A single-photon single-pixel imaging method for estimating intensity based on the average number of pulses

Abstract

The present invention discloses a single-photon single-pixel imaging method for estimating intensity based on the average number of pulses, comprising: recording each single-photon event; averaging the number of pulses of each recorded single-photon event to obtain the average number of pulses for different numbers of photons; using the average number of pulses for different numbers of photons to perform intensity estimation to obtain the intensity estimated by the average number of pulses, and performing information restoration on the target object to obtain an image of the target object; based on the image of the target object, evaluating the imaging quality of the target object by calculating different image quality metrics. The image is restored by averaging the number of pulses before each photon arrives. In the experiment, only one single-photon avalanche diode is used as a single-photon detector to obtain photon information, and the efficiency of the method of the present invention under low-light conditions is demonstrated. Compared with the traditional time-correlated single-photon counting imaging method, the method of the present invention can use fewer photons to achieve information restoration of the target object.

Description

Technical Field

[0001] The present invention belongs to the technical field of single - photon single - pixel imaging, and particularly relates to a single - photon single - pixel imaging method based on average pulse number to estimate intensity. Background Art

[0002] Traditional imaging techniques are affected by absorption, scattering, turbulence, and complex light - matter interaction effects during propagation, making it difficult to obtain clear underwater images. Single - pixel imaging has characteristics such as high sensitivity, anti - interference, and a wide working wavelength range, and has significant advantages in weak light, special wavelength bands, and increasing imaging distance. It is expected to become the next - generation key - developed information acquisition technology. However, current single - pixel imaging methods lack in - depth exploration of the imaging scattering physical mechanism, resulting in poor information recovery, and the time - consuming sampling time makes it difficult to obtain dynamic real - time information recovery of the target object, severely restricting the popularization and application of this technology in underwater imaging detection.

[0003] Single - photon single - pixel imaging technology uses highly sensitive single - photon detectors that can detect single - photon events. This high sensitivity enables effective imaging in environments with extremely weak light intensities, which is difficult to achieve in conventional optical imaging technologies. Single - photon detectors can record the arrival time of photons on an extremely short time scale. This not only allows single - photon detectors to capture fast - dynamic events but also endows them with the ability to perform high - time - resolution imaging. In addition, single - photon single - pixel imaging technology also has strong penetration ability. In many application scenarios, single - photon detectors can effectively penetrate obstacles, thereby realizing imaging of deep structures or distant targets. This characteristic makes single - photon single - pixel imaging technology have broad application potential in fields such as biomedicine, environmental monitoring, and astronomical observation. Single - photon single - pixel imaging can also be combined with other imaging technologies (such as super - resolution microscopy, quantum imaging technology, etc.) to further improve the spatial and temporal resolution of imaging. Through multi - modal imaging, image data at different scales can be obtained simultaneously, thereby achieving a more comprehensive and accurate imaging effect. With the continuous development of quantum technology, single - photon single - pixel imaging technology is expected to be widely applied in more fields, promoting scientific research and technological innovation.

[0004] In the process of implementing the technical method of the embodiments of the present invention, the inventors of the present application at least found the following technical problems in the prior art:

[0005] Traditional time-correlated single-photon counting imaging methods require a relatively large number of photons to effectively recover the information of the target object. Since each photon event must be precisely recorded in terms of time, the data volume generated by time-correlated single-photon counters is extremely large, resulting in high storage requirements, complex data processing, and large computational overhead. In addition, since photon events need to be counted and processed one by one, the imaging speed is relatively slow. Especially when facing high-intensity or rapidly changing signals, it is often difficult to obtain real-time high-quality images. Summary of the Invention

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art and propose a single-photon single-pixel imaging method based on estimating intensity using the average number of pulses. Different from traditional time-correlated single-photon counting imaging methods, this method can use fewer photons to achieve the information recovery of the target object.

[0007] To achieve the above purpose, the present invention adopts the following technical solutions:

[0008] A single-photon single-pixel imaging method based on estimating intensity using the average number of pulses, comprising the following steps:

[0009] Step S1: The pulsed light emitted by an ultrafast continuum pulse laser passes through an attenuator and a beam expander and irradiates a digital micromirror device. The substrate illumination pattern on the digital micromirror device encodes the incident light, and is focused and transmitted through a first lens to irradiate the target object. The photon signal transmitted by the target object is received by a single-photon avalanche diode through a second lens and input into a TCSPC module to record each single-photon event;

[0010] Step S2: Average the number of pulses of each recorded single-photon event to obtain the average number of pulses for different numbers of photons;

[0011] Step S3: Use the average number of pulses for different numbers of photons to perform intensity estimation to obtain the intensity estimated by the average number of pulses, and perform information recovery on the target object to obtain an image of the target object;

[0012] Step S4: Based on the image of the target object, evaluate the imaging quality of the target object by calculating different image quality metrics.

[0013] Optionally, the average number of pulses described in step S2 is expressed as:

[0014] ,

[0015] In the above formula, represents the number of pulses before the arrival of the th photon of the th substrate illumination pattern, M represents the total number of photons, represents the The average number of pulses corresponding to a base illumination pattern.

[0016] Optionally, the average pulse number estimation intensity described in step S3 is expressed as:

[0017] ,

[0018] In the above formula, represents the total intensity of the th base illumination pattern, represents the th average number of pulses corresponding to the base illumination pattern.

[0019] Optionally, the image of the target object in step S3 is expressed as:

[0020] ,

[0021] In the above formula, represents the image of the target object, K represents the number of base illumination patterns, represents the th intensity value of the base illumination pattern, represents the th average number of pulses corresponding to the base illumination pattern, represents the th average intensity of the base illumination pattern.

[0022] Optionally, the image quality evaluation index in step S4 is specifically the variance of the gray values of the image pixel points and the Brenner value of the image.

[0023] Optionally, the formula for the variance of the gray values of the image pixel points is:

[0024] ,

[0025] In the above formula, represents the variance of the gray values of the image pixel points within the selected range, a represents the total number of pixel points within the selected range, represents the gray value of the pixel point with coordinates at , represents the average gray value of the pixel points within the selected range.

[0026] Optionally, the formula for the Brenner value of the image is:

[0027] ,

[0028] In the above formula, b represents the Brenner value of the image, represents the coordinate at the gray value of the pixel point, represents the abscissa of the pixel points within the selected range, represents the ordinate of the pixel points within the selected range.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] 1. Compared with the traditional time-correlated single-photon counting imaging method, the single-photon single-pixel imaging method based on average pulse number estimation of intensity in the present invention has a faster imaging speed, can face high-intensity or rapidly changing signals, and realizes the acquisition of real-time high-quality images. Since in the single-photon single-pixel imaging method based on average pulse number estimation of intensity in the present invention, the time-correlated single-photon counter does not need to record every photon event, the amount of generated data is less, resulting in low storage requirements, simple data processing, low computational overhead, and facilitating real-time analysis. The single-photon single-pixel imaging method based on average pulse number estimation of intensity in the present invention reduces the influence of background noise to a certain extent. Especially in the case of strong background signals, it can still provide relatively clear images.

[0031] 2. The single-photon single-pixel imaging method based on average pulse number estimation of intensity in the present invention provides important theoretical and technical guiding significance for the application field of ultra-low weak light imaging. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is the experimental optical path schematic diagram of a single-photon single-pixel imaging method based on average pulse number estimation of intensity in an embodiment of the present invention;

[0033] Figure 2 is the time sequence diagram of the photon signal and the synchronization signal recorded by the time-correlated single-photon counter in an embodiment of the present invention;

[0034] Figure 3 is the image reconstruction result diagram obtained through experiments in an embodiment of the present invention;

[0035] Figure 4 Comparison diagram of the imaging effects between the single-photon single-pixel imaging method based on average pulse number estimation of intensity and the traditional time-correlated single-photon counting imaging method in an embodiment of the present invention;

[0036] Figure 5 For the embodiment of the present invention Figure 3 the Brenner values of the images from (a) to (g);

[0037] In the figure: 1 - supercontinuum pulse laser; 2 - attenuator; 3 - beam expander; 4 - time-correlated single photon counter; 5 - digital micromirror device; 6 - first lens; 7 - target object; 8 - second lens; 9 - single photon avalanche diode; 10 - computer; 11 - front view of the target object. Specific implementation mode

[0038] For ease of understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0039] Embodiment

[0040] As Figure 1 shown, the computer 10 is connected to the digital micromirror device 5 and the time-correlated single photon counter 4. The pulsed light emitted by the supercontinuum pulse laser 1 with a repetition frequency of 5 MHz is irradiated onto the digital micromirror device 5 through the attenuator 2 and the beam expander 3. The computer 10 controls the parameters of the encoded substrate illumination pattern projected by the digital micromirror device 5. The substrate illumination pattern on the digital micromirror device 5 encodes the incident light and is focused and transmitted through the first lens 6 to irradiate the target object 7. The photon signal transmitted by the target object 7 is received by the single photon avalanche diode 9 as a single photon detector through the second lens 8 and input into the TCSPC (Time-Correlated Single Photon Counting) module of the time-correlated single photon counter 4. The synchronization signal of the pulsed light is input into the SYNC-IN channel of the time-correlated single photon counter 4, and the synchronization signal of the substrate illumination pattern of the digital micromirror device 5 is input into the M1 channel of the time-correlated single photon counter 4 to maintain the synchronization of the entire system. The data of the time-correlated single photon counter 4 is fed back to the computer 10, and the computer 10 performs information recovery of the target object 7. The front view 11 of the target object is the front projection view of the target object 7.

[0041] Furthermore, as Figure 2 shown, record the number of pulses of the photons corresponding to each substrate illumination pattern. For each substrate illumination pattern, the photons projected from the target object are recorded by the single photon avalanche diode; then the digital signal is fed to the time-correlated single photon counter, and the time-correlated single photon counter simultaneously receives the synchronization signals from the digital micromirror device and the pulsed light source. Immediately afterwards, use the average number of pulses of different photon numbers to estimate the intensity, where the average number of pulses is expressed as:

[0042] ,

[0043] In the above formula, Indicates The first The number of pulses before the photon arrives, M represents the total number of photons, Indicates The average number of pulses corresponding to the base illumination pattern.

[0044] The average pulse number estimated intensity is expressed as:

[0045] ,

[0046] In the above formula, Indicates The total intensity of the base illumination pattern, Indicates The average number of pulses corresponding to the base illumination pattern.

[0047] Specifically, by intensity estimation Correlation measurement with the substrate illumination pattern to recover the image of the target object , the image of the target object is represented as:

[0048] = ,

[0049] In the above formula, An image representing the target object, K Indicates the number of base lighting patterns, Indicates The intensity value of the base lighting pattern, Indicates The average number of pulses corresponding to the base illumination pattern, Indicates The average intensity of the substrate illumination patterns.

[0050] like Figure 3 As shown, Figure 3 Images (a) to (f) are images of the target object obtained by using the single-photon single-pixel imaging method to estimate the intensity using the average pulse number. Figure 3 The image (g) is an image of the target object obtained using the time-correlated single photon counting imaging method. Figure 3 The number of photons used in images (a) to (g) are 10, 100, 200, 300, 400, 500, and 584, respectively. Figure 3 The image (h) in the figure shows the position of the target pattern in the reconstructed image. The coordinates of point A in the black frame are (200, 370), and the coordinates of point B are (390, 200), indicating that the range of the target pattern is x =200 tox = 390, y = 200 to y = 370.

[0051] Furthermore, the imaging effect of the single-photon single-pixel imaging method based on the average pulse number to estimate intensity is evaluated by calculating different image quality metrics. The variance of the grayscale values of the image pixel points and the Brenner value of the image are calculated respectively to evaluate the imaging quality of the target object. The formula for calculating the variance of the grayscale values of the image pixel points is as follows:

[0052] ,

[0053] In the above formula, represents the variance of the grayscale values of the image pixel points within the selected range, a represents the total number of pixel points within the selected range, is the grayscale value of the pixel point with coordinates at , represents the average grayscale value of the pixel points within the selected range.

[0054] Figure 4 This is a comparison chart of the imaging effects between the single-photon single-pixel imaging method based on the average pulse number to estimate intensity in the present invention and the traditional time-correlated single-photon counting imaging method, indicating that Figure 3 the (a) to (g) images in Figure 4 are respectively the variances of the grayscale values of the pixel points at y = 230, y = 260, y = 290, y = 320, and y = 350. The grayscale value of each pixel point has been normalized, and the abscissa represents the number of photons. As can be seen from

[0055] Figure 5 is Figure 3 the Brenner value of the (a) to (g) images in

[0056] ,

[0057] In the above formula, b represents the Brenner value of the image, represents the grayscale value of the pixel point with coordinates at , represents the abscissa of the pixel points within the selected range, represents the ordinate of the pixel points within the selected range.

[0058] As can be seen from Figure 5It can be seen that the single-photon single-pixel imaging method for estimating intensity based on the average number of pulses to a certain extent is superior to the traditional time-correlated single-photon counting imaging method. Specifically, compared with the traditional time-correlated single-photon counting imaging method, the single-photon single-pixel imaging method for estimating intensity based on the average number of pulses can use fewer photons to achieve the information recovery of the target object.

[0059] It should be understood that the above description of the preferred embodiment is relatively detailed, and it should not be considered as a limitation to the protection scope of the present invention. Under the inspiration of the present invention, those of ordinary skill in the art can also make substitutions or deformations without departing from the protection scope defined by the claims of the present invention, and all fall within the protection scope of the present invention. The scope of protection claimed by the present invention shall be subject to the appended claims.

Claims

1. A single-photon single-pixel imaging method based on average pulse number intensity estimation, characterized in that: The following steps are involved: Step S1, the pulse light emitted by the supercontinuum pulse laser is irradiated onto the digital micromirror device through the attenuator and the beam expander, the substrate illumination pattern on the digital micromirror device encodes the incident light, which is focused and transmitted by the first lens to irradiate the target object, and the photon signal transmitted by the target object is received by the single photon avalanche diode through the second lens and input into the TCSPC module to record each single photon event; Step S2, averaging the number of pulses of each single photon event recorded to obtain the average number of pulses with different photon numbers; the average number of pulses in step S2 is expressed as: ， In the above formula, Indicates The first The number of pulses before the photon arrives, M represents the total number of photons, Indicates The average number of pulses corresponding to the base illumination pattern; Step S3, using the average pulse number of different photon numbers to perform intensity estimation to obtain the average pulse number estimation intensity, and performing information recovery on the target object to obtain an image of the target object; Step S4: Based on the image of the target object, the imaging quality of the target object is evaluated by calculating different image quality indicators.

2. The method according to claim 1, characterized in that The average pulse number estimation intensity described in step S3 is expressed as: ， In the above formula, Indicates The total intensity of the base illumination pattern, Indicates The average number of pulses corresponding to the base illumination pattern.

3. The method according to claim 1, characterized in that: The image of the target object in step S3 is represented as: ， In the above formula, An image representing the target object, K Indicates the number of base lighting patterns, Indicates The intensity value of the base lighting pattern, Indicates The average number of pulses corresponding to the base illumination pattern, Indicates The average intensity of the substrate illumination patterns.

4. The method according to claim 1, characterized in that The image quality evaluation index in step S4 is specifically the variance of the grayscale value of the image pixels and the Brenner value of the image.

5. The method according to claim 4, characterized in that The formula for the variance of the grayscale value of the image pixel is: ， In the above formula, represents the variance of the grayscale values ​​of the image pixels within the selected range, a represents the total number of pixels within the selected range, Indicates the coordinates in The gray value of the pixel, Represents the average grayscale value of pixels within the selected range.

6. The method according to claim 4, characterized in that The formula for the Brenner value of the image is: ， In the above formula, b represents the Brenner value of the image, Indicates the coordinates in The gray value of the pixel, Indicates the horizontal coordinate of the pixel point within the selected range. Indicates the vertical coordinate of the pixel points within the selected range.

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