An imaging spectral adaptive exposure system and method based on exposure parameter sequences

Abstract

This invention discloses an adaptive exposure system and method for imaging spectroscopy based on an exposure parameter sequence, relating to the field of imaging spectrometer technology. The method includes based on pre-selected characteristic exposure parameters P... n (λ′), obtain the spectral image data corresponding to the characteristic wavelength λ′; calculate the mean of the obtained spectral image of the characteristic wavelength λ′ and compare the mean with the set threshold DN′. λ' Output the index n corresponding to the optimal exposure parameter sequence; based on the optimal exposure parameter sequence E n Exposure parameters P corresponding to all detection wavelengths n (λ) Imaging detection is performed at each detection wavelength λ to acquire spectral images of each detection wavelength λ, completing the adaptive exposure operation of the imaging spectrum. The system includes an adaptive exposure parameter control module, optical components, a spectrometer, and a detector. Compared with conventional automatic exposure methods for imaging spectra, this invention improves the spectral acquisition speed, simplifies the calibration steps, reduces the calibration difficulty, and ensures the quantitative accuracy of the acquired spectral data.

Description

Technical Field

[0001] This invention relates to the field of imaging spectrometer technology, and more specifically to an imaging spectral adaptive exposure system and method based on an exposure parameter sequence. Background Technology

[0002] Imaging spectrometers typically employ spectrometers and area array detectors to acquire spatial images of the target at nanometer-level spectral resolution across a continuous wavelength range. This allows for the creation of a unified spectral image cube, enabling analysis and identification of the target based on both its geometric shape and spectral characteristics. Currently, imaging spectroscopy technology is widely used in resource exploration, marine remote sensing, environmental monitoring, and military reconnaissance. However, when detecting targets, the combined effects of the target's radiation characteristics at different wavelengths, as well as the differences in the spectral response characteristics of the optical medium and detector at different wavelengths, result in significant differences in spectral energy across different wavelengths. Using the same exposure parameters (gain and integration time) when acquiring spectra at different wavelengths will lead to substantial data discrepancies, potentially resulting in overexposure (signal amplitude exceeding the detector's quantization range) or underexposure (signal amplitude too low), severely impacting the dynamic range and sensitivity of the data. Adjusting exposure parameters for different wavelengths is one method to address this problem in the field of imaging spectroscopy. For example, Chinese invention patent CN104270575A proposes a method and apparatus for adaptively adjusting the exposure time of an imaging spectrometer. By adjusting the exposure time, the maximum DN value of the acquired spectral image does not exceed the detector's maximum quantization bit depth. However, this patent's exposure parameter adjustment method requires adjusting the exposure time for each frame of the acquired spectral image, resulting in a long processing time. Furthermore, since the calibration accuracy of the spectrometer and the quantitative inversion accuracy of spectral data are important factors in evaluating data quality, this patent's method requires adjusting the exposure parameters during spectral acquisition. Accurate exposure parameters cannot be obtained before acquisition, requiring calibration of the exposure parameters after acquisition or calibration of a large number of exposure parameters before acquisition. This introduces difficulties and uncertainties into the calibration and quantitative inversion of spectral data.

[0003] Therefore, how to adjust the exposure parameters for different wavelengths while ensuring the accuracy of data calibration and quantification, and improving the speed of spectral acquisition, is a current challenge in the field of imaging spectroscopy. Summary of the Invention

[0004] This invention addresses the problems existing in the prior art by providing an imaging spectral adaptive exposure system and method based on exposure parameter sequences.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] An imaging spectral adaptive exposure method based on exposure parameter sequences includes the following steps:

[0007] Step S1: Based on the pre-selected feature exposure parameter P n (λ′), to obtain the spectral image data corresponding to the characteristic wavelength λ′, where the characteristic exposure parameter P n (λ′) represents the exposure parameter corresponding to the characteristic wavelength λ′ in the exposure parameter sequence set E. The exposure parameter sequence set E contains k exposure parameter sequences, and each exposure parameter sequence contains the exposure parameter P corresponding to all detection wavelengths. n (λ);

[0008] Step S2: Calculate the mean value of the digital quantization value DN corresponding to the obtained characteristic wavelength λ′ spectral image. Comparison of means With the set threshold DN′ λ' Based on the comparison results, the index n corresponding to the optimal exposure parameter sequence suitable for the current detection scene is output. The criterion for determining the optimal exposure detection sequence is: mean value. and threshold DN′ λ' The absolute value of the difference between the values ​​is equal to the minimum value; the minimum value is calculated as follows: based on the current exposure parameter number n, the mean value is obtained. With threshold DN′ λ' The difference between them is DN diff The minimum value refers to the difference DN when the exposure parameter number is n+1. diff The difference DN between the exposure parameter number n-1 and the value of the exposure parameter number n-1 diff The difference DN between the current exposure parameter number n and the current exposure parameter number n is DN. diff Large, meaning the difference DN is considered to be when the current exposure parameter number is n. diff It is the minimum value;

[0009] Step S3: Based on the optimal exposure parameter sequence E n Exposure parameters P corresponding to all detection wavelengths n (λ) Imaging detection is performed on each detection wavelength λ to obtain the spectral image of each detection wavelength λ, and the adaptive exposure operation of the imaging spectrum is completed.

[0010] Based on the above technical solution, further, in step S1, the characteristic wavelength λ′ includes the wavelength with the largest spectral response and the wavelength with the smallest spectral response among all wavelengths. The spectral response of the largest wavelength refers to the degree of response to light intensity or light signal at the position of the largest wavelength, and the spectral response of the smallest wavelength refers to the degree of response to light intensity or light signal at the position of the smallest wavelength. It is related to the detector of the imaging spectrometer. Once the detector of the imaging spectrometer is determined, the wavelength with the largest spectral response and the wavelength with the smallest spectral response are obtained. The unit of the characteristic wavelength λ′ is nm.

[0011] Based on the above technical solution, further, in step S2, the mean value of the characteristic wavelength λ′ With threshold DN′ λ' The comparison process is as follows:

[0012] When the mean Greater than the threshold DN′ λ' and mean With threshold DN t If the difference between the two values ​​is greater than the minimum value, then adjust the feature exposure parameter P. n (λ′) is the characteristic exposure parameter P of the characteristic wavelength λ′ corresponding to the lower-level sequence number. n-1 (λ′), where n = n-1, repeat step S1;

[0013] When the mean Less than threshold DN′ λ' and mean With threshold DN′ λ' If the difference between them is greater than the minimum value, then adjust the feature exposure parameter P. n (λ′) is the characteristic exposure parameter P of the characteristic wavelength λ′ corresponding to the next higher sequence number. n+1 (λ′), where n = n + 1, repeat step S1;

[0014] If the mean Equal to threshold DN′ λ' Or, mean With threshold DN′ λ' If the absolute value of the difference is equal to the minimum value, then the index n in the current exposure parameter sequence set E is output.

[0015] Based on the above technical solution, further, in step S2, the mean... The calculation process is as follows: add up the DN values ​​of all pixels in the spectral image and then divide by the number of pixels to obtain the mean value of the spectral image corresponding to the characteristic wavelength λ′.

[0016] Based on the above technical solution, further, in step S2, the characteristic exposure parameter P of the pre-selected characteristic wavelength λ′ is... nThe sequence number n corresponding to (λ′) is the middle sequence number of the total number of exposure parameter sequences k. For example, if there are 10 sequences k = 10, then the pre-selected sequence number n is n = 5.

[0017] Based on the above technical solution, the steps for generating the exposure parameter sequence set E are as follows:

[0018] Step 1: Adjust the amplitude and brightness energy level of the light source to C. Use gain G and integration time T to obtain the spectral image under this amplitude and brightness energy level condition. Initialize the amplitude and brightness energy level C of the light source as the minimum brightness energy level of the light source, and obtain the initial spectral image wavelength λ. s ;

[0019] Step 2: Calculate the wavelength λ of the initial spectral image. s spectral image mean Determine the mean of the spectral image With detection threshold DN t The difference between them is used to determine the integral time T and the gain G.

[0020] Step 3: Record the output integration time T and gain G as the exposure parameters for that wavelength at the current amplitude brightness level, and adjust the wavelength λ of the acquired spectral image. s , so that λ s =λ s +1, repeat steps 1 to 3 until the wavelength λ of the spectral image is reached. s The wavelength λ of the maximum spectral image max Output the exposure parameters obtained corresponding to the wavelengths of each spectral image;

[0021] Step 4: Collect the output exposure parameters and denote them as the exposure parameter sequence E of the light source energy level C. c (λ), adjust the luminance level C of the light source to C+1, and repeat steps 1 to 4 until the luminance level C is the maximum luminance level C of the light source. max Output the exposure parameter sequence E for each brightness level. c The set of (λ) is denoted as

[0022] Based on the above technical solution, further, in step 1, the initial gain G is set to the maximum gain G1 of the detector, and the initial integration time T is set to the minimum integration time T1 of the detector.

[0023] Based on the above technical solution, further, in step 2, the judgment process is as follows:

[0024] If the mean of the spectral image Greater than the detection threshold DN t Reduce the gain G so that G = G-1, repeat step 1, and acquire the spectral image under the light source conditions until the mean of the spectral image is reached. and detection threshold DN t equal;

[0025] If the mean of the spectral image Less than the detection threshold DN t Increase the integration time T so that T = T + 1, and repeat step 1 to obtain the spectral image under the light source conditions until the mean of the spectral image is reached. and detection threshold DN t equal;

[0026] If the mean of the spectral image Equal to the spectral image threshold DN t Then the current integration time T and gain G will be output.

[0027] Based on the above technical solution, further, in step 2, the detection threshold DN t Not greater than the detector's maximum digital quantization value DN max 50%.

[0028] An adaptive exposure system based on an exposure parameter sequence employs an adaptive exposure method based on an exposure parameter sequence. It includes an adaptive exposure parameter control module and an exposure imaging module. The exposure imaging module comprises optics, a beam splitter, and a detector, and is used to acquire spectral images. Light reflected from the target surface enters the adaptive exposure system, is collimated by the optics, and then incident on the beam splitter. The beam splitter separates the polychromatic beam, and the output monochromatic light is converged and incident on the detector. The adaptive exposure parameter control module automatically selects the optimal exposure parameter sequence suitable for the imaging scene from a set of exposure parameter sequences according to the adaptive exposure method, and controls the exposure imaging module to adjust the exposure parameters of spectral images with different characteristic wavelengths, thereby acquiring spectral images with different characteristic wavelengths.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The system and method described in this invention, through a pre-determined sequence of exposure parameters, eliminates the need for individual wavelength-specific exposure parameter determination during spectral acquisition. Instead, it focuses on determining the optimal exposure parameters for the characteristic wavelengths, thereby obtaining the optimal exposure parameter sequence. This enables rapid acquisition of spectral images across all wavelengths, achieving full-wavelength dynamic range and sensitivity. Compared to conventional automatic exposure methods for imaging spectroscopy, this significantly improves spectral acquisition speed. Furthermore, since the exposure parameter sequence is pre-obtained, pre-radiometric calibration of each parameter is possible, eliminating the need for repeated calibration of the imaging spectrometer. This simplifies the calibration process, reduces calibration difficulty, and ensures the quantitative accuracy of the acquired spectral data. In essence, this invention selects the appropriate exposure sequence based on the specific scenario to acquire the optimal image. Attached Figure Description

[0031] Figure 1 This is a simplified flowchart of the imaging spectrum adaptive exposure method of the present invention;

[0032] Figure 2 This is a simplified structural diagram of the imaging spectrum adaptive exposure system of the present invention;

[0033] The attached figures are labeled as follows: 1. Adaptive exposure parameter control module; 2. Exposure imaging module; 21. Optical device; 22. Spectrometer; 23. Detector. Detailed Implementation

[0034] The present invention will be further described and illustrated below with reference to the accompanying drawings and specific embodiments. The technical features of each embodiment of the present invention can be combined accordingly, provided that there is no mutual conflict.

[0035] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below. Technical features in the various embodiments of the present invention can be combined accordingly without mutual conflict.

[0036] In the description of this invention, it should be understood that when an element is considered to be "connected" to another element, it can be a direct connection to the other element or an indirect connection, i.e., there is an intermediate element. Conversely, when an element is said to be "directly" connected to another element, there is no intermediate element.

[0037] Example

[0038] Combination Figure 1 The illustrated imaging spectral adaptive exposure method based on an exposure parameter sequence includes the following steps:

[0039] Step S1: Based on the pre-selected feature exposure parameter P n (λ′), to obtain the spectral image data corresponding to the characteristic wavelength λ′, where the characteristic exposure parameter P n (λ′) represents the exposure parameter corresponding to the characteristic wavelength λ′ in the exposure parameter sequence set E. The exposure parameter sequence set E contains k exposure parameter sequences, each of which contains exposure parameters corresponding to all detection wavelengths. The characteristic wavelength λ′ includes the wavelength with the largest spectral response and the wavelength with the smallest spectral response among all wavelengths. The spectral response of the largest wavelength refers to the degree of response to light intensity or light signal at the position of the largest wavelength, and the spectral response of the smallest wavelength refers to the degree of response to light intensity or light signal at the position of the smallest wavelength. It is related to the detector of the imaging spectrometer. Once the detector of the imaging spectrometer is determined, the wavelengths with the largest and smallest spectral responses are obtained. The unit of the characteristic wavelength λ′ is nm.

[0040] Step S2: Calculate the mean value of the digital quantization value DN corresponding to the obtained spectral image of the characteristic wavelength λ′. Comparison of means With the set threshold DN′ λ' Based on the comparison results, the index n corresponding to the optimal exposure parameter sequence suitable for the current detection scene is output. The criterion for determining the optimal exposure detection sequence is: mean value. and threshold DN′ λ' The absolute value of the difference between the values ​​is equal to the minimum value; the calculation process for the minimum value is as follows: based on the current exposure parameter index n, the mean value is obtained. With threshold DN′ λ' The difference between them is DN diff The minimum value refers to the difference DN when the exposure parameter number is n+1. diff The difference DN between the exposure parameter number n-1 and the value of the exposure parameter number n-1 diff The difference DN between the current exposure parameter number n and the current exposure parameter number n is DN. diff Large, meaning the difference DN is considered to be when the current exposure parameter number is n. diff It is a local minimum.

[0041] Specifically, in step S2, the mean value of the characteristic wavelength λ′ With threshold DN′ λ' The comparison process is as follows: when the mean Greater than the threshold DN′ λ' and mean With threshold DN tIf the difference between the two values ​​is greater than the minimum value, then adjust the feature exposure parameter P. n (λ′) is the characteristic exposure parameter P of the characteristic wavelength λ′ corresponding to the lower-level sequence number. n-1 (λ′), where n = n-1, repeat step S1; when the mean Less than threshold DN′ λ' and mean With threshold DN′ λ' If the difference between them is greater than the minimum value, then adjust the feature exposure parameter P. n (λ′) is the characteristic exposure parameter P of the characteristic wavelength λ′ corresponding to the next higher sequence number. n+1 (λ′), where n = n + 1, repeat step S1; if the mean Equal to threshold DN′ λ' Or, mean With threshold DN′ λ' If the difference is equal to the minimum value, then the index n in the current exposure parameter sequence set E is output. Here, the mean... The calculation process is as follows: Add the DN values ​​of all pixels in the spectral image and then divide by the number of pixels to obtain the mean value of the spectral image corresponding to the characteristic wavelength λ′. The characteristic exposure parameter P for the pre-selected characteristic wavelength λ′ is... n The sequence number n corresponding to (λ′) is the middle sequence number of the total number of exposure parameter sequences k. For example, if there are 10 sequences k = 10, then the pre-selected sequence number n is n = 5.

[0042] Step S3: Based on the output sequence number n and the optimal exposure parameter sequence E corresponding to sequence number n. n Based on the optimal exposure parameter sequence E n Exposure parameters P corresponding to all detection wavelengths n (λ) Imaging detection is performed on each detection wavelength λ to obtain the spectral image of each detection wavelength λ, and the adaptive exposure operation of the imaging spectrum is completed. Among them, the characteristic wavelength λ′ is one case of each detection wavelength λ, and the method of obtaining the spectral image is similar to that of camera photography, which is the existing method, and will not be described in detail here.

[0043] Furthermore, the steps for generating the exposure parameter sequence are as follows:

[0044] Step 1: Adjust the amplitude and brightness energy level of the light source to C. Use gain G and integration time T to obtain the spectral image under this amplitude and brightness energy level condition. Initialize the amplitude and brightness energy level C of the light source as the minimum brightness energy level of the light source, and obtain the initial spectral image wavelength λ. sThe approach of acquiring spectral images using gain and integration time is similar to the exposure parameters of a camera. Gain and integration time control the DN value of the acquired image. Gain has no unit, while the unit of integration time is ms. In step 1, the initial gain G is set to the detector's maximum gain G1, and the initial integration time T is set to the detector's minimum integration time T1.

[0045] Step 2: Calculate the wavelength λ of the initial spectral image. s spectral image mean Determine the mean of the spectral image With detection threshold DN t The difference between them is used to output the integration time T and the gain G based on the judgment result; where the initial spectral image wavelength λ is understood as follows: when acquiring a spectral image of 400-900nm, the initial spectral image wavelength λ is 400nm and λmax is 900nm.

[0046] Specifically, in step 2, the judgment process is as follows: if the mean of the spectral image... Greater than the detection threshold DN t Reduce the gain G so that G = G-1, repeat step 1, and acquire the spectral image under the light source conditions until the mean of the spectral image is reached. and detection threshold DN t Equal; if the mean of the spectral image is equal; Less than the detection threshold DN t Increase the integration time T so that T = T + 1, and repeat step 1 to obtain the spectral image under the light source conditions until the mean of the spectral image is reached. and detection threshold DN t If they are equal, the amplitude brightness energy level C is still the minimum brightness energy level of the light source; if the mean of the spectral image is equal... Equal to the spectral image threshold DN t Then, the current integration time T and gain G are output. Wherein, the detection threshold DN... t Not greater than the detector's maximum digital quantization value DN max 50%. And this quantization value is the number of bits in the DN value. For example, for an 8-bit detector, the quantization value is 2 to the power of 8, which equals 256.

[0047] Step 3: Record the output integration time T and gain G as the exposure parameters for that wavelength at the current amplitude brightness level, and adjust the wavelength λ of the acquired spectral image. s , so that λ s =λ s +1, repeat steps 1 to 3 until the wavelength λ of the spectral image is reached. s The wavelength λ of the maximum spectral image max Output the exposure parameters obtained corresponding to the wavelengths of each spectral image;

[0048] Step 4: Collect the output exposure parameters and denote them as the exposure parameter sequence E of the light source energy level C. c (λ), adjust the luminance level C of the light source to C = C + 1, and repeat steps 1-4 until the luminance level C is the maximum luminance level C of the light source. max Output the exposure parameter sequence E for each brightness level. c The set of (λ) is denoted as

[0049] Combination Figure 2 As shown, this embodiment provides an imaging spectrum adaptive exposure system based on an exposure parameter sequence. The stereoscopic image of the target and spectrum in the figure better illustrates the contrast. Specifically, it includes an adaptive exposure parameter control module 1 and an exposure imaging module 2. The exposure imaging module includes an optical device 21, a beam splitter 22, and a detector 23. The process is as follows: light reflected from the target surface enters the imaging spectrum adaptive exposure system, is collimated by the optical device, and then incident on the beam splitter. The beam splitter splits the polychromatic beam, and the output monochromatic light is converged and incident on the detector. Among them, the optical device 21 is used for collimation and convergence of the target beam, and it can be a collimator; the beam splitter 22 is used to split the polychromatic beam into monochromatic light output, and the wavelength of the monochromatic light can be adjusted, and it can be a beam splitter; the detector 23 is an area array detector used for detection. Monochromatic light is used to obtain a single-wavelength spectral image. The detector is a CMOS detector with a maximum quantization value of 10 bits and an imaging wavelength range of 450nm to 950nm. The gain and integration time are adjustable. The adaptive exposure parameter control module is used to automatically select the optimal exposure parameter sequence suitable for the imaging scene from the set of exposure parameter sequences according to the adaptive exposure method of imaging spectrum. It controls the spectrometer 21 in the exposure imaging module to output monochromatic light of different wavelengths and controls the detector 23 to use different exposure parameters (gain and integration time) in the sequence to adjust the exposure parameters of different wavelength spectral images, thereby obtaining spectral images of different wavelengths and directly combining them to form an image cube.

[0050] In this embodiment, a visible-near-infrared integrating sphere is selected as the light source. The amplitude and brightness levels of the visible-near-infrared integrating sphere are adjustable from 1 to 8 levels, and a threshold DN is set. t ′ represents 50% of the detector's maximum quantization value. Wherein, the detection threshold DN... t This is the detection threshold in the exposure sequence generation; the threshold DN′ is set. t It is the threshold for target detection, and the two are the same in numerical value.

[0051] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, and is not intended to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions made by those skilled in the art to the technical solution of the present invention do not depart from the essence and scope of the technical solution of the present invention.

Claims

1. An imaging spectral adaptive exposure method based on an exposure parameter sequence, characterized in that, Includes the following steps: Step S1: Based on the pre-selected feature exposure parameter P n ( ), to obtain characteristic wavelengths The corresponding spectral image data, where the characteristic exposure parameter P n ( ) represents the characteristic wavelength corresponding to the exposure parameter sequence set E. The exposure parameters are given, and the set of exposure parameter sequences E contains k exposure parameter sequences, each of which contains the exposure parameter P corresponding to all detection wavelengths. n ( ); Step S2: Calculate the obtained characteristic wavelength The mean value of the digital quantization (DN) of the spectral image Compare the mean With the set threshold Based on the comparison results, the optimal exposure parameter sequence E suitable for the current detection scenario is output. n The corresponding sequence number n, where the optimal exposure detection sequence E n The judgment condition is: mean and threshold The absolute value of the difference between the values ​​is equal to the minimum value; the minimum value is calculated as follows: based on the current exposure parameter number n, the mean value is obtained. With threshold The difference between them is DN diff The minimum value refers to the difference DN when the exposure parameter number is n+1. diff The difference DN between the exposure parameter number n-1 and the value of the exposure parameter number n-1 diff The difference DN between the current exposure parameter number n and the current exposure parameter number n is DN. diff Large, meaning the difference DN is considered to be when the current exposure parameter number is n. diff It is the minimum value; In step S2, the characteristic wavelength mean With threshold The comparison process is as follows: When the mean Greater than the threshold and mean With threshold If the difference between them is greater than the minimum value, then adjust the feature exposure parameter P. n ( () represents the characteristic wavelength corresponding to the next lower sequence number. Feature exposure parameter P n-1 ( ), at this point n=n-1, repeat step S1; When the mean Less than the threshold and mean With threshold If the difference between them is greater than the minimum value, then adjust the feature exposure parameter P. n ( () represents the characteristic wavelength corresponding to the next higher sequence number. Feature exposure parameter P n+1 ( At this point, n = n + 1, and step S1 is repeated; If the mean equal to threshold Or, mean With threshold If the difference is equal to the minimum value, then output the index n in the current exposure parameter sequence set E; Step S3: Based on the optimal exposure parameter sequence E n Exposure parameters P corresponding to all detection wavelengths n ( For each detection wavelength Perform imaging detection and acquire various detection wavelengths. The spectral image is used to complete the adaptive exposure operation of the imaging spectrum; The steps for generating the exposure parameter sequence set E are as follows: Step 1: Adjust the amplitude and brightness energy level of the light source to C. Use gain G and integration time T to obtain the spectral image under this amplitude and brightness energy level condition. Initialize the amplitude and brightness energy level C of the light source to the minimum brightness energy level of the light source, and obtain the wavelength of the initial spectral image. ; Step 2: Calculate the wavelength of the initial spectral image. spectral image mean Determine the mean of the spectral image With detection threshold The difference between them is used to determine the integral time T and the gain G. Step 3: Record the output integration time T and gain G as the exposure parameters for the wavelength of the spectral image at the current amplitude brightness level, and adjust the acquired spectral image wavelength. ,make = +1, repeat steps 1 through 3 until the wavelength of the spectral image is reached. For the maximum spectral image wavelength Output the exposure parameters obtained corresponding to the wavelengths of each spectral image; Step 4: Collect the output exposure parameters and record them as the exposure parameter sequence of the light source energy level C. Adjust the luminance level of the light source to C = C + 1, and repeat steps 1 to 4 until the luminance level C is the maximum luminance level of the light source. Output the exposure parameter sequence for each brightness level. The set is denoted as .

2. The imaging spectral adaptive exposure method based on an exposure parameter sequence according to claim 1, characterized in that, In step S1, the characteristic wavelength This includes the wavelengths with the largest and smallest spectral responses among all detection wavelengths. The largest wavelength's spectral response refers to the degree of response to light intensity or signal at the wavelength with the largest response, while the smallest wavelength's spectral response refers to the degree of response to light intensity or signal at the wavelength with the smallest response. Characteristic wavelengths... The unit is nm.

3. The imaging spectral adaptive exposure method based on an exposure parameter sequence according to claim 1, characterized in that, In step S2, the mean The calculation process is as follows: add the DN values ​​of all pixels in the spectral image and then divide by the number of pixels to obtain the characteristic wavelength. The mean of the corresponding spectral image.

4. The imaging spectral adaptive exposure method based on an exposure parameter sequence according to claim 1, characterized in that, In step S2, the pre-selected characteristic wavelength Feature exposure parameter P n ( The corresponding index n is the index in the middle of the total number k of exposure parameter sequences.

5. The imaging spectral adaptive exposure method based on an exposure parameter sequence according to claim 1, characterized in that, In step 1, the initial gain G is set to the maximum gain G1 of the detector, and the initial integration time T is set to the minimum integration time T1 of the detector.

6. The imaging spectral adaptive exposure method based on an exposure parameter sequence according to claim 1, characterized in that, In step 2, the judgment process is as follows: If the mean of the spectral image Greater than the detection threshold Reduce the gain G so that G = G-1, repeat step 1, and acquire the spectral image under the light source conditions until the mean of the spectral image is reached. and detection threshold equal; If the mean of the spectral image Less than the detection threshold Increase the integration time T so that T = T + 1, repeat step 1, and obtain the spectral image under the light source conditions until the mean of the spectral image is reached. and detection threshold equal; If the mean of the spectral image Equal to the spectral image threshold Then the current integration time T and gain G will be output.

7. The imaging spectral adaptive exposure method based on an exposure parameter sequence according to claim 6, characterized in that, In step 2, the detection threshold is set. Not greater than the detector's maximum digital quantization value DN max 50%.

8. An imaging spectral adaptive exposure system based on an exposure parameter sequence, characterized in that, It includes an adaptive exposure parameter control module and an exposure imaging module, the latter being used to acquire spectral images; The exposure imaging module includes optical components, a beam splitter, and a detector. Light reflected from the target surface enters the imaging spectrum adaptive exposure system, is collimated by the optical components, and then incident on the beam splitter. The beam splitter splits the polychromatic beam, and the output monochromatic light is converged and then incident on the detector. The adaptive exposure parameter control module is used in the imaging spectral adaptive exposure method based on exposure parameter sequences as described in any one of claims 1-7, to automatically select the optimal exposure parameter sequence E suitable for the imaging scenario from the set of exposure parameter sequences. n It controls the exposure imaging module to adjust the exposure parameters of spectral images with different characteristic wavelengths, thereby obtaining spectral images with different characteristic wavelengths.

Images