Single-photon multi-wavelength imaging system and method based on physical driving model

Abstract

The invention provides a single-photon multi-wavelength imaging system and method based on a physical driving model, and belongs to the technical field of single-pixel multi-wavelength imaging. The problems that an existing single-photon multi-wavelength imaging scheme is prone to being influenced by noise and poor in imaging quality in an extreme environment are solved. Comprising a multi-wavelength modulation illumination module, a spatial modulation coding module and a detection imaging module. The multi-wavelength modulation illumination module uses signal light with different modulation repetition frequencies to illuminate a color target object and scatter the light to the spatial modulation coding module, the spatial modulation coding module performs spatial coding on the color target object and transmits the coded light to the detection imaging module, and the detection imaging module captures modulation signal light and transmits the modulation signal light to the computer. A physical driving model program is written into the computer in advance, a physical driving model comprises a measured value denoising module and a physical driving image reconstruction module, and finally the measured value denoising module and the physical driving image reconstruction module are combined into a high-quality color target object reconstruction image; the method is applied to photon imaging.

Description

Technical Field

[0001] The invention provides a single-photon multi-wavelength imaging system and method based on a physical driving model, belonging to the technical field of single-pixel multi-wavelength imaging. Background Art

[0002] Image information plays a vital role in scientific research, industrial applications, medical diagnosis, national defense and military. At present, the main ways to obtain high-quality image information include optical cameras, infrared detection and single-pixel imaging. Among them, single-pixel imaging technology uses only one detector to obtain the heat or other information of the target through time coding or space coding. This imaging method has low cost and low power consumption, and is suitable for imaging targets in extreme environments. Single-pixel multi-wavelength imaging technology uses three basic color channels of red, green and blue to record images. Each channel corresponds to a monochrome image, and finally a color target reconstructed image is generated by combining these three channels.

[0003] Single-pixel multi-wavelength imaging systems are mainly divided into two types: time-division multiplexing systems and frequency-division multiplexing systems. The time-division multiplexing system modulates light of different wavelengths into different time periods to illuminate the target, and then detects the echo signals of each time period. However, this system has high requirements on the pulse width and time stability of the light source, and in practical applications, images at different depths may interfere with each other, which limits its scope of application. In contrast, the frequency-division multiplexing system marks light signals of different wavelengths as different repetition frequencies through intensity modulation, and extracts these echo signals in the frequency domain using fast Fourier transform. Traditional single-pixel multi-wavelength imaging systems use photodetectors for data acquisition, resulting in low system sensitivity and poor imaging in low-light environments. Single-photon multi-wavelength imaging systems use single-photon detectors to collect multi-wavelength information, with high sensitivity and excellent low-light detection capabilities. However, existing single-photon multi-wavelength imaging technology still faces two major challenges in practical applications. First, there is a large amount of fluctuation noise. Due to the uncertainty and statistical fluctuations of the photons themselves, single-photon detectors will experience fluctuations when measuring photons multiple times. In extreme environments, this fluctuation noise will have a significant impact on image quality and limit the performance of the imaging system. Second, there is a certain amount of background noise. The interference signal from non-target light sources in the environment is mixed with the target light signal and detected simultaneously, making it difficult to extract the weak target signal. Therefore, it is necessary to design a single-photon multi-wavelength imaging system based on a physical driving model to effectively suppress fluctuation noise and background noise at the data source. Summary of the invention

[0004] In order to solve the problem that the existing single-photon multi-wavelength imaging scheme is susceptible to noise and has poor imaging quality in extreme environments, the present invention proposes a single-photon multi-wavelength imaging system and method based on a physical drive model. Compared with traditional denoising methods, the physical drive model proposed in the present invention does not rely on a large number of sample learning. Under the condition that only 30 photons per pixel are required on average, the peak signal-to-noise ratio of the image can be significantly improved by more than 10dB, and it shows excellent robustness in various application scenarios.

[0005] The technical solution adopted by the present invention is: a single-photon multi-wavelength imaging system based on a physical driving model, including a multi-wavelength modulation illumination module, a spatial modulation coding module and a detection imaging module; the multi-wavelength modulation illumination module uses signal light with different modulation repetition frequencies to illuminate a color target and scatter it to the spatial modulation coding module, the spatial modulation coding module spatially encodes the color target and transmits it to the detection imaging module, the detection imaging module captures the modulated signal light and transmits it to a computer, a physical driving model program is pre-written in the computer, the physical driving model includes a measurement value denoising module and a physical driving image reconstruction module, in the measurement value denoising module, a one-dimensional measurement value is denoised by a measurement value denoising network; the physical driving image reconstruction module restores the denoised one-dimensional photon counting sequence into a two-dimensional target image of three channels of red, green and blue, and finally merges them into a high-quality reconstructed image of the color target.

[0006] The multi-wavelength modulation illumination module comprises a first wavelength laser, a beam splitter, a second wavelength laser, a third wavelength laser, an attenuation plate and a beam expander, modulates the three wavelength lasers to different repetition frequencies, and combines the beams into one beam by the beam splitter, and irradiates the color target after the light intensity is regulated by the attenuation plate and the beam is collimated and expanded by the beam expander;

[0007] The first wavelength laser, the second wavelength laser, and the third wavelength laser are used to generate red, green, and blue visible light, respectively, and the three lasers have different corresponding modulation frequencies;

[0008] There are two beam splitters, the first beam splitter is arranged between the first wavelength laser and the second wavelength laser, and combines the two beams of light into one beam of light, and the second beam splitter is arranged between the third wavelength laser and the combined beam of the first wavelength and the second wavelength, and combines the third wavelength and the first combined beam of light into one beam of light.

[0009] The spatial modulation coding module includes a first lens and a digital micromirror device, and the scattered light from the object is transmitted to the digital micromirror device through the first lens; the digital micromirror device is pre-loaded with a set of Hada code masks with a spatial resolution of 256×256 to perform spatial coding modulation on the color target;

[0010] The external trigger signal of the digital micromirror device is recorded by a time-correlated single-photon counter.

[0011] The detection imaging module includes a second lens, a single-photon detector and a time-correlated single-photon counter; the second lens converges the coded signal reflected by the digital micromirror device to the single-photon detector, and the response signal of the single-photon detector is recorded by the time-correlated single-photon counter and transmitted to a computer.

[0012] A single-photon multi-wavelength imaging method based on a physical driving model, using a single-photon multi-wavelength imaging system based on a physical driving model, comprises the following steps:

[0013] Step 1: Multi-wavelength modulated signal light source illuminates the color target and spatially codes the modulated signal;

[0014] Step 2: Single-photon multi-wavelength modulation signal detection;

[0015] Step 3: Use the measurement denoising network to remove the noise in the one-dimensional measurement value:

[0016] Step 3.1: Preprocess the raw data obtained by the computer and calculate the photon count value corresponding to each modulation mask:

[0017]

[0018] In the formula, is the photon count value corresponding to the nth mask, is the nth Hadamard mask, T (x，y) Indicates the target object;

[0019] Step 3.2: De-noise the 1D photon count values ​​using the trained measurements:

[0020]

[0021] In the formula, is the photon count value containing noise, Cp is the photon count value after denoising, and D θ Denoising a network for measurements embedded with occlusion attention;

[0022] Step 4: Use the physical driven image reconstruction module to iteratively reconstruct the two-dimensional image of the color target:

[0023] T * =R θ (DGI(C p ));

[0024] The restrictions are:

[0025] Where, T *Represents the reconstructed image, R θ is the U-net neural network, DGI is the differential ghost imaging reconstruction algorithm, C p is the photon count value after denoising, P represents the Hadamard mask, and T represents the non-optimal reconstructed image in the iterative process.

[0026] Step 1 specifically includes:

[0027] Step 1.1: modulate the repetition frequency of the first wavelength laser, the repetition frequency of the second wavelength laser, and the repetition frequency of the third wavelength laser. The three different wavelength lasers are modulated by repetition frequency and combined into one beam by a beam splitter, and then collimated and expanded by a beam expander to irradiate a color target object;

[0028] Step 1.2: Use the first lens to collect the scattered signal of the color target and image it into the modulation area of ​​the digital micromirror device. Load a set of Hadamard masks with a spatial resolution of 256×256 on the digital micromirror device to perform spatial coding modulation on the color target.

[0029] Step 2 specifically includes:

[0030] Step 2.1: Use a second lens to focus the reflected light modulated by the digital micromirror device onto the single photon detector;

[0031] Step 2.2: Use a time-correlated single photon counter to record the response data of the single photon detector and transmit it to a computer.

[0032] The beneficial effects of the present invention compared with the prior art are as follows:

[0033] 1. The present invention designs a single-photon multi-wavelength imaging system based on a physical driving model, which directly processes the data collected by the imaging front end. Compared with using a denoising algorithm to improve image quality at the imaging back end, the present invention can significantly improve the image peak signal-to-noise ratio by more than 10dB under the condition that only 30 photons per pixel are required on average.

[0034] 2. The present invention uses the denoised light intensity value as the constraint condition of the physical driving model. The model only requires a small amount of prior knowledge to be applicable to any imaging scenario, making the system extremely robust and suitable for application scenarios where the target object changes rapidly. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The present invention will be further described below in conjunction with the accompanying drawings:

[0036] Figure 1 It is a structural schematic diagram of the system of the present invention;

[0037] Figure 2 This is a schematic diagram of the measurement value denoising network structure of the present invention;

[0038] Figure 3 This is a schematic diagram of the physical drive image reconstruction network structure of the present invention;

[0039] Figure 4 Comparison of imaging results after denoising with different schemes;

[0040] Figure 5 The image quality histogram after denoising with different schemes;

[0041] Figure 6 The results of the single-photon multi-wavelength imaging experiment conducted to verify the effectiveness of the present invention;

[0042] In the figure: 101 is a 450nm wavelength laser, 102 is a beam splitter, 103 is a 520nm wavelength laser, 104 is a 635nm wavelength laser, 105 is an attenuator, 106 is a beam expander, 107 is a color target, 1081 is a first lens, 1082 is a second lens, 109 is a digital micromirror device, 110 is a single photon detector, 111 is a time-correlated single photon counter, and 112 is a computer. DETAILED DESCRIPTION

[0043] like Figures 1 to 6 As shown, the present invention provides a single-photon multi-wavelength imaging system based on a physical-driven model, including a multi-wavelength modulated illumination module, a spatial modulation coding module and a detection imaging module; the multi-wavelength modulated illumination module uses signal light of different modulation repetition frequencies to illuminate a color target and scatter it to the spatial modulation coding module, the spatial modulation coding module spatially encodes the color target and transmits it to the detection imaging module, the detection imaging module captures the modulated signal light and transmits it to a computer, a physical-driven model program is pre-written in the computer, including a measurement value denoising module and a physical-driven image reconstruction module, in which a one-dimensional measurement value is denoised by a measurement value denoising network; the physical-driven image reconstruction module restores the denoised one-dimensional photon counting sequence to a two-dimensional target image of three channels of red, green and blue, and finally merges them into a high-quality reconstructed image of the color target.

[0044] The multi-wavelength modulated lighting module includes a 450nm wavelength laser 101, a beam splitter 102, a 520nm wavelength laser 103, a 635nm wavelength laser 104, an attenuation plate 105 and a beam expander 106, and the color target 107 is illuminated by the above devices; the specific process is: the three wavelength lasers are modulated to different repetition frequencies, and the beams are combined into a beam of light by the beam splitter 102, and the color target 107 is illuminated after the light intensity is adjusted by the attenuation plate 105 and the beam is collimated and expanded by the beam expander 106. More specifically, two beam splitters 102 are provided. The first beam splitter 102 is provided between the 450nm wavelength laser 101 and the 520nm wavelength laser 103, and combines the light of 450mn wavelength and 520nm wavelength into one beam of light. The second beam splitter 102 is provided between the 635nm wavelength laser 104 and the combined light of 450mn wavelength and 520nm wavelength, and combines the 635nm wavelength and the first combined light into one beam of light.

[0045] The spatial modulation coding module includes a first lens 1081 and a digital micromirror device 109, which are used to spatially encode the optical image of the color target; the scattered light from the object is transmitted to the digital micromirror device 109 through the first lens 108; the digital micromirror device 109 is pre-loaded with a set of Hada code masks with a spatial resolution of 256×256 to perform spatial coding modulation on the color target 107, and its external trigger signal is recorded by the time-correlated single photon counter 111.

[0046] The detection imaging module uses the second lens 1082, the single-photon detector 110, the time-correlated single-photon counter 111, and the computer 112 to collect extremely weak signals; the second lens 1082 converges the coded signal reflected by the digital micromirror device 109 to the single-photon detector 110, and the response signal of the single-photon detector 110 is recorded by the time-correlated single-photon counter 111 and transmitted to the computer 112.

[0047] Based on the above system, the present invention proposes a single-photon multi-wavelength imaging method based on a physical driving model, comprising the following steps:

[0048] Step 1: Multi-wavelength modulated signal light source illuminates the color target and spatially codes the modulated signal, such as Figure 1 As shown:

[0049] Step 1.1: modulate the repetition frequency of the 450nm wavelength laser 101 to 200kHz, the repetition frequency of the 520nm wavelength laser 103 to 230kHz, and the repetition frequency of the 635nm wavelength laser 104 to 260kHz. The three lasers with different wavelengths are modulated in repetition frequency and combined into one beam by a beam splitter 102. After collimation and expansion by a beam expander 106, the beam is irradiated to a color target 107.

[0050] Step 1.2: Use the first lens 1081 to collect the scattered signal of the color target 107 and image it into the modulation area of ​​the digital micromirror device 109. Load a set of Hadamard masks with a spatial resolution of 256×256 on the digital micromirror device 109 to perform spatial coding modulation on the color target 107. Its external trigger signal is collected by the time-correlated single photon counter 111.

[0051] Step 2: Single-photon multi-wavelength modulation signal detection:

[0052] Step 2.1: Use the second lens 1082 to focus the reflected light modulated by the digital micromirror device 109 onto the single photon detector 110;

[0053] Step 2.2: Use the time-correlated single photon counter 111 to record the response data of the single photon detector 110 and transmit it to the computer 112 .

[0054] Step 3: Use the measurement denoising network (such as Figure 2 ) to remove the noise present in the one-dimensional measurement value:

[0055] Step 3.1: Pre-process the raw data acquired by the computer 112, and calculate the photon count value corresponding to each modulation mask:

[0056]

[0057] In the formula, is the photon count value corresponding to the nth mask, is the nth Hadamard mask, T (x，y) Indicates the target object;

[0058] Step 3.2: De-noise the 1D photon count values ​​using the trained measurements:

[0059]

[0060] In the formula, is the photon count value including noise, C p is the photon count value after denoising, D θ Denoising networks for measurements embedded with occluded attention.

[0061] Step 4: Use the physical drive image reconstruction module (such as Figure 3 As shown in the figure, iteratively reconstructs the two-dimensional image of the color target:

[0062] T * =R θ (DGI(C p ));

[0063] The restrictions are:

[0064] Where, T * Represents the reconstructed image, R θ is the U-net neural network, DGI is the differential ghost imaging reconstruction algorithm, C p is the photon count value after denoising, P represents the Hadamard mask, and T represents the non-optimal reconstructed image in the iterative process.

[0065] The effectiveness of the present invention is verified by experiments below:

[0066] To verify the feasibility of the physical driving model of the present invention, the target object is imaged under the conditions of a sampling time of 2 ms, a photon counting rate of 1 Mcps, a duty cycle of 10%, and a compression degree of 0.02, and denoising is performed using the physical driving model. Figure 4 A comparison chart of the denoising results of the target object reconstructed image using different denoising algorithms. Figure 5 Peak signal-to-noise ratio statistics for different denoising algorithms for reconstructing the target image. The color leaf was imaged with a sampling time of 1.5ms, a photon count rate of 1Mcps, a duty cycle of 10%, and a compression of 0.02, and denoised using a physically driven model. Figure 6 This is the experimental result of single-photon multi-wavelength imaging of colored leaves.

[0067] By analyzing Figure 4-6 It can be concluded that:

[0068] 1) If Figure 4 and Figure 5 As shown, the reconstructed image contains a lot of noise, which seriously affects the image quality. After using different denoising schemes for processing and calculating its peak signal-to-noise ratio, the results show that compared with other denoising algorithms, the peak signal-to-noise ratio based on the physical-driven model of the present invention is improved by more than 10dB on average. Specifically, the peak signal-to-noise ratio of the "moon" image processed by median filtering is 19.34dB, the result of sparse three-dimensional transform domain collaborative filtering is 22.94dB, and the peak signal-to-noise ratio of the image denoised using the physical-driven model of the present invention reaches 29.52dB. Compared with median filtering and sparse three-dimensional transform domain collaborative filtering, the denoising results of the physical-driven model proposed in the present invention are improved by 10.18dB and 6.58dB, respectively, which fully verifies the effective noise suppression ability of the present invention during the imaging process.

[0069] 2) If Figure 6As shown, the color leaf reconstruction images of the red, green and blue channels are denoised using median filtering, sparse three-dimensional transform domain collaborative filtering image denoising and the physical driving model of the present invention, and then synthesized into the final color leaf reconstruction image. It can be concluded that the present invention effectively suppresses various noises existing in single-photon multi-wavelength imaging through the technical solution of physical model-driven neural network combined with measurement value denoising network, and the effect is significantly better than other common denoising algorithms, which significantly improves the image quality.

[0070] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A single-photon multi-wavelength imaging system based on a physical driving model, characterized in that: The invention comprises a multi-wavelength modulation illumination module, a spatial modulation coding module and a detection imaging module; the multi-wavelength modulation illumination module uses signal light of different modulation repetition frequencies to illuminate a color target and scatters the signal light to the spatial modulation coding module; the spatial modulation coding module performs spatial encoding on the color target and transmits the signal light to the detection imaging module; the detection imaging module captures the modulated signal light and transmits the signal light to a computer (112); a physical driving model program is pre-written in the computer (112); the physical driving model comprises a measurement value denoising module and a physical driving image reconstruction module; in the measurement value denoising module, one-dimensional measurement values ​​are denoised by a measurement value denoising network; the physical driving image reconstruction module restores the denoised one-dimensional photon counting sequence into two-dimensional target images of three channels of red, green and blue, and finally merges them into a high-quality reconstructed image of the color target.

2. The single-photon multi-wavelength imaging system based on a physical driving model according to claim 1, characterized in that: The multi-wavelength modulation illumination module comprises a first wavelength laser, a beam splitter (102), a second wavelength laser, a third wavelength laser, an attenuation plate (105) and a beam expander (106), modulates the three wavelength lasers to different repetition frequencies, and combines the three wavelength lasers into a beam of light by using the beam splitter (102), and then irradiates a color target object (107) after the light intensity is regulated by the attenuation plate (105) and the beam is collimated and expanded by the beam expander (106); The first wavelength laser, the second wavelength laser, and the third wavelength laser are used to generate red, green, and blue visible light, respectively, and the three lasers have different corresponding modulation frequencies; Two beam splitters (102) are provided, the first beam splitter (102) is provided between the first wavelength laser and the second wavelength laser, and combines the two beams of light into one beam of light, and the second beam splitter (102) is provided between the third wavelength laser and the combined beam of the first wavelength and the second wavelength, and combines the third wavelength and the first combined beam of light into one beam of light.

3. The single-photon multi-wavelength imaging system based on a physical driving model according to claim 2, characterized in that: The spatial modulation coding module comprises a first lens (1081) and a digital micromirror device (109); scattered light from an object is transmitted to the digital micromirror device (109) through the first lens (1081); the digital micromirror device (109) is preloaded with a set of Hadamard masks with a spatial resolution of 256×256 to perform spatial coding modulation on a color target object (107).

4. The single-photon multi-wavelength imaging system based on a physical driving model according to claim 3, characterized in that: The detection imaging module comprises a second lens (1082), a single photon detector (110) and a time-correlated single photon counter (111); the second lens (1082) converges the coded signal reflected by the digital micromirror device (109) to the single photon detector (110), and the response signal of the single photon detector (110) is recorded by the time-correlated single photon counter (111) and transmitted to the computer (112); The external trigger signal of the digital micromirror device (109) is recorded by a time-correlated single photon counter (111).

5. A single-photon multi-wavelength imaging method based on a physical driving model, characterized in that: The single-photon multi-wavelength imaging system based on the physical driving model as described in any one of claims 1 to 4 comprises the following steps: Step 1: Multi-wavelength modulated signal light source illuminates the color target and spatially codes the modulated signal; Step 2: Single-photon multi-wavelength modulation signal detection; Step 3: Use the measurement denoising network to remove the noise in the one-dimensional measurement value: Step 3.1: Pre-process the raw data acquired by the computer (112) and calculate the photon count value corresponding to each modulation mask: In the formula, is the photon count value corresponding to the nth mask, is the nth Hadamard mask, T (x，y) Indicates the target object; Step 3.2: De-noise the 1D photon count values ​​using the trained measurements: In the formula, is the photon count value including noise, C p is the photon count value after denoising, D θ Denoising a network for measurements embedded with occlusion attention; Step 4: Use the physical driven image reconstruction module to iteratively reconstruct the two-dimensional image of the color target: T * =R θ (DGI(C p )); The restrictions are: Where, T * Represents the reconstructed image, R θ is the U-net neural network, DGI is the differential ghost imaging reconstruction algorithm, C p is the photon count value after denoising, P represents the Hadamard mask, and T represents the non-optimal reconstructed image in the iterative process.

6. The single-photon multi-wavelength imaging method based on a physical driving model according to claim 5, characterized in that: Step 1 specifically includes: Step 1.1: modulating the repetition frequency of the first wavelength laser, the repetition frequency of the second wavelength laser, and the repetition frequency of the third wavelength laser. The three different wavelength lasers are modulated in repetition frequency and combined into one beam of light by using a beam splitter (102). The beam is collimated and expanded by a beam expander (106) and then irradiates a color target (107). Step 1.2: Use the first lens (1081) to collect the scattered signal of the color target (107) and image it into the modulation area of ​​the digital micromirror device (109), and load a set of Hadamard masks with a spatial resolution of 256×256 on the digital micromirror device (109) to perform spatial coding modulation on the color target (107).

7. The single-photon multi-wavelength imaging method based on a physical driving model according to claim 5, characterized in that: Step 2 specifically includes: Step 2.1: using a second lens (1082) to focus the reflected light modulated by the digital micromirror device (109) onto the single photon detector (110); Step 2.2: Use a time-correlated single photon counter (iii) to record the response data of the single photon detector (110) and transmit it to a computer (112).

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