A DMD-based local imaging method and spectral system

Abstract

The present invention discloses a local imaging method and a spectral system based on DMD, including: S1: Pre-construct an instance segmentation model, which is used to identify the target to be locally imaged before imaging. The instance segmentation model is trained by learning the individual features and boundary information of the target to be locally imaged; S2: Use an imaging device equipped with the instance segmentation model to perform local shooting imaging on the target to be locally imaged. During the shooting process, the imaging device drives the flipping component to flip to a specified position according to the recognition result of the instance segmentation model, adjusts the direction and intensity of the output beam, and then splits the output beam and focuses it, so that each wavelength of light can be clearly imaged, and the local image of the target at any position can be accurately obtained, solving the problems of low data acquisition efficiency and data redundancy caused by the inability of existing spectrometers to perform flexible scanning imaging for specific regions.

Description

Technical Field

[0001] The present invention relates to the field of spectral technology, and more specifically, to a local imaging method and spectral system based on DMD. Background Art

[0002] A spectrometer analyzes the composition and structure of a substance in depth by precisely measuring the absorption, reflection, or emission characteristics of the substance for light of different wavelengths. With its precise analysis ability, spectrometers are widely used in fields such as agricultural monitoring, environmental detection, and medical diagnosis. Currently, most spectrometers use pushbroom imaging technology, where multiple detector arrays scan the target area point by point in the vertical direction to obtain hyperspectral data.

[0003] Existing pushbroom spectrometers usually need to scan the entire target area to obtain hyperspectral data. However, in practical applications, many scenarios only require data from specific areas. Take the orchard scenario as an example. Researchers and fruit farmers usually only focus on the hyperspectral data of fruit tree leaves or fruits to monitor the growth trend of fruit trees, the occurrence of pests and diseases, and evaluate the fruit quality. However, when a spectrometer using pushbroom imaging technology obtains data for a specific target, it inevitably collects data from all areas along the entire scanning path, including a large amount of irrelevant soil, branches, air, etc.

[0004] This acquisition method greatly reduces efficiency. On the one hand, scanning the entire area is time-consuming, laborious, and energy-consuming, which greatly limits the working efficiency in the case of limited resources. On the other hand, a large amount of irrelevant data leads to data redundancy. These redundant data not only occupy a large amount of storage resources, increasing the storage cost, but also significantly increase the computational amount in subsequent data processing and analysis, reducing the analysis speed and accuracy. Therefore, there is an urgent need to develop an imaging system and method that can efficiently and accurately obtain hyperspectral data for specific areas. Summary of the Invention

[0005] In view of the problems in the related art, the present invention proposes a local imaging method and spectral system based on DMD to overcome the above-mentioned technical problems existing in the existing related technologies.

[0006] To this end, the specific technical solutions adopted by the present invention are as follows:

[0007] A local imaging method based on DMD, comprising:

[0008] S1: Pre-build an instance segmentation model. The instance segmentation model is used to identify the target for local imaging before imaging, and the instance segmentation model is trained by learning the individual features and boundary information of the target for local imaging.

[0009] S2: Use an imaging device equipped with an instance segmentation model to perform local imaging on the target to be locally imaged. During the imaging process, according to the recognition result of the instance segmentation model, the imaging device drives the flipping component to flip to the specified position, adjusts the direction and intensity of the output light beam, and then splits the output light beam for focusing, so that light of each wavelength can be clearly imaged, and the local image of the target at any position can be accurately obtained.

[0010] Further, the training of the instance segmentation model includes:

[0011] S1.1: Select images of the target in different regions, under different lighting conditions, at different growth stages, and in different weather conditions, ensuring that the images cover different forms of the target, including single targets, clustered targets, and targets of different sizes and colors;

[0012] S1.2: Perform annotation on the obtained images. For images with more than one target, each target is individually annotated one by one;

[0013] S1.3: Assign class labels to each annotated target;

[0014] S1.4: Divide the annotated target images and their corresponding class labels into a training set, a validation set, and a test set according to a certain ratio, and train to obtain an instance segmentation model.

[0015] Further, use the YOLOv11 deep neural network to train the instance segmentation model.

[0016] A spectral system for local imaging based on DMD, used for the above-mentioned local imaging method based on DMD, includes:

[0017] Model construction module: Pre-construct an instance segmentation model, which is used to identify the target to be locally imaged before imaging. The instance segmentation model is trained by learning the individual characteristics and boundary information of the target to be locally imaged;

[0018] Local imaging module: Use an imaging device equipped with an instance segmentation model to perform local imaging on the target to be locally imaged. During the imaging process, according to the recognition result of the instance segmentation model, the imaging device drives the flipping component to flip to the specified position, adjusts the direction and intensity of the output light beam, and then splits the output light beam for focusing, so that light of each wavelength can be clearly imaged, and the local image of the target at any position can be accurately obtained. Further, the spectral range of the spectrometer covers 200 - 800 nm, and the FWHH resolution is less than 2 nm.

[0019] Further, the imaging device includes an imaging lens, a beam splitter, a visible light camera, a rotatable mirror, a first collimating lens group, a cosine corrector, a DMD, a second collimating lens group, a grating, a focusing lens group, and an imaging element.

[0020] The imaging lens is installed at the starting position of the system optical path. The beam splitter is installed in the focusing optical path of the imaging lens. The beam splitter is in the horizontal direction, and its center is flush with the optical axes of the imaging lens and the DMD. The beam splitter is in the vertical direction, and its center is flush with the optical axis of the visible light camera. The rotatable mirror is installed between the beam splitter and the DMD. The visible light camera is set above the beam splitter. The visible light camera is installed on the optical path in the vertical direction of the beam splitter, and its optical center coincides with the output optical axis in the vertical direction of the beam splitter. The optical center of the rotatable mirror in the vertical direction is flush with the optical axes of the first collimating lens group and the cosine corrector. The cosine corrector is located above the first collimating lens group, and the top of the cosine corrector is exposed outside the imaging device. The DMD is installed horizontally and tilted at a certain angle on one side of the rotatable mirror. The second collimating lens group, the grating, the focusing lens group, and the imaging element are sequentially set above the DMD, and their optical axes coincide with the output optical path of the DMD. The visible light camera, the rotatable mirror, and the imaging element are electrically connected to the main control board. The visible light camera receives commands from the main control board and uploads image data. The main control board sends commands to control whether the rotatable mirror is started. When started, the sunlight entering from the cosine corrector can be collimated and reflected to the DMD exactly. When not started, the sunlight is completely blocked and the light output in the horizontal direction by the beam splitter can reach the DMD. The main control board outputs commands to control the flipping of the DMD. When the galvanometer mirror does not flip on the optical path, the optical signal output by the beam splitter cannot enter the subsequent collimating and beam splitting optical path. When the galvanometer mirror flips, the optical signal output in the horizontal direction by the beam splitter can exactly reach the subsequent collimating and beam splitting optical path through reflection.

[0021] Further, the wavelength response range of the imaging lens is adjusted according to the application scenario.

[0022] Further, an electronic shutter is provided on the optical path transmission side of the imaging lens, and the opening and closing of the electronic shutter control whether the optical signal passes through the imaging lens.

[0023] Further, the beam splitter splits the optical signal image captured by the imaging lens into two beams before focusing. The light intensity ratio of the two beams can be 1:1, 2:8, 4:6, or any other ratio that meets the usage requirements. The beam splitter is in the horizontal direction, and its center is flush with the optical axes of the imaging lens and the DMD. In the vertical direction, its center is flush with the optical axis of the visible light camera.

[0024] Further, the main control board includes at least one computing power chip for coordinating the operation of the system. The main control board conducts data transmission with the computer through cables or Bluetooth.

[0025] Further, the grating, the focusing lens group, and the imaging element are implemented using a single-point spectrometer. The light input port of the single-point spectrometer is installed at the focal position of the second collimating lens group to ensure that the maximum light flux of the incident light is transmitted into the optical fiber for subsequent spectral splitting. The spectrometer internally includes a collimating lens, a grating spectral splitting system, a focusing lens, and a linear array CCD imaging system, which can convert the collected spectral signals into digital data and complete the accurate measurement of spectral information at specific points.

[0026] The beneficial effects of the present invention are as follows:

[0027] 1. This application solves the problems of low data acquisition efficiency and data redundancy caused by the inability of existing spectrometers to flexibly scan and image specific regions.

[0028] 2. This application introduces an automatic calibration function, enabling the system to complete the calibration process more simply without manual intervention. Automatic calibration can effectively ensure the accuracy and consistency of data acquisition, reduce the complexity of operation and the impact of human errors, and at the same time improve the stability and reliability of the system.

[0029] 3. This application uses the column-by-column flipping of the DMD array to replace the traditional grating scanning method, effectively avoiding the influence of vibrations that may occur during line scanning of the spectrometer on the fine optical path. The column-by-column flipping method of the DMD array can precisely control the projection of light, ensuring the stability of the optical path during the scanning process, and further improving the accuracy of spectral data acquisition and the overall performance of the system. Description of the Drawings

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0031] Figure 1 is a schematic structural diagram of a DMD-based local imaging spectral system according to Embodiment 2 of the present invention;

[0032] Figure 2 is a schematic diagram of the position of the rotatable mirror when the DMD-based local imaging spectral system according to Embodiment 2 of the present invention is not started;

[0033] Figure 3 is a schematic diagram of the position of the rotatable mirror when the DMD-based local imaging spectral system according to Embodiment 2 of the present invention is started.

[0034] In the figure:

[0035] 1. Imaging lens; 2. Electronic shutter; 3. Beam splitter; 4. Visible light camera; 5. Rotatable mirror; 6. First collimating lens group; 7. Cosine corrector; 8. DMD; 9. Second collimating lens group; 10. Grating; 11. Focusing lens group; 12. Imaging element; 13. Main control board; 14. Computer. Detailed implementation manner

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention. Embodiment 1

[0037] A local imaging method based on DMD includes:

[0038] S1: Pre-build an instance segmentation model, which is used to identify the target of the required local imaging before imaging. The instance segmentation model is trained by learning the individual features and boundary information of the target of the required local imaging. Specifically, taking the detection of bayberries in an orchard as an example, the training of the instance segmentation model includes:

[0039] S1.1: Take images of bayberries in different regions, different lighting conditions, different growth stages and different weather conditions in the orchard, and take a sufficient number of bayberry images to ensure that the images cover different forms of the target, including single bayberries, clustered bayberries, bayberries of different sizes and colors;

[0040] S1.2: For each bayberry image, carefully outline the contour of each bayberry to ensure the accuracy and integrity of the annotation. Each bayberry instance should be individually annotated. Even for clustered bayberries, they should be separately annotated so that the model can learn the individual features and boundary information of the bayberries;

[0041] S1.3: Assign a class label to each annotated bayberry;

[0042] S1.4: Divide the annotated bayberry images and their corresponding class labels into a training set, a validation set and a test set according to a certain ratio, and use the YOLOv11 deep neural network to train the instance segmentation model. The common division ratio is training set: validation set: test set = 7:2:1, but it can also be adjusted according to the actual situation;

[0043] S2: Use an imaging device equipped with an instance segmentation model to perform local imaging on the target to be imaged locally. During the imaging process, according to the recognition result of the instance segmentation model, the imaging device drives the flipping component to flip to the specified position, adjusts the direction and intensity of the output light beam, then splits the output light beam and focuses it, so that each wavelength of light can be clearly imaged, and the local image of the target at any position can be accurately obtained. Embodiment 2

[0044] Taking the application scenario of detecting the sugar content or diseases of bayberries still on the tree in a bayberry orchard based on hyperspectral data as an example, a spectral system for local imaging based on DMD is implemented by using the local imaging method based on DMD in Embodiment 1, and includes:

[0045] Model construction module: Pre-construct an instance segmentation model, which is used to identify the target to be imaged locally before imaging. The instance segmentation model is trained by learning the individual features and boundary information of the target to be imaged locally;

[0046] Local imaging module: Use an imaging device equipped with an instance segmentation model to perform local imaging on the target to be imaged locally. During the imaging process, according to the recognition result of the instance segmentation model, the imaging device drives the flipping component to flip to the specified position, adjusts the direction and intensity of the output light beam, then splits the output light beam and focuses it, so that each wavelength of light can be clearly imaged, and the local image of the target at any position can be accurately obtained.

[0047] As Figures 1-3 shown, the imaging device includes an imaging lens 1, a beam splitter 3, a visible light camera 4, a rotatable mirror 5, a first collimating lens group 6, a cosine corrector 7, a DMD 8, a second collimating lens group 9, a grating 10, a focusing lens group 11, and an imaging element 12.

[0048] The imaging lens 1 is installed at the starting position of the system optical path. The wavelength response range of the imaging lens 1 is adjusted according to the application scenario. The beam splitter 3 is installed in the focusing optical path of the imaging lens 1. The beam splitter 3 is in the horizontal direction. The beam splitter 3 splits the optical signal image captured by the imaging lens 1 into two beams before focusing. The light intensity ratio of the two beams is adjusted according to the usage requirements. For example, the light intensity ratio of the two beams can be 1:1, 2:8, 4:6 or any other ratio that meets the usage requirements. Its center is aligned with the optical axes of the imaging lens 1 and the DMD 8 in the horizontal direction. In the vertical direction, its center is aligned with the optical axis of the visible light camera 4. An electronic shutter 2 is provided on one side of the optical path transmission of the imaging lens 1. The opening and closing of the electronic shutter 2 control whether the optical signal passes through the imaging lens 1. The visible light camera 4 is arranged above the beam splitter 3. The visible light camera 4 is installed on the optical path in the vertical direction of the beam splitter 3. The optical center coincides with the output optical axis of the beam splitter 3 in the vertical direction and is connected to the main control board 13 through a cable for receiving commands and uploading image data. The rotatable mirror 5 is installed between the beam splitter 3 and the DMD 8. The rotatable mirror 5 is installed horizontally between the beam splitter 3 and the DMD 8. The optical center of the rotatable mirror 5 is aligned with the optical axes of the first collimating lens group 6 and the cosine corrector 7 in the vertical direction and is connected to the main control board 13 through a cable. The main control board 13 sends commands to control whether the rotatable mirror 5 is activated. When activated, it can just reflect the sunlight coming in from the cosine corrector 7 to the DMD 8 after collimation. When not activated, it completely blocks the sunlight and allows the light output in the horizontal direction of the beam splitter 3 to reach the DMD 8. The cosine corrector 7 is located above the first collimating lens group 6. The top of the cosine corrector 7 is exposed outside the imaging device. The DMD 8 is installed horizontally and tilted at a certain angle on one side of the rotatable mirror 5. The DMD 8 is connected to the main control board 13 through a cable and receives the flipping command. When the galvanometer mirror does not flip on the optical path, the optical signal output by the beam splitter 3 cannot enter the subsequent collimating and beam splitting optical path. When the galvanometer mirror flips, the optical signal output in the horizontal direction by the beam splitter 3 can just reach the subsequent collimating and beam splitting optical path through reflection. The second collimating lens group 9, the grating 10, the focusing lens group 11 and the imaging element 12 are arranged in sequence above the DMD 8. The optical axis coincides with the output optical path of the DMD 8 to ensure that the optical signal output by the DMD 8 can accurately enter the subsequent beam splitting and imaging system. At the same time, the imaging element 12 is connected to the main control board 13 through a cable and transmits data to the main control board 13. The main control board 13 includes at least one computing power chip for coordinating the operation of the system. The main control board 13 performs data transmission with the computer 14 through a cable or Bluetooth method.

[0049] It should be noted that all the above optical and electronic components except the computer 14 are installed on the same set of high-strength and high-precision structural parts. The structural parts are made of high-quality materials, and factors such as heat dissipation and anti-interference are considered to ensure the relative positions of all components are stable.

[0050] The imaging principle of the imaging device is as follows:

[0051] As Figure 2 shown, in the initial state of the system, the electronic shutter 2 is not pressed, and the rotatable mirror 5 is not activated. At this time, no optical signal passes through the optical path, and the system enters the dark background signal acquisition mode;

[0052] As Figure 3 shown, when the rotatable mirror 5 is activated, the system enters the ambient light acquisition mode. External light sources such as sunlight are corrected for uniform light intensity by the cosine corrector 7 and collimated by the first collimating lens group 6. After being reflected by the mirror, the light beam will be conducted to the DMD 8. At this time, the main control board 13 precisely controls the DMD 8 to ensure that the light source signal is correctly output to the subsequent optical path;

[0053] After the electronic shutter 2 is pressed, the rotatable mirror 5 is in the non-activated state, and the imaging lens 1 starts to capture the optical signal image of the measured area. The optical signal collected by the imaging lens 1 is split by the beam splitter 3 into two beams of light. One beam of light is collimated and focused onto the visible light camera 4, and the other beam of light passes through the non-activated rotatable mirror 5 and continues to be transmitted to the DMD 8 for subsequent optical processing.

[0054] The pixels of the image captured by the visible light camera correspond to one or several galvanometers of the DMD 8, and are combined with the pre-loaded instance segmentation model through the main control board 13 to perform region recognition and analysis on the captured image in real time. According to the recognition result, the main control board 13 controls the DMD 8 to perform precise pixel flipping operations, by flipping the pixels in the specified area on the DMD 8 column by column, to adjust the direction and intensity of the output light beam. This process is further collimated by the second collimating lens group 9 to ensure that the light beam propagates along the predetermined direction. The light beam regulated by the DMD 8 enters the grating 10, and the light beam split by the grating 10 is precisely focused by the focusing lens group 11 to ensure that the light of each wavelength can be clearly imaged on the imaging element 12;

[0055] The imaging element 12 converts the focused optical signal into an electrical signal and transmits it to the main control board 13 for data processing and storage. The main control board 13 can be used as a temporary data storage, or can be equipped with a model to further analyze and optimize the data according to the preset algorithm. The processed data can be transmitted to the computer 14 through a cable or Bluetooth for in-depth analysis or display. The computer 14 can send down the model algorithm or receive data transmission for subsequent analysis. Example Three

[0056] Compared with the second embodiment, the grating 10, the focusing lens group 11, and the imaging element 12 are implemented using a single-point spectrometer. The light input port of the single-point spectrometer is installed at the focal position of the second collimating lens group 9 to ensure that the maximum light flux of the incident light enters the optical fiber for subsequent spectral splitting. The spectrometer internally includes a collimating lens, a grating spectral splitting system, a focusing lens, and a linear array CCD imaging system, which can convert the collected spectral signals into digital data and complete the accurate measurement of spectral information at specific points. The difference in the imaging method between this embodiment and the second embodiment is that according to the recognition result, the main control board 13 controls the DMD8 to flip sequentially from left to right and from top to bottom. The optical signal output by the DMD8 is focused on the optical fiber interface of the single-point spectrometer by the second collimating lens group 9. After spectral splitting by the single-point spectrometer, the data is transmitted to the main control board 13. Using a single-point spectrometer can significantly reduce the equipment cost, and since the single-point spectrometer uses a linear array detector, the optimization difficulty is much lower than that of an area array detector.

[0057] In summary, for the system instrument, first, it is confirmed that the mirror is closed, and a dark noise data is collected when the shutter is not pressed. Then, the mirror is opened, and the spectral data of the solar ambient light is collected. Next, data is collected, the shutter is pressed, and the light is split into two beams by the beam splitter. After visible light imaging, the visible light image is transmitted to the main control board. The main control board is equipped with an instance segmentation model, and according to the data I pre-trained, the target object is segmented from the image. The target is bayberry, and the image of the bayberry is segmented to obtain a mask or logical matrix, where only the target area is 1 and the rest are 0. The main control board controls the DMD to flip. The DMD galvanometer array corresponds to the visible light pixels, and only the target area, that is, the part with 1, is flipped. Subsequently, it flips column by column or several columns corresponding to one column as a strategy to replace the slit. Finally, spectral data is obtained by spectral splitting and then imaging.

[0058] This application has a flexible local scanning function, which can avoid redundant data generated in traditional full-field scanning, thus significantly improving the scanning efficiency. This function enables the device to perform accurate and local area scanning when needed, reducing unnecessary data acquisition and optimizing the spectral data processing process, thereby saving time and computing resources.

[0059] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A local imaging method based on DMD, characterized in that: include: S1: Pre-build an instance segmentation model, which is used to identify the target of the required local imaging before imaging. The instance segmentation model is trained by learning the individual features and boundary information of the required local imaging target. During the training process, each target is individually labeled and assigned a category label; S2: An imaging device equipped with an instance segmentation model is used to perform local imaging of a target for which local imaging is required. During the imaging process, the imaging device drives the flip component to flip to a specified position according to the recognition result of the instance segmentation model, adjusts the direction and intensity of the output light beam, and then focuses the output light beam after splitting it, so that each wavelength of light can be clearly imaged and a local image of a target at any position can be accurately obtained. The imaging device includes a rotating reflector (5), a DMD (8), an imaging element (12) and a main control board (13). The DMD (8) is installed on a rotatable reflector at a certain angle and is tilted horizontally at a certain angle. On one side of the reflector (5), an imaging element (12) is arranged above the DMD (8). The rotatable reflector (5), the DMD (8) and the imaging element (12) are electrically connected to a main control board (13). The main control board (13) controls the rotation switching system of the rotatable reflector (5) to enter a dark background signal acquisition mode or a spectral data acquisition mode. The main control board (13) controls the DMD (8) to perform a pixel flipping operation. By flipping the pixels of a designated area on the DMD (8) column by column, the direction and intensity of the output light beam are adjusted to ensure that each wavelength of light can be clearly imaged on the imaging element (12).

2. A DMD-based local imaging method according to claim 1, characterized in that: Training of the instance segmentation model involves: S1.1: Select images of targets in different regions, different lighting conditions, different growth stages, and different weather conditions, ensuring that the images cover different forms of targets, including single targets, clustered targets, and targets of different sizes and colors; S1.2: annotate the acquired image with objects, wherein, for an image with more than one object, annotate each object individually; S1.3: Assign a category label to each annotated object; S1.4: Divide the labeled target images and their corresponding category labels into training set, validation set and test set according to a certain ratio to obtain the instance segmentation model.

3. A DMD-based local imaging method according to claim 1, characterized in that: The instance segmentation model is trained using the YOLOv11 deep neural network.

4. A spectral system for local imaging based on DMD, used to implement a local imaging method based on DMD according to any one of claims 1 to 3, characterized in that: include: Model building module: pre-building an instance segmentation model, the instance segmentation model is used to identify the target of the required local imaging before imaging, and the instance segmentation model is trained by learning the individual features and boundary information of the required local imaging target; Local imaging module: An imaging device equipped with an instance segmentation model is used to perform local imaging of the target required for local imaging. During the shooting process, the imaging device drives the flip component to flip to the specified position according to the recognition result of the instance segmentation model, adjusts the direction and intensity of the output light beam, and then focuses the output light beam after splitting it, so that each wavelength of light can be clearly imaged and the local image of the target at any position can be accurately obtained.

5. A spectral system based on local imaging of DMD according to claim 4, characterized in that: The imaging device comprises an imaging lens (1), a beam splitter (3), a visible light camera (4), a rotatable reflector (5), a first collimating lens group (6), a cosine corrector (7), a DMD (8), a second collimating lens group (9), a grating (10), a focusing lens group (11), and an imaging element (12). The imaging lens (1) is installed at the starting position of the system optical path, the beam splitter (3) is installed in the focusing optical path of the imaging lens (1), the center of the beam splitter (3) is aligned with the optical axis of the imaging lens (1) and the DMD (8) in the horizontal direction, the center of the beam splitter (3) is aligned with the optical axis of the visible light camera (4) in the vertical direction, the rotatable reflector (5) is installed between the beam splitter (3) and the DMD (8), the visible light camera (4) is arranged above the beam splitter (3), and the optical center of the rotatable reflector (5) is aligned with the first collimating lens group (6) and the cosine correction lens group (8) in the vertical direction. The optical axis of the corrector (7) is aligned, the cosine corrector (7) is located above the first collimating lens group (6), the top end of the cosine corrector (7) is exposed outside the imaging device, the DMD (8) is installed horizontally at a certain angle on one side of the rotatable reflector (5), the second collimating lens group (9), the grating (10), the focusing lens group (11) and the imaging element (12) are arranged in sequence above the DMD (8), the optical axis coincides with the output optical path of the DMD (8), and the visible light camera (4), the rotatable reflector (5) and the imaging element (12) are electrically connected to the main control board (13).

6. A spectral system based on local imaging of DMD according to claim 5, characterized in that: The wavelength response range of the imaging lens (1) is adjusted according to the application scenario.

7. A spectral system based on local imaging of DMD according to claim 5, characterized in that: An electronic shutter (2) is provided on the optical transmission side of the imaging lens (1), and the switch of the electronic shutter (2) controls whether the optical signal passes through the imaging lens (1).

8. The spectral system based on local imaging of DMD according to claim 5, characterized in that: The beam splitter (3) splits the light signal image captured by the imaging lens (1) into two beams before focusing, and the light intensity ratio of the two beams is adjusted according to usage requirements.

9. The spectral system based on local imaging of DMD according to claim 5, characterized in that: The grating (10), the focusing lens group (11) and the imaging element (12) are implemented using a single-point spectrometer. The light inlet of the single-point spectrometer is installed at the focal position of the second collimating lens group (9). The spectrometer contains a collimating lens, a grating light splitting system, a focusing lens and a linear array CCD imaging system.

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