Single photon avalanche diode array detection method and device and medium

Abstract

The invention relates to a single photon avalanche diode array detection method and device and a medium, and the method comprises the steps: S1, setting the size of a data window, and dividing a pixel array into a plurality of window units; step S2, obtaining TDC data of each pixel; s3, based on the first bit of the TDC data of each pixel in the window unit, judging whether the number of effective pixels in the window unit exceeds a pre-configured threshold number m or not, if yes, executing the step S4, and otherwise, executing the step S5; s4, judging whether the effective pixels with the same first n bits of the TDC data exist in the window units or not, and selecting the TDC data of all or part of the effective pixels; s5, outputting the TDC data of all effective pixels or not outputting the TDC data; and S6, obtaining a detection result according to the output TDC data. Compared with the prior art, the method has the advantages of improving the speed and the like.

Description

Technical Field

[0001] This invention relates to the field of lidar sensors, and in particular to a method, apparatus and medium for detecting single-photon avalanche diode arrays. Background Technology

[0002] Single-photon detection technology, as an important branch of optical sensing, has received widespread attention and in-depth research in recent years due to the rapid development of photonics, semiconductor processes, and electronic technologies. Single-photon avalanche diode arrays (SPADs) are photodetectors based on the avalanche multiplication effect, capable of achieving single-photon-level detection sensitivity. Due to their high sensitivity and high temporal resolution in single-photon detection, they are widely used in low-light environment imaging, 3D LiDAR, medical imaging, quantum communication, and other fields. With advancements in process technology and the demands of different detection scenarios, the scale of SPADs has evolved from tens of pixels to hundreds of thousands or even millions of pixels, achieving higher resolution and larger fields of view.

[0003] The imaging process of a traditional single-photon avalanche diode array mainly includes several steps: photon detection, signal conversion, data readout, and image reconstruction. First, incident photons are focused by an optical system onto individual pixels in the single-photon avalanche diode array. Each time a single photon hits a pixel, it triggers the avalanche multiplication effect, and the avalanche current is converted into a digital pulse signal. A counter or time-to-digital converter within each pixel counts the number of single-photon events or the timing of these events, obtaining the raw data for each pixel. Subsequently, this data is sequentially transmitted to an external processor via a traditional row-by-row readout circuit according to a fixed timing sequence. The processor performs operations such as histogram accumulation, multi-frame fusion, or noise correction on the acquired pixel data to reconstruct a two-dimensional intensity image or a three-dimensional depth image. While this traditional imaging mode is simple in structure and easy to implement, the data volume increases rapidly with the scale of the single-photon avalanche diode array. The row-and-column scanning readout method makes data transmission bandwidth and processing speed bottlenecks, limiting further improvements in high frame rates and real-time imaging performance. Furthermore, single-photon events exhibit strong randomness and sparsity in both space and time, with most pixels experiencing no events at most points in time. Therefore, traditional readout methods transmit a large amount of invalid data, severely wasting bandwidth and power resources. Improving data transmission efficiency, reducing redundancy, lowering power consumption, and rapidly extracting valid information when reading large amounts of data to ensure the system's real-time performance and reliability are key challenges in current single-photon detection technology.

[0004] While some existing technologies offer the option of using correlation detection to streamline the output, such methods typically involve hardware design to combine multiple pixels into a macropixel. This requires redesigning the hardware for different application scenarios, limiting their applicability. Furthermore, the comparison of macropixels is mostly divided into two categories: valid and invalid. This can introduce significant errors, and under certain harsh conditions, a large amount of invalid interference TDC data will still be used for subsequent application layer processing, resulting in limited speed improvements. Summary of the Invention

[0005] The purpose of this invention is to provide a single-photon avalanche diode array detection method, device, and medium, which is based on data correlation detection, can quickly extract effective information from the pixel array, suppress noise interference, significantly improve the imaging frame rate, and adapt to various detection scenarios without redesigning the hardware.

[0006] The objective of this invention can be achieved through the following technical solutions: A detection method based on a single-photon avalanche diode array includes: Step S1: Set the data window size to W×W and divide the pixel array into multiple window units; Step S2: Obtain TDC data for each pixel. The TDC data is a multi-bit data sequence corresponding to the detection time window. The first bit indicates whether an avalanche triggering event is detected in the entire detection time window. The remaining bits correspond to each time slot of the detection time window. If an avalanche triggering event is detected in any time slot, the corresponding bit in the TDC data is set to 1. If no avalanche triggering event is detected in any time slot, the corresponding bit in the TDC data is set to 0. Step S3: Based on the first bit of the TDC data of each pixel in the window unit, determine whether the number of valid pixels in the window unit exceeds the pre-configured threshold number m. If yes, proceed to step S4; otherwise, proceed to step S5. If the first bit of the TDC data of a pixel indicates that an avalanche trigger event has been detected, then the pixel is a valid pixel. Step S4: Determine whether there are valid pixels in the window cell whose first n bits of TDC data are the same, and select all or part of the valid pixels of TDC data based on the determination result; Step S5: Output TDC data for all valid pixels or do not output TDC data depending on the detection scene; Step S6: Obtain the detection results based on the output TDC data.

[0007] In step S5, if the main occluding objects in the detected scene are distributed in a discrete pattern, then the TDC data of all valid pixels is output; if the main occluding objects in the detected scene are distributed continuously, then no TDC data is output.

[0008] Step S4 includes: Determine whether there are any valid pixels in the window unit whose first n bits of TDC data are the same. If yes, mark the valid pixels whose first n bits are the same as matching pixels and execute the first filtering step. Otherwise, execute the second filtering step. First filtering step: Output TDC data of all matching pixels or output TDC data of all valid pixels according to the detection scene; The second filtering step is to randomly output the TDC data of m valid pixels according to the detection scene, or not to output TDC data.

[0009] In the first filtering step, if the main occluding objects in the detected scene are distributed in a discrete pattern, the TDC data of all valid pixels is output; if the main occluding objects in the detected scene are distributed continuously, the TDC data of all matching pixels is output.

[0010] Step S4 includes: Determine whether there are valid pixels in the window unit whose first n bits of TDC data are the same. If yes, execute the first discrimination step; otherwise, execute the second filtering step. First discrimination step: Determine whether the number of matching pixels in the window exceeds the pre-configured threshold number m. If yes, output the TDC data of all matching pixels; otherwise, execute the third filtering step. The third filtering step: output the TDC data of all matching pixels according to the detection scene, or randomly output the TDC data of mk valid pixels when outputting the TDC data of all matching pixels, where k is the number of matching pixels; The second filtering step is to randomly output the TDC data of m valid pixels according to the detection scene, or not to output TDC data.

[0011] In the second filtering step, if the main occluding objects in the detected scene are distributed in a discrete pattern, then the TDC data of m effective pixels are randomly output; if the main occluding objects in the detected scene are distributed continuously, then no TDC data is output.

[0012] In the third filtering step, if the main occluding objects in the detected scene are distributed in a discrete pattern, the TDC data of mk effective pixels are randomly output while outputting the TDC data of all matching pixels. If the main occluding objects in the detected scene are distributed continuously, the TDC data of all matching pixels are output.

[0013] The length of the data window is the common divisor of the length and width of the pixel array.

[0014] A single-photon avalanche diode array detection device includes a memory, a processor, and a program stored in the memory, wherein the processor executes the program to implement the method described above.

[0015] A storage medium having a program stored thereon, which, when executed, implements the method described above.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. On the one hand, setting the first bit of the TDC data as a marker indicates whether an avalanche trigger event was detected throughout the detection time window, thus greatly improving efficiency in determining effective pixels. On the other hand, by setting a data window and making judgments based on the number of effective pixels and correlation, effective information in the pixel array can be extracted quickly, reducing the output of invalid data, thereby significantly improving data processing speed and imaging frame rate. Simultaneously, this method implements correlation detection in software, eliminating the need for hardware redesign, offering strong adaptability, and reducing system bandwidth and power consumption requirements.

[0017] 2. By dynamically adjusting the data output strategy according to the distribution (discrete or continuous) of occluded objects in the detection scene, more data is retained in discrete distribution scenes to improve accuracy, and output is reduced in continuous distribution scenes to save resources, thereby optimizing the performance balance of the system in different environments.

[0018] 3. By introducing the concept of matching pixels and filtering steps, highly correlated pixel data can be identified more accurately, effectively suppressing noise interference and improving data quality. Simultaneously, a hierarchical filtering mechanism ensures efficient data selection and avoids redundant processing.

[0019] 4. When matching pixels exist, the system selects to output all valid pixels or matching pixels based on the scene distribution, further enhancing scene adaptability: ensuring data integrity under discrete distribution and prioritizing the output of relevant data under continuous distribution, thereby improving detection accuracy and system robustness.

[0020] 5. By determining whether the number of matched pixels exceeds the threshold and adjusting the output accordingly (such as supplementing random data), the problem of data overload or insufficiency is avoided, ensuring that the output data is representative and improving the reliability and stability of the detection results.

[0021] 6. When there are no matching pixels, data is output randomly or not at all according to the scene distribution, which effectively reduces the transmission of invalid data and further optimizes bandwidth utilization and power efficiency. In particular, it can significantly reduce the impact of noise in continuous occlusion scenes.

[0022] 7. The introduction of the distinction between the first n bits and the consistency of the data filtering strategy has elevated the data filtering strategy from the simple "whether there is an event" to the intelligent level of "whether the event is related". This not only achieves efficient data compression, greatly improves processing speed and reduces bandwidth power consumption, but more importantly, it significantly improves the quality and reliability of the final detection results through precise noise suppression and signal enhancement. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the overall structure of the present invention; Figure 2 This is a schematic diagram of the data correlation detection module of the present invention; Figure 3 This is a schematic diagram of the relevant detection unit logic in Mode 1 of the present invention; Figure 4 This is a schematic diagram of the relevant detection unit logic in Mode 2 of the present invention; Figure 5 This is a schematic diagram of the relevant detection unit logic in Mode 3 of the present invention; Figure 6 This is a schematic diagram illustrating an example of the relevant detection unit in Mode 1 of the present invention; Figure 7 This is a schematic diagram illustrating an example of the relevant detection unit in Mode 2 of the present invention; Figure 8 This is a schematic diagram illustrating an example of the relevant detection unit in Mode 3 of the present invention; Figure 9 This is a schematic diagram of the main steps of the method of the present invention. Detailed Implementation

[0024] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0025] A single-photon avalanche diode array detection method, implemented based on data correlation detection, such as... Figure 9 As shown, it includes: Step S1: Set the data window size to W×W and divide the pixel array into multiple window units; In this embodiment, as Figure 1As shown in the figure, it includes: an M×N detection pixel array, a pixel data validity detection circuit, and a data compression module. The pixel data validity detection circuit performs validity detection on the TDC data of each pixel in the array. The TDC data is a multi-bit data sequence corresponding to the detection time window, and the first bit indicates whether an avalanche trigger event is detected during the entire detection time window. The remaining bits respectively correspond to the time slots of the detection time window. If an avalanche trigger event is detected in any time slot, the corresponding bit in the TDC data is set to 1. If no avalanche trigger event is detected in any time slot, the corresponding bit in the TDC data is set to 0; In this embodiment, if an avalanche trigger event is detected during the entire detection time window, the first bit of the TDC data is set to 1, and vice versa, it is set to 0.

[0026] For a single-photon avalanche diode array of M×N scale, a multi-bit timing circuit is designed in each pixel to collect the TDC data of the photon flight time. When the single-photon avalanche diode array operates in the 3D windowed detection mode, the validity detection is performed on the TDC data of each pixel in the array. The first bit of the TDC data of the pixel is set as the FLAG valid flag bit, and its value is 0 or 1. When the FLAG valid flag bit is 0, it indicates that no event trigger has occurred in this pixel within the detection window time, marking the data as an invalid signal; when the FLAG valid flag bit is 1, it indicates that an event trigger has occurred in this pixel within the detection window time, and the data is a photon arrival signal or an avalanche signal triggered by dark count, indicating that the data is a valid signal.

[0027] The length of the data window size is the greatest common divisor of the length and width of the pixel array, such as Figure 2 As shown in the figure, the data correlation detection module of the embodiment is described. For the original data of the M×N pixel array, since M is generally greater than N, the size of the detection data window is set to W×W (1 < W ≤ N). When W = 2, the matching detection is simultaneously performed on the TDC data of 4 pixels in each 2×2 small array window. When W = 3, the matching detection is simultaneously performed on the TDC data of 9 pixels in each 3×3 small array window, and so on. Therefore, the number K of relevant detection units required is N / W, which can achieve the fast parallel detection of the pixel array data.

[0028] Step S2: Obtain the TDC data of each pixel; Step S3: Based on the first bit of the TDC data of each pixel in the window unit, determine whether the number of valid pixels in the window unit exceeds the pre-configured threshold number m. If so, execute step S4; otherwise, execute step S5. Among them, if the first bit of the TDC data of a pixel indicates that an avalanche trigger event is detected, then this pixel is a valid pixel; Step S4: Determine whether there are valid pixels in the window cell whose first n bits of TDC data are the same, and select all or part of the valid pixels of TDC data based on the determination result; In some embodiments, step S4 includes: Determine whether there are any valid pixels in the window unit whose first n bits of TDC data are the same. If yes, mark the valid pixels whose first n bits are the same as matching pixels and execute the first filtering step. Otherwise, execute the second filtering step. First filtering step: Output TDC data of all matching pixels or output TDC data of all valid pixels according to the detection scene; The second filtering step is to randomly output the TDC data of m valid pixels according to the detection scene, or not to output TDC data.

[0029] In the first filtering step, if the main occluding objects in the detected scene are distributed in a discrete pattern, the TDC data of all valid pixels is output; if the main occluding objects in the detected scene are distributed continuously, the TDC data of all matching pixels is output.

[0030] In other embodiments, step S4 includes: Determine whether there are valid pixels in the window unit whose first n bits of TDC data are the same. If yes, execute the first discrimination step; otherwise, execute the second filtering step. First discrimination step: Determine whether the number of matching pixels in the window exceeds the pre-configured threshold number m. If yes, output the TDC data of all matching pixels; otherwise, execute the third filtering step. The third filtering step: output the TDC data of all matching pixels according to the detection scene, or randomly output the TDC data of mk valid pixels when outputting the TDC data of all matching pixels, where k is the number of matching pixels; The second filtering step is to randomly output the TDC data of m valid pixels according to the detection scene, or not to output TDC data.

[0031] In the second filtering step, if the main occluding objects in the detected scene are distributed in a discrete pattern, then the TDC data of m effective pixels are randomly output; if the main occluding objects in the detected scene are distributed continuously, then no TDC data is output.

[0032] In the third filtering step, if the main occluding objects in the detected scene are distributed in a discrete pattern, the TDC data of mk effective pixels are randomly output while outputting the TDC data of all matching pixels. If the main occluding objects in the detected scene are distributed continuously, the TDC data of all matching pixels are output.

[0033] Step S5: Output the TDC data of all valid pixels according to the detection scenario or do not output the TDC data; Among them, if the main occluding objects in the detection scenario are distributed in a discrete regular pattern, the TDC data of all valid pixels is output. If the main occluding objects in the detection scenario are continuously distributed, the TDC data is not output.

[0034] As Figures 3 to 5 shown, the logic of the relevant detection units in various working modes of the embodiment is described. When the relevant detection unit of this embodiment works in Mode 1, two parameters, the data detection window size W (1 < W ≤ N) and the valid data number threshold m (m > 1), need to be set, and then the number of valid data in the W×W data detection window is judged. If the number of valid data < m, all the valid data in the data detection window are output or no data is output at this time; if the number of valid data ≥ m, all the valid data in the data detection window are output or m valid data are randomly selected from these valid data and output at this time. When the relevant detection unit of this embodiment works in Mode 2, three parameters, the data detection window size W (1 < W ≤ N), the valid data number threshold m (m > 1), and the data matching bit number threshold n, need to be set, and then the number of valid data in the W×W data detection window is judged. If the number of valid data < m, all the valid data in the data detection window are output or no data is output at this time. If the number of valid data ≥ m, it is further judged whether there are valid data with the same first n bits in the data window. If so, these matching data are output or all the valid data are output; if not, m valid data are randomly selected from all the valid data in the data detection window and output or no data is output at this time. When the relevant detection unit of this embodiment works in Mode 3, three parameters, the data detection window size W (1 < W ≤ N), the valid data number threshold m (m > 1), and the data matching bit number threshold n, need to be set, and then the number of valid data in the W×W data detection window is judged. If the number of valid data < m, all the valid data in the data detection window are output or no data is output at this time. If the number of valid data ≥ m, it is further judged whether there are valid data with the same first n bits in the data window. If not, m valid data are randomly selected from all the valid data in the data detection window and output or no data is output at this time; if so, it is further judged whether the number of matching data in the window ≥ m. If the number of matching data in the window ≥ m, these matching valid data are output. If the number of matching data in the window < m, only the matching data are output or the matching data are output and several valid data in the window are selected to make a total of m data output.

[0035] As Figures 6 to 8The following describes examples of related detection units operating in various modes of the embodiments. The data detection window in the example is 2×2, with a total of 4 data points for related detection. For the related detection unit example in Mode 1, in the 2×2 data detection window, PIXEL1 is valid data 1100, PIXEL2 is valid data 1010, PIXEL3 is invalid data 1010, and PIXEL4 is valid data 1000. When the threshold for the number of valid data points m=2, since there are 3 valid data points in the window, all three valid data points (PIXEL1, PIXEL2, and PIXEL4) can be output, or PIXEL1 and PIXEL4 can be randomly selected from the 3 valid data points for output. The remaining data points are not output and are considered invalid (all zeros). When the threshold for the number of valid data points m=4, since there are only 3 valid data points in the window, all three valid data points (PIXEL1, PIXEL2, and PIXEL4) can be output, or none of the data can be output, which is considered invalid (all zeros). For the example of the detection unit in Mode 2, when PIXEL1 is valid data 1101, PIXEL2 is valid data 0110, PIXEL3 is invalid data 1010, and PIXEL4 is valid data 1100 in the 2×2 data detection window, and the threshold for the number of valid data is set to m=2 and the threshold for the number of matching bits is n=2, since there are 3 valid data in the window and the first 2 bits of PIXEL1 and PIXEL4 are the same, all three valid data (PIXEL1, PIXEL2, and PIXEL4) can be output, or only PIXEL1 and PIXEL4 can be output. L4 The two matched data are invalid all-zero data if the rest are not output. When PIXEL1 is valid data 1100, PIXEL2 is valid data 0110, PIXEL3 is invalid data 1010, and PIXEL4 is valid data 1000 in the 2×2 data detection window, and the threshold for the number of valid data is set to m=2 and the threshold for the number of matching bits is n=2, since the first 2 bits of the 3 valid data in the window are different, 2 valid data can be randomly selected for output and the rest can be left unoutput as invalid all-zero data, or none of the data can be output as invalid all-zero data.For the example of the detection unit in Mode 3, when PIXEL1 in the 2×2 data detection window is valid data 1100, PIXEL2 is valid data 1110, PIXEL3 is valid data 1110, and PIXEL4 is valid data 1000, and the threshold for the number of valid data is set to m=3 and the threshold for the number of matching bits is n=2, since there are 4 valid data in the window and the first 2 bits of PIXEL1, PIXEL2, and PIXEL3 are the same, 3 matching data can be output, and the remaining data is not output, which is invalid all-zero data; ... PIXEL4 is valid data 1000, PIXEL4 is valid data 1000, PIXEL2 is valid data 1110, PIXEL3 is valid data 1110, PIXEL4 is valid data 1000, PIXEL4 is valid data 1000, PIXEL2 is valid data 1110, PIXEL3 is valid data 1110, PIXEL4 is valid data 1000, PIXEL2 is valid data 1110, PIXEL3 is valid data 1110, PIXEL IXEL1 is valid data 1100, PIXEL2 is valid data 0110, PIXEL3 is valid data 1010, and PIXEL4 is valid data 1000. When the threshold for the number of valid data is set to m=3 and the threshold for the number of matching bits is n=2, since the first 2 bits of PIXEL3 and PIXEL4 in the window are the same, the matched PIXEL3 and PIXEL4 data can be output, or the matched PIXEL3 and PIXEL4 data can be output and one valid data can be randomly selected for output, for a total of 3 data. The remaining data is not output, which is invalid all-zero data.

[0036] Step S6: Obtain the detection results based on the output TDC data.

[0037] In this embodiment, a criterion is introduced to determine whether there are valid pixels within a window unit whose first n bits of TDC data are identical. This enables intelligent and precise noise filtering, improving the signal-to-noise ratio. Dark counts caused by ambient light, thermal noise, etc., are random and uncorrelated, and occur discretely in time. Therefore, the probability that the TDC data (especially the first n bits representing precise timestamps) of different pixels are completely identical is extremely low. Photons reflected from the same laser pulse arrive at multiple adjacent pixels in the array almost simultaneously. The events detected by these pixels are highly correlated in time, so the first n bits of their TDC data (representing coarse to fine time information) are very likely to be identical or highly similar.

[0038] By searching for groups of pixels with the same first n positions, the system can intelligently identify pixel clusters that are highly likely to be triggered by the same real event (such as a laser echo). This means: We can prioritize retaining these high-confidence data.

[0039] It can decisively filter out those isolated, irrelevant "effective pixels" (which are likely noise).

[0040] This directly improves the signal-to-noise ratio at the data source, laying a solid foundation for the subsequent generation of high-quality, high-precision depth images or photon count images.

[0041] Furthermore, this application upgrades the evaluation criteria from validity to relevance, achieving a balance between data compression and quality assurance. Traditional methods may only determine whether a pixel is "valid" (i.e., whether an event has occurred) and then output the data of all valid pixels. This is effective in sparse scenarios, but in complex or high-noise scenarios, it outputs a large amount of invalid or low-value noise data, wasting bandwidth. This application adds a more advanced criterion of "relevance" to the initial "valid / invalid" screening. When there are too many valid pixels (potentially containing noise) within a window, this criterion acts as a stricter "filter," outputting only the pixel data with relevance, thereby significantly compressing the amount of data that needs to be output. This compression is not indiscriminate. It sacrifices unreliable, isolated noise data, retaining high-quality, relevant signal data. This achieves "efficient compression while ensuring data quality," avoiding sacrificing accuracy for speed.

[0042] Furthermore, in scenes detecting object edges or those with fine structures, laser echoes may simultaneously trigger multiple adjacent pixels. The first n bits of the TDC data of these pixels are identical. This criterion ensures that these crucial data representing the object's contour are fully preserved, thereby better retaining the image's edge information and spatial resolution.

[0043] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A single photon avalanche diode array detection method, characterized in that, The method comprises the following steps: Step S1: setting a data window size of WxW, and dividing the pixel array into multiple window units; Step S2: obtaining TDC data of each pixel, wherein the TDC data is a sequence of multiple bits corresponding to a detection time window, and the first bit indicates whether an avalanche trigger event is detected in the entire detection time window, and the remaining bits correspond to each time slot of the detection time window, if an avalanche trigger event is detected in any time slot, the corresponding bit in the TDC data is 1, and if an avalanche trigger event is not detected in any time slot, the corresponding bit in the TDC data is 0; Step S3: judging whether the number of valid pixels in the window unit exceeds a preconfigured threshold number m based on the first bit of the TDC data of each pixel in the window unit, if yes, executing step S4, otherwise, executing step S5, wherein if the first bit of the TDC data of a pixel indicates that an avalanche trigger event is detected, the pixel is a valid pixel; Step S4: judging whether there is a valid pixel with the same first n bits of TDC data in the window unit, and selecting the TDC data of all or part of the valid pixels based on the judgment result; Step S5: outputting the TDC data of all valid pixels or not outputting the TDC data according to the detection scene; Step S6: obtaining a detection result according to the output TDC data.

2. The method of claim 1, wherein the method further comprises: In step S5, if the main shielding object in the detection scene is distributed in a discrete regular pattern, the TDC data of all valid pixels is output, and if the main shielding object in the detection scene is distributed continuously, the TDC data is not output.

3. The method of claim 1, wherein the method further comprises: The step S4 comprises: judging whether there is a valid pixel with the same first n bits of TDC data in the window unit, if yes, marking the valid pixel with the same first n bits of TDC data as a matching pixel, and executing a first filtering step, otherwise, executing a second filtering step; the first filtering step: outputting the TDC data of all matching pixels or outputting the TDC data of all valid pixels according to the detection scene; the second filtering step: randomly outputting the TDC data of m valid pixels or not outputting the TDC data according to the detection scene.

4. The method of claim 3, wherein the step of detecting a photon is performed by a single photon avalanche diode array. In the first filtering step, if the main shielding object in the detection scene is distributed in a discrete regular pattern, the TDC data of all valid pixels is output, and if the main shielding object in the detection scene is distributed continuously, the TDC data of all matching pixels is output.

5. The method of claim 1, wherein the method further comprises: The step S4 comprises: judging whether there is a valid pixel with the same first n bits of TDC data in the window unit, if yes, executing a first discrimination step, otherwise, executing a second filtering step; the first discrimination step: judging whether the number of matching pixels in the window unit exceeds a preconfigured threshold number m, if yes, outputting the TDC data of all matching pixels, otherwise, executing a third filtering step; the third filtering step: outputting the TDC data of all matching pixels according to the detection scene, or randomly outputting the TDC data of m-k valid pixels in the case of outputting the TDC data of all matching pixels, wherein k is the number of matching pixels. The second filtering step: randomly outputting TDC data of m valid pixels or not outputting TDC data according to the detection scene.

6. The method of claim 3, wherein the step of detecting a photon is performed by a single photon avalanche diode array. In the second filtering step, if the main blocking objects in the detection scene are distributed in a discrete regular pattern, TDC data of m valid pixels is randomly outputted, and if the main blocking objects in the detection scene are distributed in a continuous pattern, no TDC data is outputted.

7. The method of claim 5, wherein the step of detecting a photon is performed by a single photon avalanche diode array. In the third filtering step, if the main blocking objects in the detection scene are distributed in a discrete regular pattern, TDC data of m-k valid pixels is randomly outputted in the case of outputting TDC data of all matched pixels, and if the main blocking objects in the detection scene are distributed in a continuous pattern, TDC data of all matched pixels is outputted.

8. The method of claim 1, wherein the method further comprises: The length of the data window size is the greatest common divisor of the length and width of the pixel array.

9. A single photon avalanche diode array detection device comprising a memory, a processor, and a program stored in the memory, wherein the program comprises the following steps of: receiving a signal from a single photon avalanche diode array; determining a number of photons in the signal; and determining a number of photons in a plurality of signals received from the single photon avalanche diode array. The processor implements the method of any one of claims 1-8 when executing the program.

10. A storage medium having stored thereon a program, characterized by The program implements the method of any one of claims 1-8 when executed.

Images