CN115826075B - Device and method for identifying strong and weak daytime light background targets - Google Patents
Device and method for identifying strong and weak daytime light background targets Download PDFInfo
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Abstract
According to the daytime strong and strong sunlight background dark and weak target recognition device and method, light beams enter the secondary mirror (2) after being reflected by the primary mirror (1), then enter the spectroscope (6) after being incident by the secondary mirror (2), light beams in a visible light wave band are reflected to the visible light detector (7) through the spectroscope (6), light beams in a short-wave infrared wave band are transmitted to the short-wave infrared detector (8) through the spectroscope (6), the synchronous trigger (9) controls the visible light detector (7) and the short-wave infrared detector (8) to ensure exposure at the same middle moment and simultaneously transmit the light beams to the image processing unit (10), the image processing unit (10) completes modeling of the sunlight background in the short-wave infrared wave band, and then the actually measured short-wave infrared target images are combined to obtain target extraction results.
Description
Technical Field
The application relates to the technical field of optics, in particular to a device and a method for identifying a target with strong daytime, dark background and weak daytime.
Background
With the rapid development of space science and technology, the number of artificial celestial bodies in space is increased sharply, so that the number of in-orbit artificial satellites exceeds 19000, and the method has very important significance for real-time and accurate tracking measurement and identification of the artificial satellites. The conventional foundation photoelectric detection system can only work at night or in the morning and evening due to the influence of strong daytime light background in the daytime, and the positioning accuracy and detection timeliness of the target star are seriously influenced. Therefore, the device and the method for effectively suppressing the background noise of the sky light and effectively detecting the dim target star in the daytime scene are very necessary.
In response to the above-mentioned needs, related solutions currently existing are as follows:
chinese patent CN 1815258A (publication No. 20060809) proposes a scanning galvanometer-based optoelectronic imaging tracking system. The scanning galvanometer is utilized to form view field offset, and the suppression of the sunlight background noise is realized according to the characteristic of huge view field and variable frequency aberration of a target signal and a background signal.
Chinese patent CN 101685162A (publication No. 20100331) proposes a daytime star detecting device. The device adopts the spectral filtering method and the polarization method to detect the target star in the cloudless sky background, thereby improving the detection performance of the star in the daytime.
Chinese patent CN 110888177A (publication No. 20200317) proposes a detection device for realizing extraction of a strong background and dark and weak space target by using a shearing interferometer. The shearing interferometer is used for realizing the periodic reciprocating motion of the shearing interference fringes, so that the frequency modulation of the target optical signal is realized, and finally the modulated target signal is detected by the weak signal detection equipment, and the influence of main noise including the sunlight background is restrained, so that the detection of the dark and weak target signal is realized.
The target signal modulation methods such as scanning galvanometer, polarization, spectral filtering, shearing interference and the like adopted in the prior art can cause target energy loss of different degrees while enhancing the signal to noise ratio, so that the detection capability of a telescope system is improved limited, and the application requirements of dark and weak space target monitoring under the strong daytime and daytime light background cannot be met at present.
Disclosure of Invention
In view of this, it is necessary to provide a detection device and an identification method for satisfying the requirements of monitoring application of dim and weak space targets under strong daytime and daytime light background, aiming at the defects existing in the prior art.
In order to solve the problems, the following technical scheme is adopted in the application:
one of the purposes of the application provides a daytime strong and sunlight background dark and weak target recognition device, which comprises a telescope main optical unit (100), a detector unit (200) and an image processing unit (10), wherein the telescope main optical unit (100) comprises a main mirror (1) and a secondary mirror (2), the detector unit (200) comprises a spectroscope (6), a visible light detector (7), a short wave infrared detector (8) and a synchronous trigger (9), the synchronous trigger (9) is electrically connected with the visible light detector (7) and the short wave infrared detector (8), and the image processing unit (10) is electrically connected with the visible light detector (7) and the short wave infrared detector (8); wherein:
the light beam enters the secondary mirror (2) after being reflected by the primary mirror (1), then enters the spectroscope (6) after being incident by the secondary mirror (2), the light beam in the visible light wave band is reflected to the visible light detector (7) by the spectroscope (6), the light beam in the short wave infrared wave band is transmitted to the short wave infrared detector (8) by the spectroscope (6), the synchronous trigger (9) controls the visible light detector (7) and the short wave infrared detector (8) to ensure the same middle moment exposure and simultaneously transmits the same to the image processing unit (10), the image processing unit (10) utilizes a visible light sky light background signal to complete short wave infrared wave band sky light background modeling, and then combines the actually measured short wave infrared target image to obtain a target extraction result.
In some embodiments, the primary mirror (1) and the secondary mirror (2) form a cassegrain structure, and the telescope primary optical unit (100) further comprises a secondary mirror light shielding stop (3) arranged at the periphery of the secondary mirror (2), a primary mirror cylinder light shielding ring (4) arranged at the periphery of the primary mirror (1), and a primary mirror light shielding cylinder (5) arranged at the central position of the primary mirror (1).
In some embodiments, the spectroscope (6) is designed by 400 nm-900 nm high reflection and 900 nm-1700 nm high transmission spectroscope.
In some of these embodiments, the visible light detector (7) is arranged in an out-of-focus position of the optical system.
In some of these embodiments, the image processing unit (10) comprises an offline background scaling module and an online object detection module, wherein:
the off-line background calibration module generates a random brightness background light source by utilizing an integrating sphere, the visible light detector (7) and the short-wave infrared detector (8) are exposed simultaneously under the action of the synchronous trigger (9), and then the image processing unit (10) is combined to record the image data of the visible light detector (7) and the short-wave infrared detector (8) to form a deep convolutional neural network model training set;
when the online target detection module detects an online target, a strong-sky-light background dark-weak target image enters the visible light detector (7) and the short-wave infrared detector (8) through the spectroscope (6) respectively, then the visible light image is input into the trained deep convolutional neural network model by the aid of the image processing unit (10) to generate a sky-light background image corresponding to the short-wave infrared detector (8), and then the sky-light background image is combined with the short-wave infrared detector (8) image to remove the background, so that final extraction of the target image is realized.
In some of these embodiments, the structure of the deep convolutional neural network model comprises: the device comprises a feature extraction layer, a feature mapping layer and a background reconstruction layer, wherein:
the feature extraction layer is used for extracting a plurality of features from an input visible light image, and the formula is as follows:
wherein:
representing an input image +.>
Output +.>
Personal feature map->
Representing the convolution of the image +.>
Represents a convolution kernel where the convolution kernel dimension is +.>
，/>
Representation->
A dimension offset vector;
the feature mapping layer is used for realizing nonlinear mapping between the visible light image feature vector and the short wave infrared image feature vector, and the formula is expressed as follows:
in the method, in the process of the invention,
represents a convolution kernel where the convolution kernel dimension is +.>
The amount is->
,/>
Indicating the layer->
A dimension offset vector;
the background reconstruction layer is used for generating a short-wave infrared background model with a mapping relation with a visible light image, and the formula is expressed as follows:
in the above
A background model image representing the final output, the convolution kernel dimension is +.>
The amount is->
,/>
Indicating the layer->
And (5) maintaining the offset vector.
In some embodiments, the online object detection module has the mathematical expression:
in the method, in the process of the invention,
shortwave infrared image representing measured target signal, < >>
Representing a short-wave infrared daylight background image generated with a visible light image,/for example>
Is the final target signal image.
The second object of the present application is to provide a method for identifying a target with strong daytime and dark background, which comprises the following steps:
the light beam enters the secondary mirror (2) after being reflected by the primary mirror (1), and then enters the spectroscope (6) after being incident by the secondary mirror (2);
the light beam of the visible light wave band is reflected to the visible light detector (7) through the spectroscope (6), and the light beam of the short wave infrared wave band is transmitted to the short wave infrared detector (8) through the spectroscope (6);
the synchronous trigger (9) controls the visible light detector (7) and the short-wave infrared detector (8) to ensure exposure at the same intermediate moment and simultaneously transmits the exposure to the image processing unit (10);
the image processing unit (10) utilizes visible light sky light background signals to complete sky light background modeling of short wave infrared wave bands, and then combines actual measurement short wave infrared target images to obtain target extraction results.
By adopting the technical scheme, the application has the following beneficial effects:
the utility model provides a daytime strong sunlight background dark and weak target recognition device and recognition method, light beam is through get into after the reflection of primary mirror (1) secondary mirror (2), again warp secondary mirror (2) incidence gets into spectroscope (6), the light beam of visible light wave band warp spectroscope (6) reflection extremely visible light detector (7), the light beam of short wave infrared band warp spectroscope (6) transmission extremely short wave infrared detector (8), synchronous trigger (9) control visible light detector (7) with short wave infrared detector (8) are in order to guarantee same intermediate moment exposure to simultaneously transmit to image processing unit (10), image processing unit (10) utilize visible light sunlight background signal to accomplish short wave infrared band sunlight background modeling, and then combine short wave infrared target image obtains the target extraction result, and above-mentioned device and method have utilized the visible light wave band and the infrared band of target signal simultaneously, utilize visible light wave band realization sunlight background noise and the daytime that can improve the detection power of detecting by a wide margin when not losing target short wave infrared signal energy.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the embodiments of the present application or the description of the prior art will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic structural diagram of a device for identifying objects with strong daytime light and dark background and weak daytime light provided in embodiment 1 of the present application.
Fig. 2 is a schematic diagram of an offline background calibration process of the daytime strong and weak background target recognition device provided in embodiment 1 of the present application.
Fig. 3 is a flowchart of a daytime strong and background dark and weak target recognition algorithm provided in embodiment 1 of the present application.
Fig. 4 is a schematic structural diagram of a deep convolutional neural network model used in the daytime strong and daytime background dark and weak target recognition algorithm provided in embodiment 1 of the present application.
In the figure: 1. the device comprises a main mirror, a secondary mirror 3, a secondary mirror light shielding diaphragm, a main mirror cylinder 4, a light shielding ring 5, a main mirror light shielding cylinder 6, a spectroscope 7, a visible light detector 8, a shortwave infrared detector 9, a synchronous trigger 10, an image processing unit 11 and an integrating sphere
Detailed Description
Embodiments of the present application are described in detail below, examples of which are illustrated in the accompanying drawings, wherein the same or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present application and are not to be construed as limiting the present application.
In the description of the present application, it should be understood that the terms "upper," "lower," "horizontal," "inner," "outer," and the like indicate an orientation or a positional relationship based on that shown in the drawings, and are merely for convenience of description and simplification of the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present application.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples.
Example 1
Referring to fig. 1 and fig. 2, a device for identifying a strong daytime light background and a weak daytime light background according to an embodiment of the present application includes a telescope main optical unit 100, a detector unit 200, and an image processing unit 10. Specific implementations of the various components are described in detail below.
The primary mirror 1 and the secondary mirror 2 in the telescope main optical unit 100 form a cassegrain structure, and the telescope main optical unit 100 further comprises a secondary mirror light shielding stop 3 arranged at the periphery of the secondary mirror 2, a primary mirror cylinder light shielding ring 4 arranged at the periphery of the primary mirror 1 and a primary mirror light shielding cylinder 5 arranged at the center of the primary mirror 1.
It can be understood that the primary mirror 1 and the secondary mirror 2 adopt a cassegrain structure, and stray light is inhibited by the secondary mirror aperture 3, the primary mirror cylinder light blocking ring 4 and the secondary mirror light blocking cylinder 5, so that the influence of the stray light on the rear-end image processing unit is reduced. The telescope main optical unit 100 is mainly responsible for the collection and transmission of target signals and the suppression of stray light outside the field of view, and the target signals are reflected to the spectroscope 6 by the primary mirror and the secondary mirror, so as to enter the rear-end combined related image processing unit.
The detector unit 200 comprises a spectroscope 6, a visible light detector 7, a short-wave infrared detector 8 and a synchronous trigger 9, wherein the synchronous trigger 9 is electrically connected with the visible light detector 7 and the short-wave infrared detector 8.
Specifically, after the light beam passes through the telescope main optical unit 100, 400 nm-900 nm wave band target signals are reflected to the visible light detector 7 by the spectroscope 6, 900-1700 nm wave band target signals are transmitted to the short wave infrared detector 8 by the spectroscope, and the two detectors are controlled by the synchronous trigger 9 to ensure the same intermediate moment exposure and simultaneously transmitted to the joint related image processor 10.
Further, the visible light detector 7 is located at the out-of-focus position of the optical system so as to diverge the dark and weak target signals, thereby reducing the influence of the target signals on the detection of the background of the sky light.
It will be appreciated that the beam splitters and visible light detectors used in this embodiment are not limited thereto and may be replaced with, for example, mid-infrared, long-wave infrared band beam splitters and photodetectors.
The image processing unit 10 is electrically connected with the visible light detector 7 and the short-wave infrared detector 8.
It can be understood that the method for detecting the target signal in the visible light band and the short wave infrared band separately is adopted, and the target signal energy is utilized to the maximum extent.
The working mode of the device for identifying a strong daytime, strong background and weak background according to the embodiment 1 is as follows:
the light beam enters the secondary mirror (2) after being reflected by the primary mirror (1), then enters the spectroscope (6) after being incident by the secondary mirror (2), the light beam in the visible light wave band is reflected to the visible light detector (7) by the spectroscope (6), the light beam in the short wave infrared wave band is transmitted to the short wave infrared detector (8) by the spectroscope (6), the synchronous trigger (9) controls the visible light detector (7) and the short wave infrared detector (8) to ensure the same middle moment exposure and simultaneously transmits the same to the image processing unit (10), the image processing unit (10) utilizes a visible light sky light background signal to complete short wave infrared wave band sky light background modeling, and then combines the actually measured short wave infrared target image to obtain a target extraction result.
In some embodiments, the image processing unit 10 is divided into two working modes of offline background calibration and online target detection, and the main functions of the two working modes are to realize nonlinear mapping from a visible light band sky light background signal to a short wave infrared band sky light background signal based on a deep convolutional neural network model. And on the basis again, generating a final target image by combining the measured signal image of the short wave infrared detector. The integrating sphere 11 is mainly used for generating background light sources with different brightness as training samples of the neural network model in an offline background calibration process, and a schematic diagram of the calibration process is shown in fig. 2.
The off-line background calibration module generates a random brightness background light source by utilizing an integrating sphere, the visible light detector (7) and the short-wave infrared detector (8) are exposed simultaneously under the action of the synchronous trigger (9), and then the image processing unit (10) is combined to record the image data of the visible light detector (7) and the short-wave infrared detector (8) to form a deep convolutional neural network model training set;
when the online target detection module detects an online target, a strong-sky-light background dark-weak target image enters the visible light detector (7) and the short-wave infrared detector (8) through the spectroscope (6) respectively, then the visible light image is input into the trained deep convolutional neural network model by the aid of the image processing unit (10) to generate a sky-light background image corresponding to the short-wave infrared detector (8), and then the sky-light background image is combined with the short-wave infrared detector (7) image to remove the background, so that final extraction of the target image is realized.
Referring to fig. 3, the structure of the deep convolutional neural network model includes: the device comprises a feature extraction layer, a feature mapping layer and a background reconstruction layer, wherein:
the feature extraction layer is used for extracting a plurality of features from an input visible light image, and the formula is as follows:
wherein:
representing an input image +.>
Output +.>Personal feature map->
Representing the convolution of the image +.>
Represents a convolution kernel where the convolution kernel dimension is +.>
，/>
Representation->
A dimension offset vector;
the feature mapping layer is used for realizing nonlinear mapping between the visible light image feature vector and the short wave infrared image feature vector, and the formula is expressed as follows:
in the method, in the process of the invention,
represents a convolution kernel where the convolution kernel dimension is +.>
The amount is->
,/>
Indicating the layer->
A dimension offset vector;
the background reconstruction layer is used for generating a short-wave infrared background model with a mapping relation with a visible light image, and the formula is expressed as follows:
in the above
A background model image representing the final output, the convolution kernel dimension is +.>
The amount is->
,/>
Indicating the layer->
And (5) maintaining the offset vector.
In this embodiment, the deep convolutional neural network model activation function used in the present invention selects a ReLU function, and the model structure parameters are:
，/>
. And training the network model by taking the cut 200000 visible light, shortwave infrared background images with 480-480 resolution as a training sample set.
It can be understood that the nonlinear mapping from the visible light band sky light background to the short wave infrared sky light background is realized by using the deep convolutional neural network model, and the short wave infrared image sky light background is removed without causing the loss of target energy.
In some embodiments, the online object detection module has the mathematical expression:
in the middle of
Shortwave infrared image representing measured target signal, < >>
Representing a short-wave infrared sky-light background image generated using a visible light image,/for example>
Is the final target signal image.
According to the daytime strong and daytime strong background and weak target recognition device provided by the embodiment 1, the visible light wave band and the short wave infrared wave band of the target signals are utilized, modeling and rejection of the sunlight background noise are realized by utilizing the visible light wave band while the target short wave infrared signal energy is not lost, and the daytime detection capability of the foundation photoelectric detection equipment can be greatly improved.
Example 2
The embodiment also provides a recognition method of the daytime strong and daytime light background dark and weak target recognition device, which comprises the following steps:
step S110: the light beam enters the secondary mirror (2) after being reflected by the primary mirror (1), and then enters the spectroscope (6) after being incident by the secondary mirror (2);
step S120: the light beam of the visible light wave band is reflected to the visible light detector (7) through the spectroscope (6), and the light beam of the short wave infrared wave band is transmitted to the short wave infrared detector (8) through the spectroscope (6);
step S130: the synchronous trigger (9) controls the visible light detector (7) and the short-wave infrared detector (8) to ensure exposure at the same intermediate moment and simultaneously transmits the exposure to the image processing unit (10);
step S140: the image processing unit (10) utilizes visible light sky light background signals to complete sky light background modeling of short wave infrared wave bands, and then combines actual measurement short wave infrared target images to obtain target extraction results.
The detailed working steps of the recognition method of the recognition device for the strong daytime and dark background and weak background can be added in the embodiment 1, and are not repeated here.
According to the method for identifying the strong daytime and strong daytime background and weak daytime and provided by the embodiment 2 of the application, the visible light wave band and the short wave infrared wave band of the target signals are utilized, modeling and removing of the background noise of the daytime are realized by utilizing the visible light wave band while the energy of the target short wave infrared signals is not lost, and the daytime detection capability of the foundation photoelectric detection equipment can be greatly improved.
It will be understood that the technical features of the above-described embodiments may be combined in any manner, and that all possible combinations of the technical features in the above-described embodiments are not described for brevity, however, they should be considered as being within the scope of the description provided in the present specification, as long as there is no contradiction between the combinations of the technical features.
The foregoing description of the preferred embodiments of the present application has been provided for the purpose of illustrating the general principles of the present application and is not meant to limit the scope of the present application in any way. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application, and other embodiments of the present application, which may occur to those skilled in the art without the exercise of inventive faculty, are intended to be included within the scope of the present application, based on the teachings herein.
Claims (5)
1. The device is characterized by comprising a telescope main optical unit (100), a detector unit (200) and an image processing unit (10), wherein the telescope main optical unit (100) comprises a main mirror (1) and a secondary mirror (2), the detector unit (200) comprises a spectroscope (6), a visible light detector (7), a short wave infrared detector (8) and a synchronous trigger (9), the synchronous trigger (9) is electrically connected with the visible light detector (7) and the short wave infrared detector (8), the visible light detector (7) is arranged at a defocusing position of an optical system, and the image processing unit (10) is electrically connected with the visible light detector (7) and the short wave infrared detector (8); wherein:
the light beam enters the secondary mirror (2) after being reflected by the primary mirror (1), then enters the spectroscope (6) after being incident by the secondary mirror (2), the light beam in the visible light wave band is reflected to the visible light detector (7) by the spectroscope (6), the light beam in the short wave infrared wave band is transmitted to the short wave infrared detector (8) by the spectroscope (6), the synchronous trigger (9) controls the visible light detector (7) and the short wave infrared detector (8) to ensure the same middle moment exposure and simultaneously transmits the same to the image processing unit (10), and the image processing unit (10) completes short wave infrared wave band astronomical background modeling by utilizing a visible light astronomical background signal and then combines the actually measured short wave infrared target image to obtain a target extraction result;
the image processing unit (10) comprises an offline background scaling module and an online target detection module, wherein:
the off-line background calibration module generates a random brightness background light source by utilizing an integrating sphere, the visible light detector (7) and the short-wave infrared detector (8) are exposed simultaneously under the action of the synchronous trigger (9), and then the image processing unit (10) is combined to record the image data of the visible light detector (7) and the short-wave infrared detector (8) to form a deep convolutional neural network model training set;
when the online target detection module detects an online target, a strong-sky background dark-weak target image enters the visible light detector (7) and the short-wave infrared detector (8) through the spectroscope (6) respectively, then the visible light image is input into a trained deep convolutional neural network model by combining the image processing unit (10) to generate a natural-sky background image corresponding to the short-wave infrared detector (8), and then the natural-sky background image is combined with the short-wave infrared detector (8) image to remove the background, so that the final extraction of the target image is realized;
the structure of the deep convolutional neural network model comprises: the device comprises a feature extraction layer, a feature mapping layer and a background reconstruction layer, wherein:
the feature extraction layer is used for extracting a plurality of features from an input visible light image, and the formula is as follows:
wherein:
representing an input image +.>
Output +.>
Personal feature map->
Representing the convolution of the image +.>
Represents a convolution kernel where the convolution kernel dimension is +.>
，/>
Representation->
A dimension offset vector;
the feature mapping layer is used for realizing nonlinear mapping between the visible light image feature vector and the short wave infrared image feature vector, and the formula is expressed as follows:
in the method, in the process of the invention,
represents a convolution kernel where the convolution kernel dimension is +.>
The amount is->
,/>
Indicating the layer->
A dimension offset vector;
the background reconstruction layer is used for generating a short-wave infrared background model with a mapping relation with a visible light image, and the formula is expressed as follows:
in the above
A background model image representing the final output, the convolution kernel dimension is +.>
The amount is->
,/>
Representing the layer
And (5) maintaining the offset vector.
2. The daytime strong and daytime light background dark and weak target recognition device according to claim 1, wherein the primary mirror (1) and the secondary mirror (2) form a cassegrain structure, and the telescope primary optical unit (100) further comprises a secondary mirror light shielding screen (3) arranged at the periphery of the secondary mirror (2), a primary mirror cylinder light shielding ring (4) arranged at the periphery of the primary mirror (1) and a primary mirror light shielding cylinder (5) arranged at the central position of the primary mirror (1).
3. The daytime strong and daytime strong background dark and weak target recognition device according to claim 1, wherein the spectroscope (6) is designed by adopting a 400 nm-900 nm high-reflection 900nm high-transmission light-splitting film system.
4. The daytime strong and daytime light background dark and weak target recognition device according to claim 1, wherein the online target detection module has the following mathematical expression:
in the method, in the process of the invention,
shortwave infrared image representing measured target signal, < >>
Representing a short-wave infrared daylight background image generated with a visible light image,/for example>
Is the final target signal image.
5. A method for identifying a daytime strong and background and dim target identification device according to claim 1, comprising the steps of:
the light beam enters the secondary mirror (2) after being reflected by the primary mirror (1), and then enters the spectroscope (6) after being incident by the secondary mirror (2);
the light beam of the visible light wave band is reflected to the visible light detector (7) through the spectroscope (6), and the light beam of the short wave infrared wave band is transmitted to the short wave infrared detector (8) through the spectroscope (6);
the synchronous trigger (9) controls the visible light detector (7) and the short-wave infrared detector (8) to ensure exposure at the same intermediate moment and simultaneously transmits the exposure to the image processing unit (10);
the image processing unit (10) utilizes visible light sky light background signals to complete sky light background modeling of short wave infrared wave bands, and then combines actual measurement short wave infrared target images to obtain target extraction results.
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