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Three-wavelength phase unpacking method, system and device based on deep learning and medium

A deep learning, three-wavelength technology, applied in neural learning methods, optical devices, measurement devices, etc., can solve the problems of complex experimental systems and large errors, and achieve the effects of improving measurement accuracy, solving phase noise amplification, and improving range.

Pending Publication Date: 2021-12-03
DONGGUAN UNIV OF TECH
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Problems solved by technology

[0007] The present invention aims to overcome at least one defect (deficiency) of the above-mentioned prior art, and provides a three-wavelength phase unpacking method, system, equipment and medium based on deep learning, which are used to solve the problem of experimental phase unpacking in the process of sample phase unpacking. Problems with complex systems and large errors

Method used

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  • Three-wavelength phase unpacking method, system and device based on deep learning and medium
  • Three-wavelength phase unpacking method, system and device based on deep learning and medium
  • Three-wavelength phase unpacking method, system and device based on deep learning and medium

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Embodiment 1

[0064] Such as figure 1 As shown, this implementation provides a three-wavelength phase unpacking method based on deep learning, which specifically includes the following steps:

[0065] S1: Place the sample at wavelength λ 1 The following interferogram is input into the deep learning neural network to obtain the sample at wavelength λ 2 and lambda 3 Under the interferogram, the deep learning neural network is used to learn the relationship between the three wavelength interferograms from the sample at one wavelength λ 1 The interferogram of the sample is obtained simultaneously at two other different wavelengths λ 2 and lambda 3 Interferogram below;

[0066] S2: According to the sample at wavelength λ 1 The interferogram below, and the resulting sample at wavelength λ 2 and lambda 3 Under the interferogram, calculate the sample at wavelength λ 1 , lambda 2 and lambda 3 The wrapped phase distribution under ;

[0067] S3: Calculate the wavelength λ of the sample acc...

Embodiment 2

[0112] Such as Figure 4 As shown, this embodiment provides a three-wavelength phase unpacking system based on deep learning, which specifically includes:

[0113] The interferogram acquisition module 100 is used to convert the sample at the wavelength λ 1 The following interferogram is input into the deep learning neural network to obtain the sample at wavelength λ 2 and lambda 3 Under the interferogram, the deep learning neural network is used to learn the relationship between the three wavelength interferograms from one wavelength λ 1 The interferogram of the other two different wavelengths λ is obtained at the same time 2 and lambda 3 the interferogram;

[0114] Wrapped phase calculation module 200, for according to the sample at wavelength λ 1 The interferogram below, and the resulting sample at wavelength λ 2 and lambda 3 Under the interferogram, calculate the sample at wavelength λ 1 , lambda 2 and lambda 3 The wrapped phase distribution under ;

[0115] The...

Embodiment 3

[0159] This embodiment provides a computer device, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, the three-wavelength phase unpacking method based on deep learning in the above-mentioned embodiment 1 is implemented. step.

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Abstract

The invention relates to the field of optical interference measurement or digital holographic measurement, in particular to a three-wavelength phase unpacking method, system and device based on deep learning and a medium. The method comprises the steps of inputting an interferogram of a sample under a wavelength lambda1 into a deep learning neural network to obtain an interferogram of the sample under wavelengths lambda2 and lambda3, the deep learning neural network being used for learning a relationship among the interferograms of three wavelengths, and simultaneously obtaining the interferograms of the sample under the other two different wavelengths lambda2 and lambda3 from the interferogram of the sample under the wavelength lambda1; calculating wrapped phase distribution of the sample under the wavelengths lambda 1, lambda 2 and lambda 3; and calculating the unwrapped phase of the sample under the wavelengths of lambda 1, lambda 2 and lambda 3 according to the calculated wrapped phase distribution. The interference measurement device is greatly simplified, the measurement error is reduced, the phase measurement range is effectively improved, the problem of phase noise amplification is solved, and the measurement precision is improved.

Description

technical field [0001] The present invention relates to the field of optical interferometry or digital holography, and more specifically, to a three-wavelength phase unwrapping method, system, device and medium based on deep learning. Background technique [0002] Optical interferometry is a technology that uses light waves as information carriers to obtain phase modulation information of objects through the principle of light interference or diffraction. It realizes the measurement of the phase information of the object by recording and analyzing the interferogram with the phase information of the object to be measured. It has the advantages of full-field, fast, non-contact, and high precision. It has been widely used in biological microscopic imaging and high-precision quantification. measuring. Then, the optical interferometric phase measurement technique uses the basic principle of trigonometric functions to achieve phase reconstruction, and the extracted phase is distr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G01B9/02
CPCG06N3/08G01B9/02G06N3/045
Inventor 章勤男凌东雄李娇声刘竞博魏东山
Owner DONGGUAN UNIV OF TECH
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