A photon-level single-pixel optical communication system and method based on frequency domain information extraction

Abstract

The application provides a photon-level single-pixel optical communication system and method based on frequency domain information extraction, and belongs to the technical field of optical communication; solves the problems of signal modulation, encryption and the like faced by the existing single-photon compressed sensing imaging technology in underwater optical communication application; comprises a signal encryption and emission module, a signal transmission module and a signal receiving and decoding module; the signal encryption and emission module combines two different image information code patterns obtained by encrypting two different repetitive frequency pulse lights into one signal light, transmits the signal light to the signal receiving and decoding module through the signal transmission module, encodes and modulates the image by loading Hadamard mask, records the photon statistical sequence by using single-photon detection technology, reconstructs the image information code by combining the frequency domain information extraction technology and Hadamard mask, and identifies and decodes the information encrypted by the image information code by using a machine vision system; the application is applied to optical communication.

Description

Technical Field

[0001] This invention provides a photon-level single-pixel optical communication system and method based on frequency domain information extraction, belonging to the field of optical communication technology. Background Technology

[0002] With the rapid development of marine resource development, marine environmental monitoring, marine military applications, and underwater robotics, the demand for efficient underwater communication technologies is increasing. Traditional underwater communication technologies mainly rely on underwater acoustic communication and radio communication. Underwater acoustic communication has the advantages of long-distance transmission and high stability, but suffers from low bandwidth, low data rate, and high latency. Radio communication can provide high bandwidth and real-time communication over short distances, but it suffers from rapid attenuation in water, high energy consumption, and is greatly affected by the environment. Underwater free-optical communication, as an emerging technology, excels in providing high bandwidth, low latency, and resistance to electromagnetic interference, making it suitable for applications such as real-time data transmission, high-resolution imaging, and highly secure communication. However, its limited transmission distance, strong environmental dependence, and high line-of-sight requirements restrict its application scope. To fully leverage the advantages of underwater optical communication, it is necessary to improve the sensitivity and efficiency of detection equipment and enhance environmental adaptability to promote the widespread application and industrialization of underwater optical communication technology.

[0003] Single-pixel imaging technology, by capturing signals using a highly sensitive single-pixel detector and reconstructing images or information through computation, enables high signal-to-noise ratio detection under low photon number conditions, providing a new approach for efficient and reliable optical communication in complex underwater environments. In recent years, single-pixel imaging has made significant progress in underwater free-light communication. By employing high-performance single-photon detectors and compressed sensing algorithms, high-quality signals can be reconstructed under extremely low light intensity conditions, overcoming the strong absorption and scattering effects in underwater environments. The application of compressed sensing theory in single-pixel imaging allows for the reconstruction of complete signals with only a small amount of measurement data, significantly improving the data transmission efficiency of communication systems. However, existing single-photon compressed sensing imaging technologies still face three major challenges in practical applications of underwater optical communication. First, they typically require complex signal modulation and demodulation processes, and the efficiency of information transmission depends on the transmission protocol and equipment performance. Second, they require long signal processing times and have slow interactive responses. Third, although encryption techniques can be used, their implementation and management are complex, requiring additional security protocols and encryption devices. As a novel communication method, image information codes utilize the visual characteristics and data storage capabilities of images to embed information into them, and are widely used in modern communication, data storage, security authentication, and image processing. Their efficiency, convenience, large data capacity, and high fault tolerance make them an important tool for information transmission and management. Therefore, it is necessary to design a photon-level underwater single-pixel free-light communication system based on image information codes to address the aforementioned technical challenges. Summary of the Invention

[0004] To address the challenges of existing single-photon compressed sensing imaging technology in underwater optical communication applications, such as complex signal modulation and demodulation processes, slow interactive response, and sophisticated encryption methods, this invention proposes a photon-level single-pixel optical communication system and method based on frequency domain information extraction. This system applies frequency domain information extraction technology to photon-level single-pixel imaging, significantly improving image quality. By using image information codes to encrypt information instead of traditional modulation and demodulation techniques, it effectively enhances the information transmission efficiency, ease of use, security, and versatility of underwater optical communication applications.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: a photon-level single-pixel optical communication system based on frequency domain information extraction, including a signal encryption and transmission module, a signal transmission module, and a signal receiving and decoding module. The signal encryption and transmission module encrypts two pulses of light with different repetition frequencies into different image information code patterns and then merges them into a single signal light. The signal light is transmitted to the signal receiving and decoding module through the signal transmission module. The signal receiving and decoding module encodes and modulates the image by loading a Hadamard mask, records the photon statistical sequence within the statistical time of each Hadamard mask using single-photon detection technology, and reconstructs the image information code by combining frequency domain information extraction technology and Hadamard mask. The encrypted information of the image information code is identified and decoded by a machine vision system.

[0006] The signal encryption and transmission module includes a first pulse light, a second pulse light, and a first computer with different repetition frequencies. The first pulse light is expanded by a first beam expander and then reflected by a first reflector before shining on the working area of ​​the first digital micromirror device. The second pulse light is expanded by a second beam expander and then reflected by a second reflector before shining on the working area of ​​the second digital micromirror device.

[0007] The first computer encrypts the two signals to be transmitted into different image information code patterns and sends them to the first digital micromirror device and the second digital micromirror device respectively. The two signal beams carrying the image information codes are imaged by the first convex lens and the second convex lens respectively. Under the action of the beam splitter, the two signal beams carrying the image information codes are merged into one signal beam, so that the two image information codes completely overlap. The beam is then collimated by the third beam expander and then transmitted to the signal receiving and decoding module through the signal transmission module, wherein the signal transmission module is a water tank.

[0008] The signal receiving and decoding module includes a third convex lens, a third digital micromirror device, a fourth convex lens, a single-photon detector, a time-correlated single-photon counter, and a second computer. The third convex lens images the signal light from the signal transmission module onto the working area of ​​the third digital micromirror device. A set of compressed Hadamard masks is loaded onto the third digital micromirror device to encode and modulate the image. The modulated signal is converged to the single-photon detector through the fourth convex lens. The time-correlated single-photon counter records the photon statistical sequence of the single-photon detector within the statistical time of each mask and transmits it to the second computer.

[0009] The second computer uses frequency domain information extraction technology to extract effective information and reconstructs image information codes by combining the recorded Hada code mask. Finally, it uses a machine vision system to identify and decode the information encrypted by the image information code, thereby realizing long-distance underwater optical communication.

[0010] The repetition frequency difference between the two pulse beams ranges from 5 kHz to 50 kHz.

[0011] The image information code is a barcode, QR code, dot matrix code, or optical character recognition.

[0012] A photon-level single-pixel optical communication method based on frequency domain information extraction, employing a photon-level single-pixel optical communication system based on frequency domain information extraction, includes the following steps:

[0013] Step 1: Signal encryption and transmission process;

[0014] Step 2: A beam of signal light carrying image information codes is transmitted in the water tank;

[0015] Step 3: Signal reception and decoding process;

[0016] Step 4: Data processing and image reconstruction process.

[0017] The implementation process of step 1 is as follows:

[0018] Step 1.1: Modulate the first pulse light and the second pulse light to different repetition frequencies;

[0019] Step 1.2: Two beams of first pulse light and second pulse light with different repetition frequencies are expanded by the first beam expander and the second beam expander, respectively, and then reflected by the first mirror and the second mirror to the working areas of the first digital micromirror device and the second digital micromirror device, respectively.

[0020] Step 1.3: The first computer encrypts the signal to be transmitted into two image information codes, and sends them to the working areas of the first digital micromirror device and the second digital micromirror device respectively. At this time, the two pulsed light beams carry the image information codes respectively.

[0021] Step 1.4: The two image information codes are imaged using the first convex lens and the second convex lens respectively, and then combined into a single signal beam under the action of the beam splitter. The images of the two image information codes are completely superimposed, and then collimated by the third beam expander.

[0022] The implementation process of step 3 is as follows:

[0023] Step 3.1: Use the third convex lens to image the signal light transmitted from the water tank onto the working area of ​​the third digital micromirror device;

[0024] Step 3.2: Using a second computer, load a set of Hadamard masks onto the third digital micromirror device to encode and modulate the image information code;

[0025] Step 3.3: The modulated signal is converged to the single-photon detector by the fourth convex lens;

[0026] Step 3.4: Use a time-correlated single-photon counter to record the photon statistical sequence of the single-photon detector within the statistical time of each mask and transmit it to the second computer.

[0027] The implementation process of step 4 is as follows:

[0028] Step 4.1: The statistical sequence y(t, m) of photons collected by the single-photon detector during the sampling time t, obtained by the second computer, is as follows:

[0029] y(t,m)=A(x′,y′,m)(o1(x′,y′,t)+o2(x′,y′,t))+γ(t,m);

[0030] In the above formula: A is an m×n dimensional Hadamard matrix (m≤n), the compression ratio is defined as r=m / n, m is the number of observations, n is the total number of image pixels, each row of A is a 1×n dimensional vector, which is reconstructed into a mask of x′×y′ pixels to modulate the image information codes o1(x′,y′,t) and o2(x′,y′,t); γ(t,m) is the noise signal;

[0031] Step 4.2: Perform a Fast Fourier Transform on the acquired photon statistical sequence y(t, m) to obtain the spectral representation Y(f, m) of the photon statistical sequence:

[0032] Y(f,m)=A(x′,y′,m)(O1(x′,y′,f1)+02(x′,y′,f2))+Γ(f,m);

[0033] In the above formula: O1(x′, y′, f1) and O2(x′, y′, f2) are the Fourier transforms of o1(x, y′, t) and o2(x′, y′, t) respectively, f1 is the repetition frequency of the first pulse light, f2 is the repetition frequency of the second pulse light, and Γ(f, m) is the Fourier transform of γ(t, m);

[0034] Since the signal light carrying the two image information codes has different repetition frequencies, Y(f1,m) and Y(f2,m) can be extracted from Y(f,m).

[0035] Step 4.3: Based on the repetition frequencies f1 and f2 of the two pulses, the harmonic peaks are extracted, and the optimal number of harmonic intensities are summed to obtain the observation value of a single mask.

[0036] Step 4.4: Image reconstruction is performed by combining the loaded Hadamard matrix with the single mask observation value using a single-pixel compressed sensing reconstruction algorithm;

[0037] Step 4.5: Use a machine vision system to identify and decode the signal encrypted by the image information code to achieve long-distance optical communication.

[0038] The advantages of this invention over the prior art are as follows:

[0039] 1. This invention extracts effective information based on spectrum information extraction for image information code reconstruction, which significantly enhances imaging quality and increases the distance of optical communication;

[0040] 2. This invention encrypts information by encoding image information codes. The reconstructed image information codes can be quickly recognized and decoded by machine vision systems, effectively improving the information transmission efficiency, ease of use, security, and diversified applications of optical communication. Attached Figure Description

[0041] The present invention will be further described below with reference to the accompanying drawings:

[0042] Figure 1 This is a system structure diagram of the present invention;

[0043] Figure 2 This is a mathematical model diagram for frequency domain information extraction in this invention;

[0044] Figure 3 This is a graph showing the relationship between the peak signal-to-noise ratio of the reconstructed image and the number of extracted harmonics.

[0045] Figure 4 This is a graph showing the relationship between the structural similarity of the reconstructed image and the number of extracted harmonics.

[0046] Figure 5 The reconstructed QR code image of this invention;

[0047] In the diagram: 1 is the signal encryption and transmission module, 2 is the signal transmission module, 3 is the signal receiving and decoding module, 101 is the first pulse light, 102 is the second pulse light, 103 is the first beam expander, 104 is the first reflector, 105 is the first digital micromirror device, 106 is the first convex lens, 107 is the beam splitter, 108 is the first computer, 109 is the second beam expander, 110 is the second reflector, 111 is the second digital micromirror device, 112 is the second convex lens, and 113 is the third beam expander.

[0048] 301 is the third convex lens, 302 is the third digital micromirror device, 303 is the fourth convex lens, 304 is the single-photon detector, 305 is the time-correlated single-photon counter, and 306 is the second computer. Detailed Implementation

[0049] like Figures 1 to 5 As shown, this invention provides a photonic-level single-pixel optical communication system based on frequency domain information extraction, including a signal encryption and transmission module 1, a signal transmission module 2, and a signal receiving and decoding module 3. The signal encryption and transmission module 1 includes a first pulse light 101 and a second pulse light 102, which have different repetition frequencies. The first pulse light 101 is expanded by a first beam expander 103 and then reflected by a first reflector 104 before illuminating the working area of ​​a first digital micromirror device 105. The second pulse light 102 is expanded by a second beam expander 109 and then... The signal reflected by the second reflector 110 illuminates the working area of ​​the second digital micromirror device 111. The first computer 108 encrypts the signal to be transmitted into different image information code patterns, which are then sent to the first digital micromirror device 105 and the second digital micromirror device 111, respectively. The two beams of signal light carrying the image information codes are imaged by the first convex lens 106 and the second convex lens 112, respectively, and then merged into a single beam of signal light by the beam splitter 107. The two image information codes completely overlap and are then collimated by the third beam expander 113. Finally, the single beam of signal light is transmitted through the signal transmission module 2, which is a water tank.

[0050] In the signal receiving and decoding module 3, the signal light transmitted from the signal transmission module 2 is imaged onto the working area of ​​the third digital micromirror device 302 using the third convex lens 301. A set of compressed Hadamard code masks is loaded onto the third digital micromirror device 302 to encode and modulate the image. The modulated signal is converged to the single-photon detector 304 through the fourth convex lens 303. The time-correlated single-photon counter 305 records the photon statistical sequence of the single-photon detector 304 within the statistical time of each mask and transmits it to the second computer 306. The second computer 306 uses frequency domain information extraction technology to extract the effective information and reconstructs the image information code by combining it with the recorded Hadamard code mask. Finally, the machine vision system is used to identify and decode the signal encrypted by the image information code to realize long-distance underwater optical communication.

[0051] This invention also proposes a photon-level single-pixel optical communication method based on frequency domain information extraction. Based on the above communication system, it mainly includes the following steps:

[0052] Step 1: Signal Encryption and Transmission Process:

[0053] Step 1.1: Modulate the first pulse light 101 and the second pulse light 102 to different repetition frequencies;

[0054] Step 1.2: Two beams of pulse light with different repetition frequencies are expanded by the first beam expander 103 and the second beam expander 109 respectively, and then reflected by the first mirror 104 and the second mirror 110 to the working areas of the first digital micromirror device 105 and the second digital micromirror device 111 respectively.

[0055] Step 1.3: The first computer 108 encrypts the signal to be transmitted into two image information codes and sends them to the working areas of the first digital micromirror device 105 and the second digital micromirror device 111, respectively. At this time, the two pulsed lights carry the image information codes respectively.

[0056] Step 1.4: The two image information codes are imaged using the first convex lens 106 and the second convex lens 112 respectively, and then merged into a single signal beam under the action of the beam splitter 107. The images of the two image information codes are completely superimposed, and then collimated by the third beam expander 113.

[0057] Step 2: A beam of signal light carrying image information code is transmitted in the water tank.

[0058] Step 3: Signal reception and decoding process:

[0059] Step 3.1: Use the third convex lens 301 to image the signal light transmitted from the water tank onto the working area of ​​the third digital micromirror device 302;

[0060] Step 3.2: Using the second computer 306 to load a set of Hadamard masks onto the third digital micromirror device 302, the image information code is encoded and modulated;

[0061] Step 3.3: The modulated signal is converged to the single-photon detector 304 by the fourth convex lens 303;

[0062] Step 3.4: Use the time-correlated single-photon counter 305 to record the photon statistical sequence of the single-photon detector 304 within the statistical time of each mask and transmit it to the second computer 306.

[0063] Step 4: Data processing and image reconstruction process:

[0064] Step 4.1: The photon statistical sequence y(t, m) collected by the single-photon detector 304 during the sampling time t, obtained by the second computer 306, is as follows:

[0065] y(t,m)=A(x′,y′,m)(o1(x′,y′,t)+o2(x′,y′,t))+γ(t,m);

[0066] In the above formula: A is an m×n dimensional Hadamard matrix (m≤n), the compression ratio is defined as r=m / n, m is the number of observations, n is the total number of image pixels, each row of A is a 1×n dimensional vector, which is reconstructed into a mask of x′×y′ pixels to modulate the image information codes o1(x′,y′,t) and o2(x′,y′,t); γ(t,m) is the noise signal;

[0067] Step 4.2: Perform a Fast Fourier Transform on the acquired photon statistical sequence y(t, m) to obtain the spectral representation Y(f, m) of the photon statistical sequence:

[0068] Y(f,m)=A(x′,y′,m)(O1(x′,y′,f1)+O2(x′,y′,f2))+Γ(f,m);

[0069] In the above formula: O1(x′, y′, f1) and O2(x′, y′, f2) are the Fourier transforms of o1(x′, y′, t) and o2(x′, y′, t) respectively, f1 is the repetition frequency of the first pulse light, f2 is the repetition frequency of the second pulse light, and Γ(f, m) is the Fourier transform of γ(t, m);

[0070] Since the signal light carrying the two image information codes has different repetition frequencies, Y(f1,m) and Y(f2,m) can be extracted from Y(f,m).

[0071] Step 4.3: Based on the repetition frequencies f1 and f2 of the two pulses, the harmonic peaks are extracted, and the optimal number of harmonic intensities are summed to obtain the observation value of a single mask.

[0072] Step 4.4: Image reconstruction is performed by combining the loaded Hadamard matrix with the single mask observation value using a single-pixel compressed sensing reconstruction algorithm;

[0073] Step 4.5: Use a machine vision system to identify and decode the signal encrypted by the image information code to achieve long-distance optical communication.

[0074] The effectiveness of this invention will be verified through experiments below:

[0075] With a compression ratio of 0.04 and a sampling time of 1.0s, the repetition frequency of one pulse light was set to 200kHz, and the repetition frequencies of the other pulse light were set to 205kHz, 215kHz, and 230kHz, respectively. Figure 3-4 The peak signal-to-noise ratio (PSNR) and structural similarity index of the reconstructed image information code are presented as a function of the number of extracted harmonics. It can be seen that the image quality is close to optimal when the sum of the intensities of the first seven harmonics is used for image information code reconstruction. Therefore, in this system, considering imaging conditions such as sampling time and compression, extracting the first seven harmonics is the optimal number of harmonics to extract. Furthermore, the PSNR and structural similarity index of the image show very little difference when the repetition frequency difference between the two pulses changes. The results demonstrate that this system has good robustness to the setting of the repetition frequency of the two pulses.

[0076] To further illustrate the effectiveness of image information encoding in this system, the two texts to be transmitted, "Hello" and "World," are encoded into two QR codes, which are then loaded onto the first digital micromirror device 105 and the second digital micromirror device 111, respectively. Two pulses of light with repetition frequencies of 200kHz and 230kHz (duty cycle of 10%) are irradiated into the working windows of the first digital micromirror device 105 and the second digital micromirror device 111. The two beams carrying QR code information are imaged by the first convex lens 106 and the second convex lens 112, respectively, and then combined by the beam splitter 107. After collimation by the third beam expander 113, the beams are transmitted through a 50m long water tank. At the signal receiving end, the beams are modulated using the third digital micromirror device 302, which applies a 256×256 pixel Hadamard mask with a compression ratio of 0.04 and plays back the modulation mask at a speed of 6560Hz. The dual-path pulsed laser counting rate was adjusted to 4MHz, and the modulated photon statistical sequence was measured using a single-photon detector 304 and a time-correlated single-photon counter 305. The sum of the intensities of the first seven spectral harmonics was extracted using a spectral harmonic extraction algorithm, and the QR code image was reconstructed using the TVAL3 algorithm.

[0077] Reconstruction results as follows Figure 5 As shown, the left image represents a QR code image reconstructed using photon counting imaging technology. Because the two QR code images completely overlap, the machine vision system cannot recognize the information carried in the images. The middle and right images are QR code images reconstructed using spectral harmonic extraction technology, respectively. It can be seen that the two QR codes can be effectively recognized and decoded, realizing information communication at a distance of 50m underwater. More importantly, the reconstructed image resolution is 256×256 pixels, the reconstruction frame rate is 2.5 frames per second, and only 24 photons are needed per pixel to complete the effective QR code image reconstruction.

[0078] In summary, this invention is the first to propose a photonic-level single-pixel free-light communication system with high information transmission efficiency, large transmission capacity, long transmission distance, high security, and diverse applications, providing an effective means for realizing long-distance free-light communication underwater.

[0079] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions 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 photon-level single-pixel optical communication system based on frequency domain information extraction, comprising a signal encryption and transmission module (1), a signal transmission module (2), and a signal reception and decoding module (3), characterized in that: The signal encryption and transmission module (1) encrypts two pulses of light with different repetition frequencies into different image information code patterns and then merges them into a signal light. The signal light is transmitted to the signal receiving and decoding module (3) through the signal transmission module (2). The signal receiving and decoding module (3) encodes and modulates the image by loading a Hadamard mask, records the photon statistical sequence within the statistical time of each Hadamard mask using single-photon detection technology, and reconstructs the image information code by combining frequency domain information extraction technology and Hadamard mask. The machine vision system is used to identify and decode the information encrypted by the image information code. The signal encryption and transmission module (1) includes a first pulse light (101), a second pulse light (102), and a first computer (108) with different repetition frequencies. The first pulse light (101) is expanded by a first beam expander (103) and then reflected by a first reflector (104) to illuminate the working area of ​​a first digital micromirror device (105). The second pulse light (102) is expanded by a second beam expander (109) and then reflected by a second reflector (110) to illuminate the working area of ​​a second digital micromirror device (111). The first computer (108) encrypts the two signals to be transmitted into different image information code patterns and sends them to the first digital micromirror device (105) and the second digital micromirror device (111) respectively. The two signal beams carrying image information codes are imaged by the first convex lens (106) and the second convex lens (112) respectively. Under the action of the beam splitter (107), the two signal beams carrying image information codes are merged into one signal beam, so that the two image information codes are completely overlapped. The beam is then collimated by the third beam expander (113) and then transmitted to the signal receiving and decoding module (3) through the signal transmission module (2). The signal transmission module (2) is a water tank. The signal receiving and decoding module (3) includes a third convex lens (301), a third digital micromirror device (302), a fourth convex lens (303), a single-photon detector (304), a time-correlated single-photon counter (305), and a second computer (306). The third convex lens (301) images the signal light transmitted from the signal transmission module (2) onto the working area of ​​the third digital micromirror device (302). A set of compressed Hadamard masks is loaded on the third digital micromirror device (302) to encode and modulate the image. The modulated signal is converged to the single-photon detector (304) through the fourth convex lens (303). The time-correlated single-photon counter (305) records the photon statistical sequence of the single-photon detector (304) within the statistical time of each mask and transmits it to the second computer (306). The second computer (306) uses frequency domain information extraction technology to extract effective information and reconstructs image information codes in combination with the recorded Hadamard mask. Finally, it uses a machine vision system to identify and decode the information encrypted by the image information code, thereby realizing long-distance underwater optical communication.

2. The photonic-level single-pixel optical communication system based on frequency domain information extraction according to claim 1, characterized in that: The repetition frequency difference between the two pulse beams ranges from 5 kHz to 50 kHz.

3. The photonic-level single-pixel optical communication system based on frequency domain information extraction according to claim 1, characterized in that: The image information code is a barcode, QR code, dot matrix code, or optical character recognition.

4. A photonic-level single-pixel optical communication method based on frequency domain information extraction, employing the photonic-level single-pixel optical communication system based on frequency domain information extraction as described in any one of claims 1-3, characterized in that: Includes the following steps: Step 1: Signal encryption and transmission process; Step 2: A beam of signal light carrying image information codes is transmitted in the water tank; Step 3: Signal reception and decoding process; Step 4: Data processing and image reconstruction process.

5. The photonic-level single-pixel optical communication method based on frequency domain information extraction according to claim 4, characterized in that: The implementation process of step 1 is as follows: Step 1.1: Modulate the first pulse light (101) and the second pulse light (102) to different repetition frequencies; Step 1.2: Two beams of first pulse light (101) and second pulse light (102) with different repetition frequencies are expanded by the first beam expander (103) and the second beam expander (109) respectively, and then reflected by the first mirror (104) and the second mirror (110) to the working areas of the first digital micromirror device (105) and the second digital micromirror device (111) respectively. Step 1.3: The first computer (108) encrypts the signal to be transmitted into two image information codes and sends them to the working areas of the first digital micromirror device (105) and the second digital micromirror device (111) respectively. At this time, the two pulsed lights carry the image information codes respectively. Step 1.4: The two image information codes are imaged using the first convex lens (106) and the second convex lens (112) respectively, and then merged into a single signal light under the action of the beam splitter (107). The images of the two image information codes are completely superimposed, and then collimated by the third beam expander (113).

6. The photonic-level single-pixel optical communication method based on frequency domain information extraction according to claim 4, characterized in that: The implementation process of step 3 is as follows: Step 3.1: Use the third convex lens (301) to image the signal light transmitted from the water tank onto the working area of ​​the third digital micromirror device (302); Step 3.2: Using the second computer (306), a set of Hadamard masks is loaded onto the third digital micromirror device (302) to encode and modulate the image information code; Step 3.3: The modulated signal is converged to the single-photon detector (304) by the fourth convex lens (303). Step 3.4: Use a time-correlated single-photon counter (305) to record the photon statistical sequence of the single-photon detector (304) within each mask statistical time and transmit it to the second computer (306).

7. The photonic-level single-pixel optical communication method based on frequency domain information extraction according to claim 4, characterized in that: The implementation process of step 4 is as follows: Step 4.1: The single-photon detector (304) acquired by the second computer (306) in t Photon statistical sequences collected within the sampling time y ( t,m )for: ； In the above formula: A yes m × n The Vihardama matrix (m≤n) has a compressibility defined as follows: r = m / n , m The number of observations, n This represents the total number of pixels in the image. A Each row is a 1× n A dimensional vector, which is then reconstructed into Pixel masking then modulates image information codes and ; This is a noise signal; Step 4.2: Statistical analysis of the collected photon sequences. y ( t,m Perform a Fast Fourier Transform to obtain the spectral representation of the photon statistical sequence. Y ( f,m ): ； In the above formula: , They are respectively and Fourier transform, f 1 represents the repetition frequency of the first pulse light. f 2 represents the repetition frequency of the second pulse light. for Fourier transform; Because the signal light carrying the two image information codes has different repetition frequencies, it is possible to... Y ( f,m Extract from ) Y ( f 1 , m )and Y ( f 2 ,m ); Step 4.3, based on the repetition frequency of the two pulses. f 1 and f 2. Extract the harmonic peak values, select the optimal number of harmonic intensities and sum them to obtain the observation value of a single mask; Step 4.4: Image reconstruction is performed by combining the loaded Hadamard matrix with the single mask observation value using a single-pixel compressed sensing reconstruction algorithm; Step 4.5: Use a machine vision system to identify and decode the signal encrypted by the image information code to achieve long-distance optical communication.

Images