Low-cost terahertz polarization imaging system

Abstract

The invention relates to the technical field of terahertz polarization imaging, in particular to a low-cost terahertz polarization imaging system which comprises the following steps: S1, selecting a light source, a filter, a lens, a spatial light modulator, a polarizer, a terahertz detection module and a data acquisition module; s2, the light source irradiates an imaging target through a lens after passing through a filter; s3, according to a compressed sensing principle, using a spatial light modulator to modulate light containing imaging target image information; s4, polarization information of the imaging target is extracted through a polaroid, the total light intensity of the modulated light is obtained through detection of a single-pixel terahertz detection module, and a single-pixel measurement value is obtained; and S5, transmitting a measured value to a computer through a data acquisition module, and carrying out image restoration by using an algorithm. According to the invention, the problem of data transmission caused by high price and large data storage amount of the existing terahertz imager is solved.

Description

Technical Field

[0001] The present invention relates to the field of terahertz polarization imaging, and in particular to a low-cost terahertz polarization imaging system. Background Art

[0002] Terahertz polarization imaging technology has important application needs and research value. In the military field, terahertz imaging technology can be applied to missile approach warning, terahertz imaging guidance, terahertz reconnaissance, etc. For example, if terahertz imaging technology is carried on satellites, it can provide early warning and tracking of ballistic missiles; in the chemical industry, it can be used for the detection of surfactants containing aromatic hydrocarbon structures, such as linoleic acid content determination, nonylphenol polyoxyethylene ether quantitative detection, and quantitative analysis of aromatic amine groups in plasma polymerization of ethylenediamine films; in the field of food safety, it can be used for the detection and analysis of spices such as cinnamyl alcohol, cinnamaldehyde and cinnamic acid in bioconversion liquid. In the field of sewage treatment, it can be used for the detection of benzene substances such as phenol, aniline and benzoic acid in water.

[0003] The manufacturing process of the terahertz array detectors used in the existing terahertz imaging systems is difficult, resulting in high overall system costs. The imaging principle used has a large amount of stored data, and its application scope is limited. Compared with traditional terahertz imagers, the detection device process of single-pixel terahertz spectral imaging technology is relatively simple and the imaging system cost is low. At present, single-pixel imaging technology has made great progress in the visible light and infrared bands and has achieved a certain degree of engineering application. In the terahertz band, there has not been much substantial progress in the research of high-performance terahertz detectors and single-pixel terahertz imaging optical systems. In addition, polarization imaging technology research is also mostly concentrated in the visible light and infrared bands. Polarization imaging can use polarization vector information to enhance the recognition ability of imaging targets, improve the imaging signal-to-noise ratio, and ultimately improve the quality of imaging.

[0004] Therefore, in response to some current problems of terahertz polarization imaging technology, the present invention proposes a low-cost single-pixel terahertz polarization imaging technology and system. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a low-cost terahertz polarization imaging system.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for realizing a low-cost terahertz polarization imaging system comprises the following steps:

[0007] S1. Select a light source, a filter, a lens, a spatial light modulator, a polarizer, a terahertz detection module, and a data acquisition module;

[0008] S2, the light source passes through the filter and is irradiated onto the imaging target by the lens;

[0009] S3, according to the principle of compressed sensing, a spatial light modulator is then used to modulate the light containing the image information of the imaging target;

[0010] S4, extracting polarization information of the imaging target through a polarizer, detecting the total light intensity of the modulated light using a single-pixel terahertz detection module, and obtaining a single-pixel measurement value;

[0011] S5. The measured values ​​are transmitted to the computer through the data acquisition module and the image is restored using the algorithm.

[0012] As a further description of the above technical solution:

[0013] The light source in step S1 is a broad spectrum light source.

[0014] As a further description of the above technical solution:

[0015] The filter in step S1 is used to perform narrow-band filtering on a wide-spectrum light source. The filter includes a plurality of filters, which can perform filtering on different narrow-band terahertz bands in a time-sharing manner to obtain spectral information.

[0016] As a further description of the above technical solution:

[0017] The polarizer in step S1 is used to obtain polarization information of an imaging target. There are multiple polarizers, and the multiple polarizers include multiple polarization directions, which are used to achieve selection of multiple polarization directions.

[0018] As a further description of the above technical solution:

[0019] The spatial light modulator in step S1 is a DMD, which is used to encode the target image information projected onto the DMD.

[0020] As a further description of the above technical solution:

[0021] The spatial light modulator coding compression process utilizes the sparsity of the signal in a certain coding domain to map the spatial signal into the coding domain for sampling. Only a small amount of measurement values ​​need to be collected to restore the target image information. The sampling frequency can be lower than the Nyquist frequency, which reduces the requirements for the sampling rate and the amount of stored data.

[0022] As a further description of the above technical solution:

[0023] The photoelectric sensor used by the terahertz detection module in step S1 is a terahertz avalanche photodiode APD.

[0024] As a further description of the above technical solution:

[0025] The mathematical model of compressed sensing in step S3 is y=ΦX, X=Ψθ, where Φ is the observation matrix, Ψ is the sparse basis matrix, and θ is the sparse vector.

[0026] As a further description of the above technical solution:

[0027] The image restoration algorithm in step S5 is to load the collected information into the spatial light modulator and control it to deflect according to the deflection pattern, and at the same time control the data acquisition module to collect the signal passing through the terahertz detector module, that is, a measurement is completed. After repeating the loading and measurement M times, the y matrix is ​​obtained, and then the image can be restored by the compressed sensing restoration algorithm.

[0028] The present invention has the following beneficial effects:

[0029] 1. Compared with the existing technology, this low-cost terahertz polarization imaging system uses the compressed sensing theory to compress and encode the image or spectral information. It can obtain the two-dimensional polarization image or spectral information of the target using only a single-pixel terahertz detector, which solves the data transmission problem caused by the high price and large amount of stored data of the existing terahertz imager, and provides a new technology for realizing terahertz polarization imaging.

[0030] 2. Compared with the existing technology, this low-cost terahertz polarization imaging system combines imaging technology with spectral technology. On the basis of detecting two-dimensional spatial information, it can also obtain the terahertz spectral information of the target, and can realize the positioning, qualitative and quantitative analysis of targets with terahertz spectral characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a structural diagram of the single-pixel terahertz polarization imaging system proposed by the present invention;

[0032] Figure 2 This is a data acquisition flow chart based on compressed sensing theory proposed by the present invention. DETAILED DESCRIPTION

[0033] Reference Figure 1-Figure 2 The present invention provides a low-cost terahertz polarization imaging system, which includes the following steps:

[0034] S1. Select a light source, a filter, a lens, a spatial light modulator, a polarizer, a terahertz detection module, and a data acquisition module;

[0035] S2, the light source passes through the filter and is irradiated onto the imaging target by the lens;

[0036] S3, according to the principle of compressed sensing, a spatial light modulator is then used to modulate the light containing the image information of the imaging target;

[0037] S4, extracting polarization information of the imaging target through a polarizer, detecting the total light intensity of the modulated light using a single-pixel terahertz detection module, and obtaining a single-pixel measurement value;

[0038] S5. The measured values ​​are transmitted to the computer through the data acquisition module and the image is restored using the algorithm.

[0039] The light source in step S1 is a wide-spectrum light source. The terahertz light source projects terahertz light of different bands onto the target object through a spectroscopic device. The spatial and spectral information carried by the reflected light of the target object is compressed by DMD encoding, and then coupled to a single-pixel terahertz detector through a terahertz optical system (including a terahertz polarization and filtering module). The electrical signal obtained after the photoelectric conversion is converted into digital and analog, and data is collected. It is decoded according to different light intensities and timing coding signals, and the image is restored and the spectral information is extracted using the graphics compression and restoration algorithm hardware and software decoding.

[0040] The filter in step S1 is used to perform narrow-band filtering on a wide-spectrum light source. The filter includes multiple filters, which can filter different narrow-band terahertz bands in time-sharing to obtain spectral information. The polarizer in step S1 is used to obtain polarization information of the imaging target. There are multiple polarizers, and the multiple polarizers include multiple polarization directions, which are used to realize the selection of multiple polarization directions.

[0041] The spatial light modulator in step S1 is a DMD, which is used to encode the target image information projected onto the DMD. The DMD model is DLP7000UV, with a resolution of 1024*768, and is suitable for the application of terahertz light sources with a wavelength of 200nm to 420nm. The spatial light modulator encoding compression process utilizes the sparsity of the signal in a certain coding domain, maps the space signal into the coding domain for sampling, and only needs to collect a small amount of measurement values ​​to restore the target image information. The sampling frequency can be lower than the Nyquist frequency, which reduces the requirements for the sampling rate and the amount of stored data.

[0042] The optoelectronic sensor used in the terahertz detection module in step S1 is a terahertz avalanche photodiode APD, which has two operating modes: linear mode and Geiger mode. In Geiger mode, it operates above the reverse bias breakdown voltage, with a gain of over 1M, single-photon sensitivity, and can be used for spectral imaging in weak scenarios. In linear mode, although the sensitivity cannot reach the single-photon level, its operating speed is relatively faster and can be used for high-speed spectral imaging under strong light conditions. This single-pixel terahertz polarization imaging technology uses a terahertz single-pixel detector without spatial resolution ability as a sensing device to convert optical signals into electrical signals, and then obtains information about the imaging target. Compressed sensing is its theoretical basis. If a signal is compressible or can be sparsely represented in a certain frequency domain, a matrix uncorrelated with the frequency domain sparse basis can be used to measure the signal, projecting the signal from a high-dimensional space to a low-dimensional space. The unknown element is the high-dimensional space signal, and the measurement value is the low-dimensional space projection information.

[0043] The mathematical model of compressed sensing in step S3 is: y = ΦX. The sparsity or compressibility of the signal is an important prerequisite for compressed sensing. The real signals existing in nature are generally not absolutely sparse, but can be approximately sparse in a certain transform domain, that is, compressible signals. For example, this transform domain can be discrete cosine transform, wavelet transform, etc. Image reconstruction is to first obtain the y matrix from the measurement. Then, since the general image signal X itself is not sparse, it needs to be sparsely represented on a certain sparse basis, that is, X = Ψθ, where Ψ is the known sparse basis matrix and θ is the sparse vector (only K of θ are non-zero values (K << N)), then the matrix A = ΦΨ can be obtained; θ can be represented by the measured y and the matrix A; due to the known sparse basis matrix Ψ, another mathematical prerequisite for image reconstruction using compressed sensing is that the observation matrix Φ and the sparse basis matrix Ψ are uncorrelated. Since the known sparse basis matrix Ψ is known, then the image X can be reconstructed.

[0044] The image restoration algorithm in step S5 is to first load a row of the deflection pattern of the DMD, that is, the generated sensing matrix Φ, onto the DMD and control it to deflect according to the deflection pattern. At the same time, control the data acquisition module to collect the signals passing through the terahertz detector module, that is, complete one measurement. After repeating the loading and measurement M times (the number of rows of the sensing matrix Φ), the y matrix is obtained, and then the image can be restored through the compressed sensing restoration algorithm.

[0045] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, it is still possible for those skilled in the art to modify the technical solutions described in the aforementioned embodiments or to make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A low-cost terahertz polarization imaging system, characterized by: The following steps are involved: S1. Select a light source, a filter, a lens, a spatial light modulator, a polarizer, a terahertz detection module, and a data acquisition module; S2, the light source passes through the filter and is irradiated onto the imaging target by the lens; S3, according to the principle of compressed sensing, a spatial light modulator is then used to modulate the light containing the image information of the imaging target; S4, extracting polarization information of the imaging target through a polarizer, detecting the total light intensity of the modulated light using a single-pixel terahertz detection module, and obtaining a single-pixel measurement value; S5. The measured values ​​are transmitted to the computer through the data acquisition module and the image is restored using the algorithm.

2. A low-cost terahertz polarization imaging system according to claim 1, characterized in that: The light source in step S1 is a broad spectrum light source.

3. The low-cost terahertz polarization imaging system according to claim 1, characterized in that: The filter in step S1 is used to perform narrow-band filtering on a wide-spectrum light source. The filter includes a plurality of filters, which can perform filtering on different narrow-band terahertz bands in a time-sharing manner to obtain spectral information.

4. The low-cost terahertz polarization imaging system according to claim 1, characterized in that: The polarizer in step S1 is used to obtain polarization information of an imaging target. There are multiple polarizers, and the multiple polarizers include multiple polarization directions, which are used to achieve selection of multiple polarization directions.

5. The low-cost terahertz polarization imaging system according to claim 1, characterized in that: The spatial light modulator in step S1 is a DMD, which is used to encode the target image information projected onto the DMD.

6. The low-cost terahertz polarization imaging system according to claim 5, characterized in that: The spatial light modulator coding compression process utilizes the sparsity of the signal in a certain coding domain to map the spatial signal into the coding domain for sampling. Only a small amount of measurement values ​​need to be collected to restore the target image information. The sampling frequency can be lower than the Nyquist frequency, which reduces the requirements for the sampling rate and the amount of stored data.

7. The low-cost terahertz polarization imaging system according to claim 1, characterized in that: The photoelectric sensor used by the terahertz detection module in step S1 is a terahertz avalanche photodiode APD.

8. The low-cost terahertz polarization imaging system according to claim 1, characterized in that: The mathematical model of compressed sensing in step S3 is y=ΦX, X=Ψθ, where Φ is the observation matrix, Ψ is the sparse basis matrix, and θ is the sparse vector.

9. The low-cost terahertz polarization imaging system according to claim 1, characterized in that: The image restoration algorithm in step S5 is to load the collected information into the spatial light modulator and control it to deflect according to the deflection pattern, and at the same time control the data acquisition module to collect the signal passing through the terahertz detector module, that is, a measurement is completed. After repeating the loading and measurement M times, the y matrix is ​​obtained, and then the image can be restored by the compressed sensing restoration algorithm.

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