Multi-spectral imaging sensor radiation calibration method and system

Abstract

The invention provides a multispectral imaging sensor radiation calibration method comprising the following steps: S1, using a multispectral imaging sensor to collect an image, the image comprising a diffuse reflection calibration plate, and calculating to obtain the radiance reflected by the diffuse reflection calibration plate; s2, photographing a target ground object by using a multispectral imaging sensor, and calculating to obtain radiance reflected by the diffuse reflection calibration plate; and calculating the surface reflectance of the normalized diffuse reflection calibration plate based on the radiance reflected by the diffuse reflection calibration plate obtained in the step S1 and the radiance reflected by the diffuse reflection calibration plate obtained in the step S2. According to the method, radiation calibration can be carried out on the multispectral imaging sensor carried on the unmanned aerial vehicle or the ground mobile platform under any weather conditions. The invention also correspondingly provides a radiation calibration system for the multispectral imaging sensor.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of radiation calibration, and more particularly to a multispectral imaging sensor radiation calibration method and system. BACKGROUND

[0002] The multispectral imaging sensor can obtain detailed information of the surface reflectance spectrum of ground objects, and can be carried on unmanned aerial vehicles or near-ground monitoring platforms to collect data. In recent years, the multispectral imaging sensor has been widely used in the field of near-ground quantitative remote sensing. The data of each grid of the original image collected by the multispectral imaging sensor is a Digital Number (DN) value, i.e. the original gray value of the ground object. This value is closely related to the characteristics of the camera itself, the waveband, the resolution, the radiation conditions during data collection, and the like. In actual applications, it is necessary to convert the DN value into the reflectance of each waveband reflecting the spectral characteristics of the ground object, and this process is called radiation calibration.

[0003] The empirical linear calibration method is one of the most commonly used radiation calibration methods. The principle of this method is to place at least two diffuse reflection calibration panels with different reflectance values on the ground (the reflectance of the diffuse reflection calibration panel is known), use the multispectral imaging sensor to take pictures of these diffuse reflection calibration panels at the same time, obtain the DN value of each diffuse reflection calibration panel, and then construct a linear relationship between the diffuse reflection calibration panel and the DN, as shown in formula (2). Figure 1 As shown in formula (2), it shows that there is a relationship between the ground reflectance of any one diffuse reflection calibration panel and the radiance recorded by the sensor (formula 1).

[0004]

[0005] wherein ρ λ represents the ground reflectance of the diffuse reflection calibration panel, represents the radiance of the waveband λ recorded by the sensor, is the radiance of the atmosphere, is the radiance of the solar incident radiation, ρ λ is the ground reflectance, a λ is Figure 1 the slope of the oblique line as shown in formula (1).

[0006] Since the ground reflectance ρ λ of the diffuse reflection calibration panel is known, and they appear in the same image, and are the same, therefore, a linear formula can be constructed according to the reflectance of the calibration panels with different reflectance, the radiance measured by the sensor, and the slope a λ of each waveband can be calculated. Then, the slope is applied to the pixels of other pictures taken by the multispectral sensor, so as to realize the conversion of the DN value of each grid in the original image to the reflectance of the ground object.

[0007] The advantage of this method is simple and easy to operate, but it requires at least two diffuse reflection calibration panels with different reflectivity to be placed on the ground, and the use of a multispectral imaging sensor to take pictures synchronously, and requires that the solar incident radiation be very stable when the image is collected, that is No change occurs, which is difficult to achieve in actual unmanned aerial vehicle flight or ground moving monitoring platform. In practical applications, only one diffuse reflection calibration panel is usually used, so it is difficult to obtain the slope a λ In addition, the diffuse reflection calibration panel is usually fixed on the ground, while the multispectral imaging sensor is carried on the unmanned aerial vehicle or ground moving monitoring platform, and pictures are taken as the unmanned aerial vehicle flies or the ground platform moves, so only part of the images will capture the diffuse reflection calibration panel. When the solar radiation is stable, that is, the entire flight process does not change, this method can be used. However, in actual monitoring, the solar radiation changes greatly, especially in cloudy conditions, and it cannot be guaranteed that the of all images are consistent, resulting in the formula not being established.

[0008] Some studies have proposed installing a downward light sensor on the multispectral imaging sensor to monitor the incident solar radiation in real time. This method is used on Micasense and other multispectral cameras. However, the data collection of the downward light sensor is not stable, resulting in poor radiation calibration, especially in cloudy conditions. Patent ZL202211273396.8 proposes a radiation calibration method using a diffuse reflection calibration panel, but this patent only considers calibration in the case of stable solar radiation and does not consider the case when the radiation changes due to cloud movement. SUMMARY

[0009] To solve the problems in the background art, the present application provides a method for radiation calibration of a multispectral imaging sensor, comprising: S1, using a multispectral imaging sensor to collect images, the images including a diffuse reflection calibration panel, and calculating the radiance reflected by the diffuse reflection calibration panel; S2, using the multispectral imaging sensor to take pictures of a target ground object, and calculating the radiance reflected by the diffuse reflection calibration panel; S3, based on the radiance reflected by the diffuse reflection calibration panel obtained in S1 and the radiance reflected by the diffuse reflection calibration panel obtained in S2, calculating the normalized ground reflectivity of the diffuse reflection calibration panel.

[0010] The present application also provides a verification method for the radiation calibration method of a multispectral imaging sensor, comprising: S1, measuring the change of solar incident radiation within a set time under completely sunny, partially cloudy, and cloudy weather conditions;

[0011] S2, in the presence of partial cloud, set multiple diffuse reflectance calibration panels on the ground, set one of them as a reference panel, and the rest as target ground objects, measure the actual reflectance of the target calibration panel, and compare it with the ground surface reflectance of the target ground object calculated by the radiation calibration method of claims 1-5, to analyze the influence of the radiation calibration method on the calculation of reflectance; S3, determine whether the radiation calibration method is effective.

[0012] The method of the present application can calibrate the multispectral imaging sensor mounted on the unmanned aerial vehicle or the ground mobile platform under any weather condition. In addition, the method of the present application eliminates the problem of calibration difficulty caused by the change of solar incident radiation, and only needs to use one diffuse reflection calibration panel to realize radiation calibration.

[0013] Compared with the prior art, the method of the present application only needs to place one diffuse reflection radiation calibration panel on the ground, and can overcome the problems of difficult radiation calibration and low precision caused by the rapid change of solar radiation due to the influence of clouds, by using the multispectral imaging sensor to collect an image before, after or during flight. The obtained normalized reflectance can be directly used to calculate various vegetation indices, or input into a radiation transfer model for quantitative inversion of leaf area index, etc.

[0014] The present application also proposes a verification system and method, which can verify the radiation calibration method proposed by the present application to ensure the accuracy of the radiation calibration method. The results of the verification can support the application of the new radiation calibration method in practice. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to make the present application easier to understand, the present application will be described in more detail by referring to the specific embodiments shown in the accompanying drawings. These drawings only depict typical embodiments of the present application and should not be considered as limiting the scope of protection of the present application.

[0016] Figure 1 is a schematic diagram of the principle of the empirical linear method.

[0017] Figure 2 is a flowchart of one embodiment of the method of the present application.

[0018] Figure 3 shows the experimental design schematic architecture for verifying the method of the present application.

[0019] Figure 4 shows the variation of solar incident radiance and PAR scattering ratio with solar zenith angle for three observation dates.

[0020] Figure 5 shows a schematic diagram of the variation of the difference between the estimated and actual reflectance with solar zenith angle.

[0021] Figure 6 The relationship between the radiation of each waveband and the total incident PAR is shown. DETAILED DESCRIPTION

[0022] Embodiments of the present application will be described below with reference to the accompanying drawings, so that those skilled in the art can better understand the present application and implement it, but the listed embodiments are not as a limitation of the present application, and the following embodiments and technical features in the embodiments can be combined with each other without conflict, wherein the same components are denoted by the same reference numerals.

[0023] The principle of the radiation calibration method of the present application will be described below.

[0024] During the movement of a general unmanned aerial vehicle flight or ground movement monitoring platform, a multi-spectral imaging sensor is used to take pictures of a diffuse reflection calibration plate placed on a horizontal ground before or after the measurement starts, and the reflected radiance of the calibration plate is collected.

[0025] When the platform carrying the multi-spectral imaging sensor is lower than 1.5 meters in height, the term in formula (1) can be ignored, and formula (1) is transformed into:

[0026]

[0027] wherein, represents the radiance of the waveband λ recorded by the multi-spectral imaging sensor, is the radiance of the solar incident radiation, ρ λ is the ground reflectivity, a λ is Figure 1 the slope of the oblique line (between the ground reflectivity of the diffuse reflection calibration plate and the radiance recorded by the multi-spectral imaging sensor) shown in the figure.

[0028] If the image element of the image collected by the multi-spectral imaging sensor represents the diffuse reflection calibration plate (R), formula (2) can be rewritten as the following formula (3).

[0029]

[0030] wherein, ρ λ (R) represents the ground reflectivity of the diffuse reflection calibration plate, which is a known value measured in the laboratory, represents the radiance of the solar incident radiation reaching the diffuse reflection calibration plate, represents the radiance of the reflection of the diffuse reflection calibration plate measured by the multi-spectral imaging sensor.

[0031] If the image element of the image collected by the multi-spectral imaging sensor represents the target ground object (T), formula (2) can be rewritten as the following formula (4). ​

[0032]

[0033] Where ρ λ (T) represents the surface reflectance of the target feature. Represents the solar incident radiation radiance reaching the target object. This represents the radiance reflected by the target ground object as measured by a multispectral imaging sensor.

[0034] according to Figure 1 The principle, a in formulas (3) and (4) λ If they are the same, then the surface reflectance ρ of the target object is... λ (T) can be expressed as formula (5).

[0035]

[0036] If the incident solar radiation remains stable throughout the measurement process, i.e., the incident solar radiation when photographing the diffuse reflection calibration plate before the measurement... Incident solar radiation reaching the target object during the measurement process exactly the same, Then formula (5) can be transformed into formula (6).

[0037]

[0038] However, in most cases, the incident solar radiation will change significantly during the measurement process. The transformation from formula (5) to formula (6) does not hold true.

[0039] Therefore, this invention proposes a method for calculating reflectivity by using one of the wavebands as a reference waveband. Taking one of the wavebands λ... * As a reference band, the normalized surface reflectance can be calculated.

[0040]

[0041] in, The target ground feature T represents the target ground feature in band λ. * Surface reflectance, ρ λ (T) represents the surface reflectance of the target object.

[0042] Calculate using formula (5):

[0043]

[0044] and These represent the diffuse reflection calibration plate and the target ground object in band λ, respectively.* the solar incident radiation, and respectively represent the diffuse reflectance calibration board and the target ground object measured by the multispectral imaging sensor in the waveband λ * reflected radiance.

[0045] Combining the formula (5), (7) and (8), the target ground surface reflectance in the waveband λ

[0046]

[0047] wherein, for the diffuse reflectance calibration board, and the radiance incident to the diffuse reflectance calibration board is consistent in different wavebands, i.e. then the formula (9) can be simplified as:

[0048]

[0049] wherein, represents the normalized ground surface reflectance of the diffuse reflectance calibration board, represents the radiance reflected by the target ground object measured by the multispectral imaging sensor, represents the radiance of the incident sun in the waveband λ * reaching the target ground object during the measurement process, represents the reflected radiance of the diffuse reflectance calibration board in the waveband λ * measured by the multispectral imaging sensor, represents the radiance reflected by the diffuse reflectance calibration board measured by the multispectral imaging sensor.

[0050] Therefore, through the formula (10), the target ground surface reflectance in any waveband λ can be calculated from the data observed by the multispectral imaging system, and is not affected by the weather condition.

[0051] The technical idea of the present application is: by selecting a reference waveband, calculating the relative reflectance, so as to eliminate the influence of weather condition change on the observation data.

[0052] Based on the above technical principle, the radiometric calibration method of the present application comprises:

[0053] S1, setting the multispectral imaging sensor at a vertical height of 1.5 meters or below, taking a photo of the diffuse reflectance calibration board placed on the ground (preferably a horizontal ground), collecting the reflected radiance of the diffuse reflectance calibration board, and obtaining the reflected radiance of the diffuse reflectance calibration board in the waveband λ * the radiance reflected by the diffuse reflectance calibration board

[0054] ​S2, use a multispectral imaging sensor to photograph the target ground object, collect the reflected radiance of the target ground object, and obtain the radiance representing the reflected radiance of the target ground object. The incident sun reaching the target object in the λ band * radiance The target feature mentioned can be any object (including farmland). If a drone is used for filming, it will move and photograph the entire farmland, and the target feature will be the content in each photo.

[0055] S3, based on the data obtained from S1 and S2, is calculated using formula (10) to obtain the normalized surface reflectance of the diffuse reflection calibration plate.

[0056] The method of this invention has been verified. To this end, the following ground verification experiment was designed, see... Figure 3 The objectives of the experiment include the following:

[0057] 1. The variation of solar incident radiation under different weather conditions (completely clear sky, partially cloudy, and overcast) over a short period of time (e.g., within 20 minutes), i.e., verifying the effect of solar radiation during this time period. Whether it is valid or not.

[0058] 2. When there are partial clouds, assuming Established, using any one of the eight diffuse emission calibration plates as a reference plate, and the rest as target features, ρ is calculated based on formula (6). λ (T) is compared with the actual reflectance of the target calibration plate to analyze the impact of this assumption on the calculated reflectance.

[0059] 3. Verification Whether it is valid or not.

[0060] The experimental design included the following: a top-view fisheye lens camera, a BF5 direct / diffuse photosynthetically active radiation (PAR) receiver sensor, and eight diffuse reflection calibration plates with different reflectivities were placed in the same plane. The reflectivities of these eight diffuse reflection calibration plates had been measured in the laboratory. Figure 3 As shown in the upper right corner.

[0061] Using a support frame (converted from two bicycles), a downward-looking multispectral imaging sensor is mounted approximately 1.5 meters above the ground. This sensor is positioned directly above the diffuse reflection calibration plate, ensuring that the acquired image includes the entire calibration plate. Simultaneously, the support frame must not obstruct the upward-looking fisheye camera or the BF5 lens, guaranteeing the effectiveness of data acquisition from both.

[0062] All data acquisition is controlled by the Campbell data acquisition unit. By modifying the data acquisition control program of the fisheye camera, multispectral imaging sensor and BF5, the data acquisition of the three instruments is synchronized, ensuring that a set of data is acquired every ten seconds.

[0063] The above experiments were conducted on a single day under the following three weather conditions: completely sunny (cloudless), partially cloudy, and overcast. Data collection for each day began at 8:00 AM and continued until 8:00 PM.

[0064] Experimental results show that a fisheye camera can capture real-time information about the sun and clouds in the sky, while the BF5 sensor can monitor the intraday variation of synchronous solar incidence PAR. Figure 4 As shown, the scattering ratio of solar incident PAR (diffuse radiation measured by BF5 divided by the sum of direct and diffuse radiation) varies with the solar angle. Specifically, on the first day, a visually clear day, the scattering ratio changes steadily with increasing solar zenith angle. However, on the second and third days, the scattering ratio fluctuates significantly, confirming that the scattering ratio changes under cloudy conditions. The assumption is not valid.

[0065] Using one of the reference boards as R, and using the measured data from 16:40 to 17:20 over these three days, assuming... The results were found to be true. The reflectance of other reference plates was calculated and compared with the measured reflectance. It was found that the estimation error of the reflectance in the 450nm band was as high as 0.5 or more, which confirmed that the hypothesis was not valid in the presence of clouds. The use of the empirical linear model would lead to a large error in the calculation of the reflectance of the target object.

[0066] Using a diffuse reflection calibration plate with a reflectivity of 1, i.e. Images captured using a multispectral sensor Calculate different bands The relationship between the measured PAR of BF5 and the actual PAR was obtained under different weather conditions. The proportional relationship between PAR and the actual value, and the fact that this ratio remains relatively constant, indirectly confirms this.

[0067] Based on the above verification methods, the effectiveness of the method of this invention can be demonstrated. Furthermore, this invention has been used in data acquisition from multiple UAV-borne multispectral cameras. The vegetation index, leaf area index, and other data calculated based on normalized reflectance show good correlation with the ground verification dataset, verifying the effectiveness of the method.

[0068] The present invention also proposes a radiometric calibration system for a multispectral imaging sensor, including a processor, the processor including a computer-executable program, which performs the radiometric calibration method as described above when the computer-executable program is executed.

[0069] The above-described embodiments are merely possible preferred embodiments of the present application. The phrase "in one embodiment", "in another embodiment", "in yet another embodiment" or "in other embodiments" in the specification can refer to one or more of the same or different embodiments according to the present disclosure. Common variations and replacements made by those skilled in the art within the scope of the technical solutions of the present application should be included in the protection scope of the present application.

Claims

1. A multispectral imaging sensor radiometric calibration method, characterized by, Comprising: S1, using a multi-spectral imaging sensor to collect images, the images including a diffuse reflection calibration board, calculating the radiance reflected by the diffuse reflection calibration board; S2, using a multi-spectral imaging sensor to take a picture of the target ground object, calculating the radiance reflected by the diffuse reflection calibration board; S3, based on the radiance reflected by the diffuse reflection calibration board obtained in S1 and the radiance reflected by the diffuse reflection calibration board obtained in S2, calculating the normalized ground reflectance of the diffuse reflection calibration board.

2. The method of claim 1, wherein, Step S1 includes: The multi-spectral imaging sensor is set at a vertical height of 1.5 meters or below, and the diffuse reflection calibration board placed on the ground is photographed.

3. The method of claim 2, wherein, Step S1 includes: selecting a reference wavelength λ * , obtaining a reflectance radiance * of the diffuse reflectance calibration panel at the reference wavelength λ a reflectance radiance 4. The method of claim 3, wherein, Step S2 includes: selecting a reference waveband λ * to obtain a radiance representative of the reflection of the target ground object and the radiance of the incident sun at the waveband λ * to the target ground object 5. The method of claim 4, wherein, Step S3 includes: in, The surface reflectance represents the normalized diffuse reflection calibration plate. This represents the radiance reflected by the target ground object as measured by a multispectral imaging sensor. This represents the incident solar radiation reaching the target object in the wavelength λ during the measurement process. * radiance, This indicates the diffuse reflection calibration plate measured by a multispectral imaging sensor in band λ. * The reflected radiance, This represents the radiance reflected by the diffuse reflection calibration plate as measured by a multispectral imaging sensor.

6. A method for verifying a method of radiometric calibration of a multispectral imaging sensor, characterized in that, Comprising: S1, measuring the change of solar incident radiation within a set time under completely sunny, partially cloudy and cloudy weather conditions; S2, when there are partial clouds, setting multiple diffuse reflection calibration boards on the ground, setting one of them as a reference board and the rest as target ground objects, measuring the actual reflectance of the target calibration board, and comparing it with the ground reflectance of the target ground object calculated by the radiation calibration method of claims 1-5 to analyze the influence of the radiation calibration method on calculating reflectance; S3, determining whether the radiation calibration method is effective.

7. The method of claim 6, wherein, Step S1 includes: An upward fisheye lens camera is placed at the same horizontal position, and the fisheye lens camera is used to capture the real-time situation of the sun and clouds in the sky; A BF5 sensor is set to monitor the diurnal variation of synchronous solar incident PAR; Eight diffuse reflection calibration boards with different reflectances are set, and the reflectances of the eight diffuse reflection calibration boards are measured; A downward multi-spectral imaging sensor is installed above the diffuse reflection calibration boards, about 1.5 meters from the ground, to ensure that the collected images contain all the diffuse reflection calibration boards; The set time is 20 minutes.

8. The method of claim 7, wherein, Step S2 includes: Using the measured data in the afternoon set time interval, the reflectance of the target ground object is calculated and compared with the measured reflectance.

9. The method of claim 8, wherein, Step S3 includes: Selecting a diffuse reflection calibration board with a reflectance of 1; Using the multi-spectral sensor to calculate the relationship between the radiance reflected by the diffuse reflection calibration board measured by the multi-spectral imaging sensor and the sensor measured solar incident PAR in different wavebands; Based on the proportional relationship between the solar incident radiance reaching the diffuse reflection calibration board and the solar incident PAR under different weather conditions, it is determined whether the calibration method is effective.

10. A multispectral imaging sensor radiometric calibration system, characterized by, The processor includes a computer executable program, which runs to complete the method of any one of claims 1-5.

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