Non-line-of-sight imaging method, device and system based on spectrum domain

Abstract

The present application provides a non-line-of-sight imaging method, device and system based on the spectrum domain. The method includes: obtaining a photon count-time distribution histogram at each sampling point set on the intermediate wall according to the reflected photon statistics; preprocessing the photon count-time distribution histogram at each of the sampling points to obtain spectrum space data; transforming the spectrum space data into image spectrum data; filtering the image spectrum data; and transforming the filtered image spectrum data into image data of the non-line-of-sight scene. The above method can improve the resolution and quality of the reconstructed image.

Description

Technical Field

[0001] The present application relates to the technical field of optical non-line-of-sight imaging, and in particular to a non-line-of-sight imaging method, device and system based on a spectrum domain. Background Art

[0002] Traditional visual technology can only image areas within the field of vision, while non-line-of-sight imaging technology can bypass obstacles and image hidden scenes behind them. Non-line-of-sight imaging technology has many potential applications. For example, in autonomous driving, non-line-of-sight imaging radar can allow cars to predict in advance whether there are cars passing on the other side at corners or intersections, playing a warning role and thus avoiding car accidents; in anti-terrorism applications in urban street fighting, non-line-of-sight imaging radar detects hidden spaces inside through windows or gaps in hiding places, and knows the ambush positions of terrorists in advance, providing powerful assistance in combating criminals and terrorists.

[0003] There are many ways to implement non-line-of-sight imaging, and the sensing methods used in imaging include but are not limited to microwaves, thermal radiation, sound waves, light waves, etc. Among them, microwaves and sound waves have long wavelengths, so the resolution is low, and they can only vaguely identify the outline of a person, and it is difficult to clearly perceive the details. They can usually only be used to locate and track targets; for imaging solutions that use thermal radiation or ambient light from objects, they are easily affected by the environment and object temperature, and are difficult to apply in imaging scenarios under actual conditions.

[0004] Among many detection methods, non-line-of-sight imaging based on optical time-resolved detection has the advantages of long range and not being easily affected by the environment. However, non-line-of-sight imaging based on optical time-resolved detection still faces some performance bottlenecks in practical application. For example, in practical applications, due to the insufficient number of photons collected by the system and insufficient sampling points, the signal-to-noise ratio and resolution of the final imaging result will be reduced; in addition, the large amount of data transmission will also limit the imaging speed or refresh rate. Summary of the invention

[0005] In order to overcome the problems existing in the related art at least to a certain extent, the present application provides a non-line-of-sight imaging method, device and system based on the spectral domain.

[0006] A non-line-of-sight imaging method based on the spectrum domain comprises: calculating a photon count-time distribution histogram at each sampling point set on an intermediate wall according to reflected photons, wherein the reflected photons are photons reflected back by a laser through the intermediate wall for performing pulse light scanning on a non-line-of-sight scene and received by a detector; preprocessing the photon count-time distribution histogram at each sampling point to obtain spectrum space data; transforming the spectrum space data into image spectrum data; filtering the image spectrum data; and transforming the filtered image spectrum data into image data of the non-line-of-sight scene.

[0007] Furthermore, the photon count-time distribution histogram at each of the sampling points is preprocessed to obtain spectrum space data including:

[0008] For each of the sampling points, the position of the direct reflection peak in the statistically obtained photon count-time distribution histogram is set as the time zero point to obtain a time-shifted photon count-time distribution histogram;

[0009] Packing the data in the time-shifted photon count-time distribution histogram at all the sampling points into a three-dimensional matrix; and

[0010] Performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain spectrum space data.

[0011] Furthermore, when a coaxial measurement method is used in the process of performing the pulse light scanning and receiving the reflected photons, a three-dimensional Fourier transform is performed on the three-dimensional matrix to obtain spectrum space data including:

[0012] The three-dimensional matrix is ​​subjected to a three-dimensional Fourier transform to obtain spectrum space data using the following formula:

[0013]

[0014] Among them, Φ(k x ,k y ,ω) represents spectrum space data, (x,y,t) represents the three-dimensional matrix, wherein x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time.

[0015] Furthermore, transforming the spectrum space data into image spectrum data comprises:

[0016] According to the relation The spectrum space data Φ(k x ,k y ,ω) is transformed into k z , get the image spectrum data Φ(k x , ky , k z ).

[0017] Furthermore, when a non-coaxial measurement method is used in the process of performing the pulse light scanning and receiving the reflected photons, a three-dimensional Fourier transform is performed on the three-dimensional matrix to obtain spectrum space data including:

[0018] The three-dimensional matrix is ​​subjected to a three-dimensional Fourier transform to obtain spectrum space data using the following formula:

[0019]

[0020] Among them, τ (k x ,k y ,ω) represents spectrum space data, (x,y,t) represents the three-dimensional matrix, wherein x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time.

[0021] Furthermore, transforming the spectrum space data into image spectrum data comprises:

[0022] According to the following formula, the spectrum space data Ψ τ (k x ,k y ,ω) is transformed into the image spectrum data:

[0023]

[0024] Among them, f (k x ,k y ,ω,z=z v ) represents the image spectrum data,

[0025] Further, filtering the image spectrum data includes:

[0026] The image spectrum data satisfies the relationship The spectral components of k are set to 0, where k rmax Represents the maximum recoverable frequency, and its value is set according to the number of sampling points;

[0027] and / or,

[0028] The image spectrum data satisfies the relationship The spectral component of is set to 0, where the value of θ is set according to the ratio of the scanning range and the object depth;

[0029] and / or,

[0030] The spectrum components in the image spectrum data that satisfy the relationship |k|>λ are set to 0, where |k| represents the size of the spectrum and the value of λ is set according to the signal strength and the system time resolution;

[0031] and / or,

[0032] The spectrum components satisfying the relationship |k|<β in the image spectrum data are set to 0, where |k| represents the size of the spectrum and the value of β is set according to the intensity of the background noise.

[0033] Further, performing inverse Fourier transform on the filtered image spectrum data to obtain image data of the non-viewing scene includes:

[0034] When the coaxial measurement method is used, the filtered image spectrum data is inversely Fourier transformed using the following formula to obtain the image data of the non-viewing scene:

[0035]

[0036] Wherein, Ψ(x, y, z, t) represents the image data of the non-viewing scene, Φ(k x ,k y ,k z ) represents the image spectrum data after filtering;

[0037] When the non-coaxial measurement method is used, the filtered image spectrum data is inversely Fourier transformed using the following formula to obtain the image data of the non-viewing scene:

[0038]

[0039] Among them, f (x, y, z, t) represents the image data of the non-viewing scene, Ψ f (k x ,k y ,ω,z=z v ) represents the image spectrum data after filtering.

[0040] In addition, the present application also provides a non-line-of-sight imaging device based on the spectral domain, including a memory and a processor coupled to the memory, wherein the processor is configured to execute the steps in the above-mentioned non-line-of-sight imaging method based on the spectral domain based on instructions stored in the memory.

[0041] In addition, the present application also provides a non-line-of-sight imaging system based on the spectral domain, including a laser that performs pulsed light scanning on a non-line-of-sight scene through an intermediate wall; a detector that receives reflected photons; and a processor that executes the steps in the above-mentioned non-line-of-sight imaging method based on the spectral domain.

[0042] According to the non-line-of-sight imaging method, device and system based on the spectral domain provided in the embodiment of the present application, the photon count-time distribution histogram at each sampling point set on the intermediate wall is obtained according to the statistics of reflected photons; the photon count-time distribution histogram at each sampling point is preprocessed to obtain spectral space data; the spectral space data is transformed into image spectral data; the image spectral data is filtered; and the filtered image spectral data is transformed into image data of the non-line-of-sight scene. In this way, higher non-line-of-sight imaging quality can be achieved. In the embodiment of the present application, non-line-of-sight imaging is achieved based on the measurement method of photon time resolution, which has strong environmental adaptability, and is compatible with coaxial or non-coaxial measurement methods, and has good robustness; processing is performed based on the spectral domain of the measurement data, and the amount of data required is smaller than that of previous methods. In addition, a spectral filtering method was used to filter out high-frequency noise in the data, thereby improving the signal-to-noise ratio of the reconstructed image; the spectral filtering method was used to correct the temporal and spatial broadening effects of the measured data and suppress the low-frequency components, thereby improving the resolution of the imaging results; in the case of a limited number of scanning points, the spectral filtering method was also used to delete the unmeasurable or erroneous spectral components, thereby realizing the image. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The attached drawings below are part of the specification of the present application, which illustrate embodiments of the present application. The attached drawings together with the description of the specification are used to explain the principles of the present application.

[0044] Figure 1 A non-video imaging scene diagram based on the spectrum domain according to an embodiment of the present application is shown.

[0045] Figure 2 A schematic diagram of a spectral domain-based non-video imaging model according to an embodiment of the present application is shown.

[0046] Figure 3 A schematic flow chart of a non-line-of-sight imaging method based on the spectrum domain according to an embodiment of the present application is shown.

[0047] Figure 4 A photon count-time distribution histogram according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clearly understood, the spirit of the contents disclosed in the present application will be clearly explained with the accompanying drawings and detailed descriptions below. After understanding the embodiments of the contents of the present application, any technician in the relevant technical field can change and modify them according to the techniques taught by the contents of the present application without departing from the spirit and scope of the contents of the present application.

[0049] The exemplary embodiments and descriptions of the present application are used to explain the present application, but are not intended to limit the present application. In addition, elements / components with the same or similar reference numerals used in the drawings and embodiments are used to represent the same or similar parts.

[0050] The terms “first”, “second”, etc. used in this document do not particularly refer to an order or sequence, nor are they used to limit this application. They are only used to distinguish elements or operations described with the same technical terms.

[0051] The words “include,” “including,” “have,” “contain,” etc. used in this document are open-ended terms, meaning including but not limited to.

[0052] As used herein, "and / or" includes any or all combinations of the items described.

[0053] As used herein, “plurality” includes “two” and “more than two”; as used herein, “plurality groups” includes “two groups” and “more than two groups”.

[0054] Certain terms used to describe the present application are discussed below or elsewhere in this specification to provide additional guidance to those skilled in the art regarding the description of the present application.

[0055] Figure 1 A non-video imaging scene diagram based on the spectrum domain according to an embodiment of the present application is shown. Figure 2 A schematic diagram of a non-video imaging model based on the spectrum domain according to an embodiment of the present application is shown, which includes a laser, a galvanometer, a detector and a processor, wherein a time synchronization module is provided between the laser and the detector for time synchronization. Figure 1 and Figure 2 As shown, the laser emits a pulsed laser, which is guided to the intermediate wall by a galvanometer. The pulsed laser is diffusely reflected on the intermediate wall and propagates to the hidden scene. Then, the photon is reflected by the surface of the scene and returns to the intermediate wall. Finally, the photon is diffusely reflected on the wall and returns to be received by the detector. The detector converts the returned photon into an electrical pulse signal. The system measures the time of photon emission and reception to obtain the flight time and distance of the photon. The galvanometer can be used to change the emission direction of the photon and the receiving direction of the detector, so that measurements can be made at different positions on the wall, and finally the image of the hidden scene can be restored.

[0056] The embodiment of the present application provides a non-line-of-sight imaging method based on the spectrum domain, which can improve the resolution and quality of the reconstructed image through an adaptive spectrum filtering algorithm. The method can obtain better signal-to-noise ratio and resolution than the traditional method under the condition of fewer photons and sampling points, and at the same time, can greatly reduce the amount of data required for imaging, thereby solving the bottleneck of data transmission in hardware.

[0057] Figure 3 A non-line-of-sight imaging method based on the spectrum domain according to an embodiment of the present application is shown, including steps S1-S5.

[0058] S1, a photon count-time distribution histogram at each sampling point set on the intermediate wall is obtained based on the reflected photon statistics, wherein the reflected photon is the photon reflected back by a laser through the intermediate wall to perform pulse light scanning on a non-viewing scene and received by a detector.

[0059] First, the laser emits pulsed light, which is guided by a galvanometer to illuminate the intermediate wall. The pulsed light is diffusely reflected on the intermediate wall and propagates to the hidden scene. The laser beam emitted from the laser is reflected by, for example, a galvanometer to the intermediate wall. After the beam interacts with the hidden scene, some photons return to the intermediate wall and are received by, for example, a single-photon detector.

[0060] In one embodiment, the time synchronization module obtains a photon count-time distribution histogram based on the time difference between the light emission and reception times, such as Figure 4 As shown, the horizontal axis is the photon flight time and the vertical axis is the photon count.

[0061] In one embodiment, a 532 nm picosecond pulse laser is used to emit pulsed laser light, a single photon detector is used to detect light signals, and a time-to-digital converter is used to measure time to obtain a photon count-time distribution histogram for each sampling point.

[0062] S2, preprocessing the photon count-time distribution histogram at each sampling point to obtain spectrum space data.

[0063] Specifically, in one embodiment, preprocessing the photon count-time distribution histogram includes S21-S23.

[0064] S21, for each sampling point, setting the position of the direct reflection peak in the statistically obtained photon count-time distribution histogram as time zero, to obtain a time-shifted photon count-time distribution histogram.

[0065] For each sampling point, the position of the direct reflection peak in the photon count-time distribution histogram is moved to the time zero point t=0. The direct reflection peak here refers to the maximum count value in the histogram, and this position is taken as the time zero point. That is, the coordinate zero point of the time axis is redefined in this step.

[0066] S22, packaging the data in the time-shifted photon count-time distribution histogram at all the sampling points into a three-dimensional matrix.

[0067] In one embodiment, the data in the time-shifted photon count-time distribution histogram at all sampling points are packed into a three-dimensional matrix (x, y, t), where x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time.

[0068] Here, according to the grid distribution of the sampling points on the intermediate wall, the two-dimensional histogram data of all the sampling points are packed into a three-dimensional (grid x-axis, grid y-axis, flight time) matrix.

[0069] S23, performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain spectrum space data.

[0070] Specifically, a three-dimensional Fourier transform is performed on the three-dimensional matrix (x, y, t) to obtain spectrum space data.

[0071] Non-line-of-sight imaging can be performed using either a coaxial measurement method or a non-coaxial measurement method. In the coaxial measurement method, the detection point (i.e., the point where the detector scans on the intermediate wall to receive the reflected photons) and the illumination point (i.e., the point where the laser scans on the intermediate wall to emit pulsed light) are scanned together and maintained in overlap. In the non-coaxial measurement method, the detection point is sampled at different positions, and the illumination point is fixed; or the detection point is fixed, and the illumination point is scanned. These two sampling methods correspond to different data conversion methods.

[0072] In one embodiment, when a coaxial measurement method is used, the three-dimensional matrix (x, y, t) is subjected to a three-dimensional Fourier transform to obtain spectrum space data using the following formula:

[0073]

[0074] Among them, Φ(k x ,k y ,ω) represents spectrum space data, (x,y,t) represents a three-dimensional matrix, wherein x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time.

[0075] Specifically, in the formula, Φ(k x ,k y ,ω) is the Fourier transformed function, which describes the characteristics in the frequency domain, where k x and k y is the spatial frequency component, and ω is the temporal frequency component.

[0076] Ψ(x,y,t) is the original time domain or space-time domain function, which is usually a signal or image defined in space (x,y) and time t.

[0077] is a complex exponential function used to represent the modulation in spatial and temporal frequencies, where k x and k y controls the spatial frequency, and ω controls the temporal frequency.

[0078] ∫∫∫Ψ(x,y,t) is a triple integral that represents the integration over the space and time variables x,y,t, computing the Fourier transform in all these dimensions.

[0079] This formula converts the signal Ψ(x, y, t) in the time domain or space-time domain to Φ(k x ,k y ,ω), so as to analyze the characteristics of the signal in space and time frequency.

[0080] In this way, the three-dimensional data (x, y, t) is transformed into the spectrum domain (kx, ky, ω) through Fourier transform, where each spectrum component represents a corresponding plane wave component.

[0081] In one embodiment, when a non-coaxial measurement method is used, the three-dimensional matrix (x, y, t) is subjected to a three-dimensional Fourier transform to obtain spectrum space data using the following formula:

[0082]

[0083] Among them, τ (k x ,k y ,ω) represents the spectrum space data, (x,y,t) represents the three-dimensional matrix, where x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time. In this way, the three-dimensional data (x,y,t) is transformed into the spectrum domain (kx,ky,ω) through Fourier transform.

[0084] S3, transforming the spectrum space data into image spectrum data.

[0085] In one embodiment, when a coaxial measurement method is used, the spectrum spatial data Φ(k x ,k y ,ω) is transformed into image spectrum data including:

[0086] According to the relation Where c represents the speed of light, the spectrum space data Φ(k x ,k y ,ω) is transformed into k z , get the image spectrum data Φ(k x , k y , k z ).

[0087] In one embodiment, when a non-coaxial measurement method is used, the spectrum space data Ψ is converted into τ (k x ,k y ,ω) is transformed into the image spectrum data:

[0088]

[0089] Among them, f (k x ,k y ,ω,z=z v ) represents the image spectrum data,

[0090] In the formula, the first phase factor Used to describe the propagation of the signal at depth z_v. The second phase factor This represents the overall phase shift contained in the spectrum.

[0091] S4, filtering the image spectrum data.

[0092] In non-viewing area measurements, the data spectrum has many defects compared to the real image spectrum, which are caused by detection noise, system time resolution, incomplete sampling, etc. When reconstructing the image, the embodiment of the present application uses spectral filtering to repair the data spectrum, thereby improving the quality of the result.

[0093] In one embodiment, when the sampling points for measurement are very sparse, only a part of the spectrum of the image to be measured can be effectively measured. Therefore, the relationship is satisfied. The spectral components of k are set to 0, that is, the spectral components that cannot be measured or are erroneous are set to 0, where k rmax is an adjustable parameter representing the maximum recoverable frequency, parameter k rmax You can select based on the number of sampling points. The number of sampling points here refers to the number of sampling points set on the intermediate wall. More sampling points can restore higher frequency components.

[0094] In one embodiment, due to the limitation of the scanning range, some areas are difficult to measure well. Therefore, the relationship The spectral components of are set to 0, where θ is an adjustable parameter whose value depends on the ratio of the scanning range and the object depth. The scanning range here refers to the range of the laser to perform pulse light scanning or the detector to receive the reflected photons. The object depth ratio here refers to the relationship between the depth of the object in the image and the depth in the actual space. The larger the scanning range, the larger the value of θ, allowing more spectral cost to be retained.

[0095] In one embodiment, due to the limitation of the time resolution of the non-field of view measurement system, the measured high-frequency component signal will be suppressed and easily submerged in the noise. Therefore, considering the trade-off between image resolution and noise, the high-frequency components with low signal-to-noise ratio are deleted or suppressed, that is, the spectrum components satisfying |k|>λ are set to 0, where |k| can represent the size of the spectrum, and λ is an adjustable parameter, whose value depends on the signal strength and the system time resolution. The signal strength here refers to the signal strength of the received photons. If the number of received photons is greater, the signal strength is greater. The system time resolution here can also be called digital resolution, which refers to the minimum unit of time or time interval that the system can distinguish and record. In a time-correlated single-photon counter device, digital resolution refers to the minimum time unit that can be represented by a digital circuit. Digital resolution determines the accuracy of the system in time measurement. For example, in an embodiment of the present application, if a 532nm picosecond pulse laser is used to emit a pulsed laser, the system can theoretically distinguish the time interval change of 532nm.

[0096] In one embodiment, in order to reduce the influence of background noise and correct the temporal and spatial broadening effect of the measured data, the low-frequency components are suppressed, that is, the spectrum cost satisfying |k|<β is set to 0, thereby sharpening the edge of the image and improving the resolution, where β is an adjustable parameter whose value depends on the background noise intensity. The background noise intensity here refers to the noise of the optoelectronic device itself and the noise that cannot be completely eliminated, such as ambient light noise. The higher the background noise, the smaller the β value.

[0097] By adjusting these parameters, the measured data can be effectively processed and repaired in the spectral domain, thereby improving the quality in the image reconstruction. These steps ensure that the most accurate and high-quality image is recovered from the valid measured data, while taking into account the effects of noise and system resolution.

[0098] The above filtering methods can be executed separately or in any combination according to actual conditions to obtain different filtering effects.

[0099] S5, transforming the filtered image spectrum data into image data of the non-viewing scene.

[0100] In one embodiment, the filtered image spectrum data is subjected to an inverse Fourier transform to obtain the image data of the non-viewing area scene.

[0101] In one embodiment, when the coaxial measurement method is adopted, the image data of the non-viewing scene is obtained by performing an inverse Fourier transform on the filtered image spectrum data using the following formula:

[0102]

[0103] Wherein, Ψ(x, y, z, t) represents the image data of the non-viewing scene, Φ(k x ,k y ,k z ) represents the image spectrum data after filtering.

[0104] In one embodiment, when a non-coaxial measurement method is used, the filtered image spectrum data is inversely Fourier transformed using the following formula to obtain the image data of the non-viewing scene:

[0105]

[0106] Among them, f (x, y, z, t) represents the image data of the non-viewing scene, Ψ f (k x ,k y ,ω,z=z v ) represents the image spectrum data after filtering.

[0107] Specifically, in the formula, (x, y, z, t) is the coordinate in the time domain or the space domain, that is, the frequency domain is converted into the time domain or the space domain, so as to obtain an image of the non-viewing scene.

[0108] In this way, an image of the non-viewing scene can be obtained.

[0109] As described above, in the non-line-of-sight imaging method of the embodiment of the present application, non-line-of-sight imaging is achieved based on a measurement method based on photon time resolution, which has strong environmental adaptability and is compatible with coaxial or non-coaxial measurement methods, and the method has good robustness. In addition, the processing is based on the spectral domain of the measurement data, and the amount of data required is smaller than that of previous methods. In addition, the spectral filtering method filters out high-frequency noise in the data, thereby improving the signal-to-noise ratio of the reconstructed image; the spectral filtering method corrects the temporal and spatial broadening effect of the measurement data, suppresses the low-frequency components, and thus improves the resolution of the imaging results; in the case of a limited number of scanning points, the spectral filtering method deletes the unmeasurable or erroneous spectral components, thereby achieving an image.

[0110] An embodiment of the present application also provides a non-line-of-sight imaging device based on the spectral domain, comprising a memory and a processor coupled to the memory, wherein the processor is configured to execute the steps in the above-mentioned non-line-of-sight imaging method based on the spectral domain based on instructions stored in the memory.

[0111] The embodiment of the present application further provides a non-line-of-sight imaging system based on the spectrum domain, comprising:

[0112] Laser, which scans the non-viewing scene with pulsed light through the intermediate wall;

[0113] a detector, which receives the reflected photons; and

[0114] A processor is used to execute the steps in the above-mentioned non-line-of-sight imaging method based on the spectrum domain.

[0115] The details of each module in this embodiment can be referred to the above method embodiment and will not be repeated here.

[0116] The above description is only an illustrative specific implementation manner of the present application. Without departing from the concept and principle of the present application, any equivalent changes and modifications made by any technician in the field should fall within the scope of protection of the present application.

Claims

1. A non-line-of-sight imaging method based on spectral domain, characterized in that: include: A photon count-time distribution histogram at each sampling point set on the intermediate wall according to reflected photon statistics, wherein the reflected photon is a photon reflected back by a laser through the intermediate wall to perform pulse light scanning on a non-viewing scene and received by a detector; Preprocessing the photon count-time distribution histogram at each sampling point to obtain spectrum space data; transforming the spectrum space data into image spectrum data; filtering the image spectrum data; and The filtered image spectrum data is transformed into image data of the non-viewing scene, The photon count-time distribution histogram at each sampling point is preprocessed to obtain spectrum space data including: For each of the sampling points, the position of the direct reflection peak in the statistically obtained photon count-time distribution histogram is set as the time zero point to obtain a time-shifted photon count-time distribution histogram; Packing the data in the time-shifted photon count-time distribution histogram at all the sampling points into a three-dimensional matrix; and Performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain spectrum space data, Wherein, when a coaxial measurement method is used in the process of performing the pulse light scanning and receiving the reflected photons: Performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain the spectrum space data includes: performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain the spectrum space data by the following formula: Among them, Φ(k x ,k y ,ω) represents spectrum space data, (x,y,t) represents the three-dimensional matrix, wherein x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time. The transforming of the spectrum space data into image spectrum data comprises: according to the relation The spectrum space data Φ(k x ,k y ,ω) is transformed into k z , get the image spectrum data Φ(k x , k y , k z ); When a non-coaxial measurement method is used in the process of performing the pulse light scanning and receiving the reflected photons: Performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain the spectrum space data includes: performing a three-dimensional Fourier transform on the three-dimensional matrix to obtain the spectrum space data by the following formula: Among them, τ (k x ,k y ,ω) represents spectrum space data, (x,y,t) represents the three-dimensional matrix, wherein x represents the x-axis of the intermediate wall, y represents the y-axis of the intermediate wall, and t represents the photon flight time. The step of transforming the spectrum space data into image spectrum data comprises: transforming the spectrum space data Ψ according to the following formula: τ (k x ,k y ,ω) is transformed into the image spectrum data: Among them, f (k x ,k y ,ω,z=z v ) represents the image spectrum data, Wherein, filtering the image spectrum data includes: The image spectrum data satisfies the relationship The spectral components of k are set to 0, where k rmax Represents the maximum recoverable frequency, and its value is set according to the number of sampling points; and / or, The image spectrum data satisfies the relationship The spectral component of is set to 0, where the value of θ is set according to the ratio of the scanning range and the object depth; and / or, The spectrum components in the image spectrum data that satisfy the relationship |k|>λ are set to 0, where |k| represents the size of the spectrum and the value of λ is set according to the signal strength and the system time resolution; and / or, The spectrum components satisfying the relationship |k|<β in the image spectrum data are set to 0, where |k| represents the size of the spectrum and the value of β is set according to the intensity of the background noise.

2. The method according to claim 1, characterized in that Performing an inverse Fourier transform on the filtered image spectrum data to obtain the image data of the non-viewing scene includes: When the coaxial measurement method is used, the filtered image spectrum data is inversely Fourier transformed using the following formula to obtain the image data of the non-viewing scene: Wherein, Ψ(x, y, z, t) represents the image data of the non-viewing scene, Φ(k x ,k y ,k z ) represents the image spectrum data after filtering; When the non-coaxial measurement method is used, the filtered image spectrum data is inversely Fourier transformed using the following formula to obtain the image data of the non-viewing scene: Among them, f (x, y, z, t) represents the image data of the non-viewing scene, Ψ f (k x ,k y ,ω,z=z v ) represents the image spectrum data after filtering.

3. A non-line-of-sight imaging device based on the spectrum domain, characterized in that: The method comprises a memory and a processor coupled to the memory, wherein the processor is configured to execute the steps in the method according to any one of claims 1 to 2 based on instructions stored in the memory.

4. A non-line-of-sight imaging system based on the spectrum domain, characterized in that: include: Laser, which scans the non-viewing scene with pulsed light through the intermediate wall; The detector receives the reflected photons; as well as A processor, configured to execute the steps in the method as claimed in any one of claims 1 to 2.

Images