system is a transmissive imaging system or a reflective imaging system.
7. A stacked diffraction computed imaging apparatus with real-time noise separation, comprising: a processor and a memory;
the memory is used for storing a computer program or instructions;
the processor is configured to execute the computer program or instructions in a memory such that the method of any of claims 1 to 6 is performed.
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