Computed imaging method for cross-bar anode single photon detector

Abstract

The present application relates to the field of computational imaging, and particularly relates to a kind of cross bar anode single photon detector's computational imaging method, the computational imaging method is first by full field of view illumination screening effective data, the average output signal amplitude of each anode bar anode bar and the total average output signal amplitude of all anode bar are calculated to obtain correction factor;When target imaging, the original output signal of each anode bar is corrected using correction factor, then the effective signal data screening of the original output signal after correction is carried out, then the incident position coordinates are calculated by substituting effective signal data into Gaussian algorithm, then the incident position coordinates are mapped to mapping matrix and stretched to 256 gray scale display.The computational imaging method provided by the present application can suppress fixed pattern noise, improve imaging resolution and reduce image distortion.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of computed imaging, and particularly relates to a computed imaging method of a cross-bar anode single photon detector. BACKGROUND

[0002] In the field of computed imaging, single photon detectors show important application value in weak target detection and long-distance detection due to their high sensitivity. Single photon detectors mainly include detectors based on microchannel plates and position-sensitive anodes, detectors based on single photon avalanche photodiodes, and detectors based on superconducting nanowires. Among them, detectors based on microchannel plates and position-sensitive anodes can be further divided into detectors of delay line anodes, cross-bar anodes, wedge-bar anodes and vernier anodes according to different anode structures.

[0003] As a new type of two-dimensional position-sensitive anode, the cross-bar anode has advantages of high photon sensitivity, high spatial resolution, low gain, long service life and extremely low dark count rate, and has become one of the key devices for long-distance dark space target detection imaging. At present, the cross-bar anode single photon detector has been successfully applied to the world ultraviolet observatory project, the Colorado high-resolution Echelle stellar spectrograph and the joint astrophysics plasma experiment and other important projects.

[0004] In the imaging process of the cross-bar anode single photon detector, the traditional incident position decoding algorithm mainly includes the center of gravity algorithm and the Gaussian algorithm. Although these algorithms can realize the basic position decoding function, they do not fully consider the fixed pattern noise introduced by the inconsistent geometric area and charge-sensitive amplifier performance between each cross-bar anode of the detector, resulting in systematic errors in the decoded position, and further causing distortion in the reconstructed image, which limits the further improvement of the imaging quality and makes it difficult to meet the needs of high-precision detection scenarios.

[0005] At present, the existing means to improve the imaging quality mainly focus on improving the processing fineness of the detector, but hardware optimization has problems such as high cost and obvious technical bottlenecks. Therefore, innovation and optimization from the algorithm level become the key direction to solve the fixed pattern noise and improve the imaging performance of the cross-bar anode single photon detector, and have important research significance and practical value. SUMMARY

[0006] Therefore, the present application aims to provide a computed imaging method of a cross-bar anode single photon detector to solve the technical problem that the existing cross-bar anode single photon detector has systematic errors in the decoded position due to the fixed pattern noise, and further reduces the imaging quality.

[0007] To achieve the above-mentioned purpose, the technical solution of the present application is as follows:

[0008] A computational imaging method for a cross-strip anode single-photon detector, wherein the cross-strip anode includes a set of anode strips extending along a first direction and another set of anode strips extending along a second direction, and the computational imaging method includes the following steps:

[0009] S1: Under full field-of-view illumination, acquire the output signal generated by the cross-strip anode single-photon detector in response to each photon incident event; record the photon incident events whose output signal amplitude is within the preset effective range as effective photon incident events, count the number of effective photon incident events for each anode strip and the total output signal amplitude of all effective photon incident events for each anode strip, and calculate the average output signal amplitude of each anode strip and the total average output signal amplitude of the cross-strip anodes;

[0010] S2: Calculate the correction factor for each anode bar based on the average output signal amplitude of each anode bar and the total average output signal amplitude of the cross-shaped anodes, and establish the mapping relationship between each anode bar and the corresponding correction factor;

[0011] S3: When imaging the target, acquire the original output signal of each anode bar; according to the mapping relationship established in step S2, correct the original output signal of each anode bar, take the data whose amplitude of the corrected output signal is within the preset effective range as the effective signal amplitude data, and input the effective signal amplitude data into the Gaussian algorithm to calculate the incident position coordinates of a single photon incident event.

[0012] S4: Map all incident position coordinates to a mapping matrix of a preset size, stretch the number of photons in each interval of the mapping matrix to 256 gray levels, and generate and display the final imaging result.

[0013] Furthermore, in step S1, the formula for calculating the average output signal amplitude of each anode bar is as follows:

[0014] ;

[0015] in, Indicates the first i The average output signal amplitude of each anode bar Indicates the first i The total output signal amplitude of all effective photon incident events of the anode strip. Indicates the first i The first anode bar k The output signal amplitude of a valid photon incident event Indicates the first i Each anode bar records the effective photon incident events.

[0016] Furthermore, in step S1, the total average output signal amplitude of the cross-bar anodes The calculation formula is:

[0017] ;

[0018] in, This represents the total number of all valid photon incident events counted by the crossbar anode. This represents the total output signal amplitude for all valid photon incident events at the crossbar anode. Indicates the first i The total output signal amplitude of all effective photon incident events of the anode strip. Indicates the first i The first anode bar k The output signal amplitude of a valid photon incident event Indicates the first i The effective photon incident events recorded by each anode bar N This represents the total number of anode bars.

[0019] Furthermore, in step S2, the correction factor for each anode bar... The calculation formula is:

[0020] ;

[0021] in, Indicates the first i The average output signal amplitude of each anode bar This represents the total average output signal amplitude of the crossbar anodes. Indicates the first i The number of valid photon incident events recorded by each anode bar tends to be infinite.

[0022] Furthermore, in step S2, the mapping relationship between each anode bar and its corresponding correction factor is as follows:

[0023] ;

[0024] in, i Indicates the anode bar number, i =1,2,…, N , N This represents the total number of anode bars. Indicates the first i The effective photon incident events recorded by each anode bar This indicates the correction factor corresponding to the anode bar number.

[0025] Furthermore, in step S3, the original output signal of each anode bar is corrected by dividing the original output signal amplitude by the correction factor of the corresponding anode bar.

[0026] Further, in step S3, the calculation formula of the incident position coordinate of each photon incident event is calculated by using the Gaussian algorithm:

[0027] ;

[0028] ;

[0029] wherein, represents the first direction position coordinate of the photon incident on the cross strip anode, represents the second direction position coordinate of the photon incident on the cross strip anode, represents the period of the cross strip anode in the first direction, represents the period of the cross strip anode in the second direction, represents the charge amount collected by the anode strip where the maximum value of the charge amount in the first direction is located, j represents the charge amount collected by the anode strip where the maximum value of the charge amount in the first direction is located, represents the charge amount collected by the anode strip where the maximum value of the charge amount in the first direction is located, j represents the charge amount collected by the anode strip where the maximum value of the charge amount in the first direction is located, represents the charge amount collected by the anode strip where the maximum value of the charge amount in the first direction is located, j represents the charge amount collected by the anode strip where the maximum value of the charge amount in the first direction is located, represents the charge amount collected by the anode strip where the maximum value of the charge amount in the second direction is located, t represents the charge amount collected by the anode strip where the maximum value of the charge amount in the second direction is located, represents the charge amount collected by the anode strip where the maximum value of the charge amount in the second direction is located, t represents the charge amount collected by the anode strip where the maximum value of the charge amount in the second direction is located, represents the charge amount collected by the anode strip where the maximum value of the charge amount in the second direction is located. t Further, in step S4, the incident position coordinate is set as

[0030] , the corresponding position coordinate in the mapping matrix is , and the calculation formula of is:

[0031] ;

[0032] ;

[0033] wherein, m represents the number of anode strips in the first direction, n represents the number of anode strips in the second direction, size represents the preset size of the mapping matrix.

[0034] Further, in step S4, the mapping matrix is composed of different intervals, each interval corresponds to a field of view sub-region in the detection field of view, and the number of photons incident in each field of view sub-region is recorded.​

[0035] Further, in step S4, the specific process of stretching the photon number of each interval in the mapping matrix to 256 gray levels is as follows:

[0036] First, traverse the mapping matrix to find the interval with the most photons, and record the photon number of the interval as n max ;

[0037] Then, divide the photon number of each interval by n max , to obtain the normalized result of each interval

[0038] Finally, multiply the normalized result of each interval by 256 to obtain a 256 gray level gray image.

[0039] Compared with the prior art, the present application can achieve the following beneficial effects:

[0040] 1. Effectively suppresses fixed pattern noise and improves imaging quality

[0041] By introducing a data screening and data correction mechanism, the output signal amplitude of each anode strip is corrected, significantly reducing the fixed pattern noise caused by geometric differences of the cross strip anode, inconsistent response of the amplifier and other factors, thereby reducing the position decoding error and improving the spatial resolution and signal-to-noise ratio of the image.

[0042] 2. Improves imaging distortion and enhances image authenticity

[0043] The present application establishes a mapping relationship between the anode strip and the correction factor, and corrects the imaging data in real time, effectively suppressing the image distortion, so that the reconstructed image is closer to the real target distribution.

[0044] 3. Strong compatibility and wide applicability

[0045] The computational imaging method of the present application is not dependent on a specific hardware structure and can be applied to various single-photon detectors with cross strip anodes. Users can adjust parameters such as anode period according to actual needs, and the method has good universality and scalability.

[0046] 4. Improving the performance of the detector and reducing the cost of system debugging

[0047] Optimizing the imaging performance of the detector at the software algorithm level reduces the stringent requirements for hardware processing precision and consistency, reduces the cost of detector production and processing, and reduces the cost of equipment debugging and maintenance, which is conducive to the wide application of this type of detector in the field of weak target detection, astronomical observation, etc.

[0048] 5. Efficient data processing and imaging display

[0049] After the photon incident position decoding is completed, the photon is mapped to a gray scale image, real-time or post-processing imaging display is supported, intuitive observation and analysis of the detection results by the user is facilitated, and the practicability and interactivity of the system are improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] The accompanying drawings, which form a part of the present application, are intended to provide further understanding of the present application and are incorporated herein for illustrative purposes. The schematic embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application. In the drawings:

[0051] Figure 1 The overall flowchart of the cross-bar anode single-photon detector computing imaging method described in the embodiments of the present application;

[0052] Figure 2 The logic flowchart of the cross-bar anode single-photon detector computing imaging method described in the embodiments of the present application;

[0053] Figure 3 The imaging results obtained by the computing imaging method and the traditional incident position decoding algorithm of the present application for the same target are compared in the schematic diagram. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below with reference to the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not constitute limitations on the present application.

[0055] It should be noted that the embodiments in the present application and the features in the embodiments can be combined with each other without conflict.

[0056] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application. In addition, the terms "first", "second" and the like are only for the purpose of description and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined with "first", "second" and the like can be explicitly or implicitly included one or more. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0057] In the description of the present application, it should be noted that unless otherwise specified and limited, the terms "assembly", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium, or it can be connected inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0058] The present application will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0059] The embodiment of the present application provides a cross-bar anode single photon detector computing imaging method, which introduces data screening and data correction mechanism to reduce the fixed pattern noise of the cross-bar anode single photon detector, thereby improving the resolution of the detection and reducing the distortion of the computing imaging.

[0060] The cross-bar anode includes a group of anode strips extending in a first direction and another group of anode strips extending in a second direction, and the plurality of anode strips in the first direction intersect the plurality of anode strips in the second direction.

[0061] As shown in Figure 1 and Figure 2 The cross-bar anode single photon detector computing imaging method includes the following steps:

[0062] S1: Collect the output signal of the cross strip anode single photon detector in response to each photon incident event under full field illumination condition; record the photon incident event with the output signal amplitude in the preset effective range as the effective photon incident event, count the number of effective photon incident events of each anode strip and the total output signal amplitude of all effective photon incident events of each anode strip, and calculate the average output signal amplitude of each anode strip and the total average output signal amplitude of the cross strip anode.

[0063] The full field illumination imaging refers to that the photons emitted by the target directly pass through the entrance window of the cross strip anode single photon detector and are incident on the microchannel plate, without imaging the target.

[0064] The screening of the photon incident event is the data screening mechanism. In the real detection, the output signal of the cross strip anode single photon detector is not all derived from the effective photon incident event signal, but also contains various noise signals. The data screening mechanism only allows the photon incident event signal meeting the condition that the output signal amplitude is in the preset effective range to pass through and enter the subsequent processing flow, so as to ensure that the data used for subsequent calculation and correction is the high-quality and effective photon incident event signal, and to ensure the accuracy and reliability of the imaging from the source.

[0065] Due to the structure of the cross strip anode, each photon incident will generate signals of 64 channels, and each channel will sample the processed charge signal for 24 times. The output signal amplitude is embodied as the maximum sampling value. The anode strip with the maximum sampling value is found, and the Gaussian fitting of the sampling value of the anode strip is performed. The Gaussian fitting result is the output signal amplitude.

[0066] The preset effective range of the output signal amplitude for the photons of different wavebands is determined according to the distribution of the maximum sampling value in several times of photon incidence.

[0067] The average output signal amplitude of each anode strip is calculated by the following formula:

[0068] (1);

[0069] wherein, represents the average output signal amplitude of the i-th anode strip, i represents the total output signal amplitude of all effective photon incident events of the i-th anode strip, represents the output signal amplitude of the j-th effective photon incident event of the i-th anode strip, i represents the effective photon incident event recorded by the i-th anode strip. i k i ​​​​​

[0070] The total average output signal amplitude of the cross strip anode, i.e. the total average output signal amplitude of all anode strips, is denoted as and is calculated by the following formula:

[0071] (2);

[0072] wherein denotes the total number of all valid photon incident events counted by the cross strip anode (all anode strips), denotes the total output signal amplitude of all valid photon incident events of the cross strip anode, N and

[0073] S2: According to the average output signal amplitude of each anode strip and the total average output signal amplitude of the cross strip anode, a correction factor of each anode strip is calculated, and a mapping relationship between each anode strip and the corresponding correction factor is established.

[0074] The correction factor of each anode strip is calculated by the following formula:

[0075] (3);

[0076] wherein denotes the average output signal amplitude of the i-th anode strip, i denotes the total average output signal amplitude of the cross strip anode, denotes the number of valid photon incident events recorded by the i-th anode strip, denotes the total number of valid photon incident events counted by the cross strip anode (all anode strips), i denotes the total number of anode strips,

[0077] Only when the number of valid photon incident events collected by each anode strip is very large (theoretically infinite), the calculated average output signal amplitude and the total average output signal amplitude will be infinitely close to their true, stable theoretical expected values, so that the correction factor calculated based on the average output signal amplitude and the total average output signal amplitude is the most accurate and reliable.

[0078] The mapping relationship between each anode strip and the corresponding correction factor is:

[0079] (4);

[0080] wherein i denotes the anode strip number, i = 1, 2, …, N ,N total number of anode strips, representing the first i anode strip record of valid photon incident events, representing the correction factor corresponding to the anode strip number.

[0081] S3: when imaging the target, obtaining the original output signal of each anode strip; correcting the original output signal of each anode strip according to the mapping relationship established in step S2, taking the data with the corrected output signal amplitude in the preset effective interval as the valid signal amplitude data, and bringing the valid signal amplitude data into the Gaussian algorithm to calculate the incident position coordinates of a single photon incident event.

[0082] The correction method of the original output signal of each anode strip is to divide the original output signal amplitude by the correction factor of the corresponding anode strip. The correction of the original output signal of the anode strip through the mapping relationship between the anode strip and the correction factor is the data correction mechanism. The data correction mechanism actively compensates for the inherent response non-uniformity of each anode strip in the cross-strip anode, thereby suppressing the fixed pattern noise at the algorithm level and ultimately improving the position decoding accuracy and imaging quality.

[0083] The traditional barycenter method or Gaussian algorithm assumes that the responses of all anode strips are the same. Therefore, when an anode strip has a naturally high gain, the algorithm will mistakenly believe that the anode strip has collected more charges, resulting in a systematic error in the calculated photon incident position towards the anode strip with high gain. The present application introduces a correction factor to correct the original output signal of each anode strip when imaging the target. The original output signal of an anode strip with high gain will be appropriately reduced, and the original output signal of an anode strip with low gain will be appropriately increased, thereby eliminating the systematic position deviation caused by the uneven gain of the anode strips. This makes the Gaussian algorithm receive a set of signals that have eliminated the fixed pattern noise, thereby calculating coordinates closer to the real photon incident position, significantly improving the position decoding accuracy of the photon incident event.

[0084] In addition, the fixed pattern noise is not random noise, but has a fixed spatial pattern. If the anode strips in a certain area of the cross-strip anode single photon detector have generally high gain, all points imaged in that area will be systematically pulled towards these channels, resulting in a repeatable, nonlinear geometric distortion in the entire image. The data correction mechanism compensates for the gain of each anode strip, breaking this fixed error spatial pattern. After correction, the positions of the points in the image are no longer affected by the high or low gain of their anode strips, thereby restoring the normal geometric relationship of the image and significantly reducing the imaging distortion.

[0085] After correcting the original output signal of each anode bar, the amplitude of the corrected output signal is filtered. The filtering condition is set as "whether the amplitude of the corrected output signal is within the preset valid range". The amplitude of the corrected output signal that meets the filtering condition is taken as the valid signal amplitude data, and the Gaussian algorithm is used to calculate the incident position coordinates.

[0086] Let the coordinates of the incident position be... , This represents the coordinates of the first direction position of the photon incident on the intersecting bar anodes. Let represent the second-direction position coordinates of the photon incident on the intersecting strip anodes. Then, the Gaussian algorithm calculates the incident position coordinates. The process is as follows:

[0087] The charge density distribution in the first direction Represented as a Gaussian distribution:

[0088] (5);

[0089] in, Q total This represents the amplitude when the charge density distribution in the first direction is considered to be a Gaussian distribution. Represents standard deviation, This indicates any point on the anode bar in the first direction.

[0090] Take the logarithm of both sides of equation (5):

[0091] (6);

[0092] After sorting, we obtained:

[0093] (7);

[0094] The first direction where the maximum charge value is located is the first j The amount of charge collected by each anode bar First direction j - The amount of charge collected by one anode bar First direction j Charge collected by +1 anode bar and the first anode bar in the first direction The coordinates of the first location point and the first Substituting the coordinates of each location point into equation (7), we can calculate... :

[0095] (8);

[0096] For the first direction period is The cross-bar anode of the formula (8) can be rewritten as:

[0097] (9).

[0098] The calculation process is the same, and the final calculation formula is:

[0099] (10);

[0100] wherein, represents the period of the cross-bar anode in the second direction, represents the charge amount collected by the first t anode bar in the second direction where the maximum charge amount is located, represents the charge amount collected by the first t -1 anode bar in the second direction, represents the charge amount collected by the first t +1 anode bar in the second direction.

[0101] S4: Map all incident position coordinates to a preset size of a mapping matrix, stretch the photon number of each interval in the mapping matrix to 256 gray levels, and generate and display the final imaging result.

[0102] Let the incident position coordinate be , and the corresponding position coordinate in the mapping matrix be , then the calculation formula of is:

[0103] (11);

[0104] (12);

[0105] wherein, m represents the number of anode bars in the first direction, n represents the number of anode bars in the second direction, size represents the preset size of the mapping matrix, for example, if the mapping matrix is 256x256, then size = 256.

[0106] For example, the incident position coordinate of one photon is (2.3, 5.7). This indicates that the incident position coordinate is closer to the second anode bar in the first direction, but deviates towards the third anode bar; in the second direction, it is closer to the fifth anode bar, but deviates towards the sixth anode bar.

[0107] The mapping matrix can be regarded as a grid composed of 1000*1000 horizontal and vertical intersecting lines, and the interval is one small square in the grid. If the interval is 1*1, the mapping matrix is composed of 1000*1000 intervals. Each interval corresponds to a field-of-view sub-region in the detection field of view. After the incident position coordinates are mapped to the mapping matrix, the number of incident photons in each field-of-view sub-region is recorded.

[0108] In step S4, the number of photons in each interval in the mapping matrix is stretched to 256 gray levels, and the specific process is as follows:

[0109] Finding the maximum value: traversing the mapping matrix, finding the interval with the most photons, and recording the number of photons in the interval as n max .

[0110] Normalization: divide the number of photons in each interval by n max , all values are scaled to the interval [0, 1] to obtain the normalized result of each interval.

[0111] Gray mapping: multiply the normalized result of each interval by 255, and round or floor the calculation result to obtain a 256 gray level gray image.

[0112] After completing the decoding of the incident position of the photons, the photons are mapped to the gray image to support real-time or post-processing imaging display, which facilitates users to intuitively observe and analyze the detection results, and improves the practicability and interactivity of the system.

[0113] The present application effectively smooths the inevitable small differences on the hardware through software algorithm processing. This means that even if a detector with slightly larger machining tolerance and lower cost is used, high-quality imaging results can be obtained through the calculation imaging method of the present application. This greatly improves the practicability and economy of the calculation imaging method.

[0114] The present application optimizes the imaging performance of the detector at the software algorithm level, reduces the stringent requirements for hardware machining precision and consistency, and reduces the production and processing cost of the detector and the cost of later equipment debugging and maintenance, which is conducive to promoting the wide application of this type of detector in the field of weak target detection, astronomical observation and the like.

[0115] The calculation imaging method of the present application does not depend on a specific hardware structure and can be applied to various single-photon detectors with intersecting strip anodes. Users can adjust parameters such as anode period according to actual needs, and has good universality and scalability.

[0116] The imaging of the cross strip anode single photon detector can be regarded as the accumulation of the incident photon position after the photon emitted by the target is coded by the detector and decoded by the host computer. The photon emitted by the target is emitted in the form of an electron cloud after passing through the photocathode and the microchannel plate of the detector, and a charge signal is generated on the cross strip anode. After being processed by the subsequent circuit, the charge signal is submitted to the host computer for imaging by using a decoding algorithm. The difference between different decoding algorithms lies in the processing method of the data output after the circuit. As can be seen from Figure 3 the imaging result calculated by using the imaging calculation method of the present application has no obvious distortion, while the imaging result calculated by using the traditional incident position decoding algorithm has obvious distortion. Therefore, the imaging calculation method of the present application is superior to the traditional incident position decoding algorithm.

[0117] It should be understood that the steps can be reordered, added or deleted using the various forms of flow shown above. For example, the steps described in the present application can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions of the present application can be achieved, which are not limited herein.

[0118] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent replacement and improvement within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A computational imaging method for a cross-strip anode single-photon detector, wherein the cross-strip anode comprises a set of anode strips extending along a first direction and another set of anode strips extending along a second direction, characterized in that, The computational imaging method includes the following steps: S1: Under full field-of-view illumination, acquire the output signal generated by the cross-strip anode single-photon detector in response to each photon incident event; photon incident events with output signal amplitude within a preset effective range are recorded as effective photon incident events; count the number of effective photon incident events for each anode strip and the total output signal amplitude of all effective photon incident events for each anode strip; and calculate the average output signal amplitude of each anode strip and the total average output signal amplitude of the cross-strip anodes. S2: Calculate the correction factor for each anode bar based on the average output signal amplitude of each anode bar and the total average output signal amplitude of the cross-shaped anodes, and establish the mapping relationship between each anode bar and the corresponding correction factor; S3: When imaging the target, acquire the original output signal of each anode bar; according to the mapping relationship established in step S2, correct the original output signal of each anode bar, take the data whose amplitude of the corrected output signal is within the preset effective range as the effective signal amplitude data, and input the effective signal amplitude data into the Gaussian algorithm to calculate the incident position coordinates of a single photon incident event. S4: Map all incident position coordinates to a mapping matrix of a preset size, stretch the number of photons in each interval of the mapping matrix to 256 gray levels, and generate and display the final imaging result.

2. The computational imaging method for the cross-strip anode single-photon detector according to claim 1, characterized in that, In step S1, the formula for calculating the average output signal amplitude of each anode bar is: ； in, Indicates the first i The average output signal amplitude of each anode bar Indicates the first i The total output signal amplitude of all effective photon incident events of the anode strip. Indicates the first i The first anode bar k The output signal amplitude of a valid photon incident event Indicates the first i The effective photon incident events recorded by each anode bar N This represents the total number of anode bars.

3. The computational imaging method for the cross-strip anode single-photon detector according to claim 1, characterized in that, In step S1, the total average output signal amplitude of the crossbar anodes The calculation formula is: ； in, This represents the total number of all valid photon incident events counted by the crossbar anode. This represents the total output signal amplitude for all valid photon incident events at the crossbar anode. Indicates the first i The total output signal amplitude of all effective photon incident events of the anode strip. Indicates the first i The first anode bar k The output signal amplitude of a valid photon incident event Indicates the first i Each anode bar records the effective photon incident events.

4. The computational imaging method for the cross-strip anode single-photon detector according to claim 1, characterized in that, In step S2, the correction factor for each anode bar The calculation formula is: ； in, Indicates the first i The average output signal amplitude of each anode bar This represents the total average output signal amplitude of the crossbar anodes. Indicates the first i The number of valid photon incident events recorded by each anode bar tends to be infinite.

5. The computational imaging method for a cross-strip anode single-photon detector according to claim 1, characterized in that, In step S2, the mapping relationship between each anode bar and its corresponding correction factor is as follows: ； in, i Indicates the anode bar number, i =1,2,…, N , N This represents the total number of anode bars. Indicates the first i The effective photon incident events recorded by each anode bar This indicates the correction factor corresponding to the anode bar number.

6. The computational imaging method for a cross-strip anode single-photon detector according to claim 1, characterized in that, In step S3, the original output signal of each anode bar is corrected by dividing the original output signal amplitude by the correction factor of the corresponding anode bar.

7. The computational imaging method for a cross-strip anode single-photon detector according to claim 1, characterized in that, In step S3, the formula for calculating the incident position coordinates for each photon incident event using the Gaussian algorithm is as follows: ； ； in, This represents the coordinates of the first direction position of the photon incident on the intersecting bar anodes. This represents the coordinates of the second direction position of the photon incident on the intersecting bar anodes. This indicates the period of the intersecting strip anodes in the first direction. This indicates the period of the intersecting strip anodes in the second direction. This indicates the position of the maximum charge value in the first direction. j The amount of charge collected by each anode bar Indicates the first direction. j - The amount of charge collected by one anode bar, Indicates the first direction. j The amount of charge collected by +1 anode bar, This indicates the location of the maximum charge value in the second direction. t The amount of charge collected by each anode bar Indicates the second direction of the first t - The amount of charge collected by one anode bar, Indicates the second direction of the first t The amount of charge collected by +1 anode bar.

8. The computational imaging method for a cross-strip anode single-photon detector according to claim 1, characterized in that, In step S4, the incident position coordinates are set as follows: The corresponding position coordinates in the mapping matrix are ,but The calculation formula is: ； ； in, m Indicates the number of anode bars in the first direction. n Indicates the number of anode bars in the second direction. size This indicates the preset size of the mapping matrix.

9. The computational imaging method for a cross-strip anode single-photon detector according to claim 1, characterized in that, In step S4, the mapping matrix is ​​composed of different intervals, each interval corresponding to a sub-region of the field of view within the detection field of view, and the number of incident photons in each sub-region of the field of view is recorded.

10. The computational imaging method for a cross-strip anode single-photon detector according to claim 1, characterized in that, In step S4, the specific process of stretching the photon count of each interval in the mapping matrix to 256 gray levels is as follows: First, traverse the mapping matrix to find the interval with the highest number of photons, and denote the number of photons in that interval as . n max ; Then, divide the number of photons in each interval by... n max Obtain the normalized result for each interval. Finally, the normalization result of each interval is multiplied by 256 to obtain a grayscale image with 256 gray levels.

Images