Methods for determining reflectance in multispectral imaging systems

Abstract

This application provides a method for determining reflectance in a multispectral imaging system. The method involves acquiring raw image data of the target band from the image sensor in the multispectral imaging system when the system captures an image of a target object. Based on the pixel value of the target pixel in the raw image data, the raw brightness of the target object is determined, where the raw brightness is positively correlated with the pixel value. A corrected brightness is obtained by compensating the raw brightness based on the target magnification of the optical subsystem of the multispectral imaging system. Finally, the reflectance of the target object to the target band is determined based on the corrected brightness and the ambient light intensity of the target band in the environment where the target object is located. The reflectance is positively correlated with the corrected brightness and negatively correlated with the ambient light intensity. Applying the reflectance determination method provided in this application can improve the efficiency and accuracy of reflectance determination.

Description

Technical Field

[0001] This application relates to the field of image processing technology, and in particular to a method for determining reflectance in a multispectral imaging system. Background Technology

[0002] In some application scenarios, it is necessary to determine the reflectance of a specified object or area (hereinafter referred to as the object) to light of a specific wavelength. For example, since the reflectance spectrum of vegetation is different from that of the ground and the reflectance spectrum of vegetation in different states is also different, the vegetation coverage and growth status in the specified area can be determined by measuring the reflectance of the specified area.

[0003] In related technologies, a diffuse reflector with known reflectivity can be set up in advance near the location of a specified object. An aircraft carrying a camera is used to take an image containing the specified object and the diffuse reflector from a high altitude. Based on the ratio of the brightness of the specified object to the brightness of the diffuse reflector in the image, the ratio of the reflectivity of the specified object to the reflectivity of the diffuse reflector is determined, thereby obtaining the reflectivity of the specified object.

[0004] However, this method requires a pre-set diffuser, so it is less efficient. Summary of the Invention

[0005] The purpose of this application is to provide a method for determining reflectance in a multispectral imaging system, so as to improve the efficiency and accuracy of reflectance determination.

[0006] In a first aspect, embodiments of this application provide a method for determining reflectance, the method comprising:

[0007] Acquire the raw image data of the target band collected by the image sensor in the multispectral imaging system when the multispectral imaging system captures the target object;

[0008] The original brightness of the target object is determined based on the pixel value of the target pixel point in the original image data, wherein the original brightness is positively correlated with the pixel value;

[0009] The original brightness is compensated to obtain the corrected brightness based on the target magnification of the optical subsystem of the multispectral imaging system.

[0010] Based on the corrected brightness and the ambient light brightness of the target band in the environment where the target object is located, the reflectivity of the target object to the light of the target band is determined, wherein the reflectivity is positively correlated with the corrected brightness and negatively correlated with the ambient light brightness.

[0011] In one possible implementation, determining the original brightness of the target object based on the pixel value of the pixel point where the target object is located in the original image data includes:

[0012] Obtain the pixel values ​​of the target pixel point where the target object is located in each color channel from the original image data;

[0013] The components of each color channel are weighted and summed according to the preset weights set for each color channel to obtain the original brightness of the target object. The preset weights of each color channel are positively correlated with the signal-to-noise ratio of each color channel.

[0014] In one possible implementation, the method further includes:

[0015] For each color channel, the weight corresponding to the target band is determined according to the preset correspondence between the bands and weights for the color channel, and is used as the preset weight of the color channel.

[0016] In one possible implementation, determining the original brightness of the target object based on the pixel value of the target pixel point in the original image data includes:

[0017] The original image data is subjected to dark noise correction to obtain corrected image data;

[0018] The original brightness of the target object is determined based on the pixel value of the target pixel point in the corrected image data.

[0019] In one possible implementation, determining the original brightness of the target object based on the pixel value of the target pixel point in the original image data includes:

[0020] The original image data is scaled to obtain processed image data;

[0021] The original brightness of the target object is determined based on the pixel value of the target pixel point in the processed image data.

[0022] In one possible implementation, the step of compensating the original brightness to obtain corrected brightness based on the target magnification of the optical subsystem of the multispectral imaging system includes:

[0023] According to the preset correspondence between magnification and compensation coefficient, the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system is determined.

[0024] The corrected brightness is obtained by multiplying the compensation coefficient by the original brightness.

[0025] In one possible implementation, the correspondence is used to record multiple standard magnifications and compensation coefficients;

[0026] The step of determining the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system according to the preset correspondence between magnification and compensation coefficient includes:

[0027] By fitting the compensation coefficients corresponding to each of the standard magnifications, the target compensation coefficients corresponding to the target magnification of the optical subsystem of the multispectral imaging system are obtained.

[0028] In one possible implementation, fitting the compensation coefficients corresponding to each of the standard magnifications to obtain the target compensation coefficients corresponding to the target magnification of the optical subsystem of the multispectral imaging system includes:

[0029] Based on the target magnification of the optical subsystem of the multispectral imaging system, a first standard magnification and a second standard magnification are determined from each of the standard magnifications, wherein the first standard magnification is the maximum value among all the standard magnifications that are less than the target magnification, and the second standard magnification is the minimum value among all the standard magnifications that are greater than the target magnification.

[0030] Interpolate the compensation coefficients corresponding to the first standard magnification and the second standard magnification to obtain the target compensation coefficient corresponding to the target magnification.

[0031] In one possible implementation, the method further includes:

[0032] The brightness of the light signal in the target band sensed by the multispectral light intensity sensor during the process of the multispectral imaging system capturing the target object is obtained as the ambient light brightness, wherein the multispectral light intensity sensor is set in the environment where the target object is located.

[0033] In one possible implementation, acquiring the brightness of the light signal in the target wavelength band sensed by the multispectral light intensity sensor during the process of the multispectral imaging system capturing the target object includes:

[0034] Acquire spectral response data generated by the multispectral light intensity sensor in response to ambient light during the process of the multispectral imaging system capturing the target object;

[0035] The intensity corresponding to the target band in the spectral response data is obtained as the ambient light intensity.

[0036] In one possible implementation, the multispectral light intensity sensor and the multispectral imaging system are integrated into a multispectral camera, and the light inlet of the multispectral light intensity sensor and the light inlet of the optical subsystem are located on two opposite surfaces of the multispectral camera.

[0037] In one possible implementation, the target object is a target surface area, and the method further includes:

[0038] The vegetation index of the target surface area is calculated based on the reflectivity of the target surface area to the target wavelength.

[0039] In one possible implementation, the target band includes multiple different bands;

[0040] The step of calculating the vegetation index of the target surface area based on the reflectivity of the target surface area to the target wavelength includes:

[0041] For each preset standard band, a target band that matches the preset standard band is determined from each of the target bands and used as the matching band corresponding to the preset standard band;

[0042] For each of the preset standard bands, the reflectivity of the target surface area to the light of the matching band is determined as the target reflectivity of the target surface area to the light of the preset standard band.

[0043] Based on the correspondence between the reflectance of the surface area to the light of the preset standard band and the vegetation index, the vegetation index corresponding to the target reflectance is determined as the vegetation index of the target surface area.

[0044] Secondly, embodiments of this application provide a reflectance determination device, the device comprising:

[0045] The data acquisition module is used to acquire the original image data of the target band collected by the image sensor in the multispectral imaging system when the multispectral imaging system captures the target object;

[0046] A brightness determination module is used to determine the original brightness of the target object based on the pixel value of the target pixel point in the original image data, wherein the original brightness is positively correlated with the pixel value;

[0047] A brightness compensation module is used to compensate the original brightness according to the target magnification of the optical subsystem of the multispectral imaging system to obtain a corrected brightness;

[0048] The reflectivity determination module is used to determine the reflectivity of the target object to light of the target wavelength band based on the corrected brightness and the ambient light brightness of the target wavelength band in the environment where the target object is located, wherein the reflectivity is positively correlated with the corrected brightness and negatively correlated with the ambient light brightness.

[0049] In one possible implementation, the brightness determination module includes:

[0050] The brightness determination first submodule is used to obtain the pixel value of the target pixel point where the target object is located in each color channel from the original image data;

[0051] The second submodule for determining brightness is used to perform a weighted summation of the components of each color channel according to the preset weights set for each color channel to obtain the original brightness of the target object, wherein the preset weights of each color channel are positively correlated with the signal-to-noise ratio of each color channel;

[0052] The device further includes:

[0053] The weight determination module is used to determine the weight corresponding to the target band for each color channel according to the preset correspondence between the bands and weights for the color channel, and use it as the preset weight of the color channel.

[0054] The brightness determination module includes:

[0055] The third submodule for brightness determination is used to perform dark noise correction on the original image data to obtain corrected image data;

[0056] The fourth submodule for determining brightness is used to determine the original brightness of the target object based on the pixel value of the target pixel point in the corrected image data.

[0057] The brightness determination module includes:

[0058] The fifth submodule for brightness determination is used to scale the original image data to obtain processed image data;

[0059] The sixth brightness determination submodule is used to determine the original brightness of the target object based on the pixel value of the target pixel point in the processed image data.

[0060] The brightness compensation module includes:

[0061] The brightness compensation first submodule is used to determine the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system according to the preset correspondence between magnification and compensation coefficient.

[0062] The second submodule for brightness compensation is used to calculate the product of the compensation coefficient and the original brightness to obtain the corrected brightness;

[0063] The correspondence is used to record multiple standard magnifications and compensation coefficients;

[0064] The first submodule for brightness compensation includes:

[0065] The first brightness compensation unit is used to fit the compensation coefficients corresponding to each of the standard magnifications to obtain the target compensation coefficients corresponding to the target magnification of the optical subsystem of the multispectral imaging system.

[0066] The first brightness compensation unit includes:

[0067] A brightness compensation first subunit is used to determine a first standard magnification and a second standard magnification from each of the standard magnifications based on the target magnification of the optical subsystem of the multispectral imaging system, wherein the first standard magnification is the maximum value among all the standard magnifications that are less than the target magnification, and the second standard magnification is the minimum value among all the standard magnifications that are greater than the target magnification.

[0068] The second brightness compensation subunit is used to interpolate the compensation coefficient corresponding to the first standard magnification and the compensation coefficient corresponding to the second standard magnification to obtain the target compensation coefficient corresponding to the target magnification.

[0069] The device further includes:

[0070] An ambient light intensity acquisition module is used to acquire the brightness of the light signal of the target band sensed by the multispectral light intensity sensor during the process of the multispectral imaging system capturing the target object, as the ambient light intensity, wherein the multispectral light intensity sensor is set in the environment where the target object is located.

[0071] The ambient light intensity acquisition module includes:

[0072] The first sub-module for acquiring ambient light brightness is used to acquire spectral response data generated by the multispectral light intensity sensor in response to ambient light during the process of the multispectral imaging system capturing the target object;

[0073] The second sub-module for acquiring ambient light intensity is used to acquire the intensity corresponding to the target band in the spectral response data as ambient light intensity.

[0074] The brightness compensation first unit, the multispectral light intensity sensor and the multispectral imaging system are integrated into the multispectral camera, and the light inlet of the multispectral light intensity sensor and the light inlet of the optical subsystem are located on two opposite surfaces of the multispectral camera;

[0075] The target object is a target surface area, and the device further includes:

[0076] The index calculation module is used to calculate the vegetation index of the target surface area based on the reflectivity of the target surface area to the light of the target wavelength band.

[0077] The target band includes multiple different bands;

[0078] The index calculation module includes:

[0079] The index calculation first module is used to determine, for each preset standard band, a target band that matches the preset standard band from each target band, as the matching band corresponding to the preset standard band;

[0080] The second index calculation module is used to determine the reflectance of the target surface area to the light of the matching band as the target reflectance of the target surface area to the light of the preset standard band for each preset standard band.

[0081] The third module for index calculation is used to determine the vegetation index corresponding to the target reflectance based on the correspondence between the reflectance of the surface area to the light of the preset standard band and the vegetation index, and use it as the vegetation index of the target surface area.

[0082] Thirdly, embodiments of this application provide an electronic device, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0083] Memory, used to store computer programs;

[0084] When a processor executes a program stored in memory, it implements any of the reflectivity determination method steps described above.

[0085] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any of the reflectivity determination method steps described above.

[0086] Beneficial effects of the embodiments in this application:

[0087] The reflectance determination method provided in this application, since the image sensor in the multispectral imaging system is used to convert the sensed light signal into image data, the pixel value of the target pixel in the original image data is obtained by the image sensor sensing the light signal reflected by the target object. This reflects the intensity of the target wavelength light reflected from the target object to the image sensor. Furthermore, since not all the light reflected from the target object illuminates the image sensor, and different proportions of the reflected light will illuminate the image sensor depending on the target magnification of the optical subsystem, the intensity of the target wavelength light can be determined by compensating the original brightness with the target magnification. Since the light reflected from the target object is ambient light and its frequency does not change during reflection, the ambient light brightness of the target wavelength light can be considered as the intensity of the light incident on the target object. According to the definition of reflectance, the reflectance of the target object can be determined when the intensity of the incident light and the intensity of the reflected light are known. Therefore, the reflectance of the target object for the target wavelength light can be calculated based on the corrected brightness and the ambient light brightness. Furthermore, since the process calculates reflectance based on the definition of reflectance, there is no need to set up a diffuse reflector with a known reflectance for calibration, thus making it highly efficient.

[0088] On the other hand, in the reflectivity determination method provided in this application, the reflectivity is calculated based on the raw image data sensed by the image sensor. Unlike the DN value, the raw image data is RAW data without ISP. Therefore, the pixel values ​​of the pixels in the raw image data are not affected by ISP, and can relatively accurately reflect the true brightness of the light reflected by the target object. The reflectivity determined by the reflectivity determination method provided in this application is more accurate.

[0089] Of course, implementing any product or method of this application does not necessarily require achieving all of the advantages described above at the same time. Attached Figure Description

[0090] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other embodiments can be obtained based on these drawings.

[0091] Figure 1 A schematic flowchart of a reflectance determination method provided in an embodiment of the present invention;

[0092] Figure 2 This is a schematic flowchart of an original brightness compensation method provided in an embodiment of the present invention;

[0093] Figure 3 This is a schematic diagram of the light inlet of a multispectral camera provided in an embodiment of the present invention;

[0094] Figure 4 A schematic diagram of the placement of a multispectral camera provided in an embodiment of the present invention;

[0095] Figure 5 This is a schematic diagram of the structure of a reflectivity determination device provided in an embodiment of this application;

[0096] Figure 6 This is a schematic diagram of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0097] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art based on this application are within the scope of protection of this application.

[0098] To provide a clearer explanation of the reflectance determination method provided in this application, the relevant terms used in this document will be explained below:

[0099] Vegetation indices: Based on the spectral characteristics of vegetation, various vegetation indices are calculated by combining image data of vegetation in different bands. Vegetation indices are commonly used in fields such as agricultural remote sensing, land cover, and mineral identification.

[0100] A diffuse reflective plate with known reflectivity: a flat plate with diffuse reflectivity, and the reflectivity of each spectral band on the surface of the plate is known.

[0101] DN (Digital Number) value: The pixel value of an image directly captured by a digital camera, that is, a pixel value that has not been corrected to a unit with specific physical meaning.

[0102] ISP (Image Signal Processing): Image signal processing mainly involves a series of processing steps on the image signals output by the image sensor in the imaging system to obtain image results suitable for human eye observation.

[0103] RAW data: Raw data directly output by the image sensor, without undergoing non-linear processing such as the ISP image processing module. RAW data is usually in Bayer format and consists of four channels: one blue channel, one red channel, and two green channels (hereinafter referred to as green channel 1 and green channel 2, respectively).

[0104] Multispectral light intensity sensor: A sensor capable of sensing and acquiring the light intensity of incident light in multiple wavelength bands.

[0105] Multispectral imaging system: A camera that can acquire image information of an object in different wavelength ranges. Generally, an imaging system that can acquire images of an object in two or more different wavelength spectral ranges is called a multispectral imaging system.

[0106] The following will exemplify one possible application scenario of the reflectance determination method provided in this application. It should be understood that the following example is only one possible application scenario of the reflectance determination method provided in this application. In other possible embodiments, the reflectance determination method provided in this application can also be applied to other possible application scenarios. The following example does not limit this in any way.

[0107] Crops are often planted over large areas, making it inefficient to determine their growth and pest / disease status through manual inspections. One relevant technology utilizes multispectral imaging systems to photograph crop areas, obtaining images of crops at different wavelengths. Based on these images, the reflectance of the crop area to different wavelengths of light is determined, resulting in a vegetation index. Because crops exhibit different reflectance spectra at different growth stages, differ from the ground's reflectance spectrum, and vary between healthy and diseased crops, the vegetation index can be used to determine crop coverage, growth status, and pest / disease status, effectively improving crop management efficiency.

[0108] Method 1:

[0109] A diffuse reflector with known reflectivity is pre-placed within the crop area. For each wavelength band of the crop image, the brightness of the crop area and the brightness of the diffuse reflector are determined from the crop image. The ratio of the crop area's brightness to the diffuse reflector's brightness, multiplied by the reflectivity of the diffuse reflector for that wavelength band, gives the reflectivity of the crop area for that wavelength band. This allows for the calculation of the reflectivity of the crop area for different wavelength bands of light.

[0110] Method 2:

[0111] For each band of crop image, the reflectance of the crop region to that band of light is directly calculated based on the pixel value of the pixel in the crop image.

[0112] For Method 1, a diffuse reflector with known reflectivity needs to be pre-set within the crop area. When the crop area is large, setting up the diffuse reflector requires significant time and manpower, resulting in low efficiency. For Method 2, since the pixel values ​​of each pixel in the crop image are DN values, which are the image results obtained through ISP (Image Signal Processing), and different multispectral imaging systems use different ISP methods—for example, some multispectral imaging systems perform significant brightness compensation during ISP, while others only perform minor compensation—the calculation results of Method 2 are significantly affected by the ISP process of the multispectral imaging system, making it difficult to calculate accurate reflectivity.

[0113] Based on this, this application provides a method for determining reflectance, which can be applied to any electronic device with reflectance determination functionality, including but not limited to servers and personal computers. The method is as follows: Figure 1 As shown, Figure 1 A flowchart illustrating a method for determining reflectance provided in an embodiment of the present invention includes:

[0114] S101, acquire the raw image data of the target band collected by the image sensor in the multispectral imaging system when the multispectral imaging system captures the target object.

[0115] S102, determine the original brightness of the target object based on the pixel value of the target pixel in the original image data.

[0116] Among them, the original brightness is positively correlated with the pixel value.

[0117] S103, based on the target magnification of the optical subsystem of the multispectral imaging system, compensates for the original brightness to obtain the corrected brightness.

[0118] S104. Based on the corrected brightness and the ambient light brightness of the target wavelength in the environment where the target object is located, determine the reflectivity of the target object to the target wavelength.

[0119] Among them, reflectivity is positively correlated with the corrected brightness and negatively correlated with the ambient light brightness.

[0120] Using the reflectance determination method provided in this application, since the image sensor in the multispectral imaging system converts the sensed light signal into image data, the pixel value of the target pixel in the original image data is obtained by the image sensor sensing the light signal reflected by the target object. This reflects the intensity of the target wavelength light in the light reflected from the target object to the image sensor. Furthermore, since not all the light reflected from the target object illuminates the image sensor, and different proportions of the reflected light will illuminate the image sensor depending on the target magnification of the optical subsystem, the intensity of the target wavelength light in the reflected light can be determined by compensating for the original brightness in conjunction with the target magnification. Since the light reflected from the target object is ambient light and its frequency does not change during reflection, the ambient light brightness of the target wavelength light can be considered as the intensity of the light incident on the target object. According to the definition of reflectance, the reflectance of the target object can be determined when the intensity of the incident light and the intensity of the reflected light are known. Therefore, the reflectance of the target object for the target wavelength light can be calculated based on the corrected brightness and the ambient light brightness. Furthermore, since this process calculates reflectance based on the definition of reflectance, there is no need to set up a diffuse reflection plate with known reflectance for calibration, thus making it more efficient. This solves the problem mentioned in Method 1.

[0121] On the other hand, in the reflectivity determination method provided in this application, the reflectivity is calculated based on the raw image data sensed by the image sensor. Unlike the DN value, the raw image data is RAW data without ISP. Therefore, the pixel values ​​of the pixels in the raw image data are not affected by ISP, and can reflect the true brightness of the light reflected by the target object relatively accurately. Therefore, compared with the aforementioned method two, the reflectivity determined by the reflectivity determination method provided in this application is more accurate.

[0122] The following will explain S101-S104 respectively:

[0123] In S101, the multispectral imaging system consists of an image sensor and an optical subsystem. The optical subsystem guides the light incident on it to the photosensitive surface of the image sensor, enabling the image sensor to sense this light and generate raw image data. The raw image data is the aforementioned RAW data, referring to image data that has not undergone ISP processing. For ease of description below, only the case where the raw image data is in Bayer format will be explained. The principle is the same for other formats of raw image data, so it will not be elaborated further here.

[0124] The target band can be one band or multiple bands. For example, if it is necessary to calculate the Normalized Difference Vegetation Value (NDVI), since NDVI is calculated based on the reflectivity of the target object for near-infrared light and the reflectivity of the red wavelength range, the target band in this application scenario includes the near-infrared band and the red wavelength range. However, if it is only necessary to determine the reflectivity of the target object for blue wavelength range light, then the target band can be the blue wavelength range.

[0125] In S102, the original brightness can be obtained by directly weighting and summing the pixel values ​​of the target pixel in the original image data. For example, using Bayer image data, the pixel values ​​of the two green channels at the target pixel in the original image data are denoted as Data. 0,green1 Data 0,green2 The pixel value of the blue channel is denoted as Data. 0,blue The pixel value of the red channel is denoted as Data. 0,red The original brightness can then be calculated using formula (1):

[0126] Light = α blue *Data 0,blue +α green1 *Data 0,green1 +α green2 *Data 0,green2 +α red *Data 0,red …Formula (1)

[0127] Where, α blue α green1 α green2 and α red Preset weights.

[0128] Alternatively, the original image data can be preprocessed to obtain processed image data, and the original brightness can be calculated based on the pixels where the target object is located in the processed image data. Preprocessing methods include, but are not limited to, any one or more combinations of dark noise correction, channel weighting, and scaling. For example, in one possible embodiment, the preprocessing method only includes dark noise correction; in another possible embodiment, the preprocessing method includes dark noise correction and channel weighting; in yet another possible embodiment, the preprocessing method includes channel weighting and scaling; and in still another possible embodiment, the preprocessing method includes dark noise correction, channel weighting, and scaling.

[0129] Regarding dark noise correction, this application does not impose any restrictions on the method of dark noise correction. Any dark noise correction method can be used. It is understood that the light signal sensed by the image sensor may include some noise light signals in addition to the light reflected by the target object. These noise light signals may cause the original brightness to be determined to be inaccurate. Therefore, the influence of these dark noise light signals on the original brightness can be reduced or even eliminated by dark noise correction, thereby improving the accuracy of the determined reflectance.

[0130] For channel weighting, the principle is the same as in the aforementioned formula (1). The pixel value of each pixel in the processed image obtained through channel weighting is the brightness. In one possible example, the original image data is first corrected for dark noise, and the resulting image data is denoted as Data1. The data of the blue channel in Data1 is denoted as Data1. 1,blue The data for the two green channels are respectively denoted as Data. 1,green1 Data 1,green2 The data in the red channel is denoted as Data. 1,red The channel weighting method can be performed according to formula (2):

[0131] Data2=β blue *Data 1,blue +β green1 *Data 1,green1 +β green2 *Data 1,green2 +β red *Data 1,red …Formula (2)

[0132] Where Data2 is the image data obtained through channel weighting, β blue β green1 β green2 β red This refers to the pre-set weights for each color channel. These weights can be set based on user experience and / or actual needs, or they can be set based on the signal-to-noise ratio (SNR) of each color channel, with higher SNR channels receiving higher weights. For example, if the SNR of the red channel > the SNR of green channel 1 > the SNR of green channel 2 > the SNR of the blue channel, then β... red >β green1 >β green2 >β blue .

[0133] By using this embodiment, the influence of noisy light signals in the weighted results can be reduced or even eliminated as much as possible through channel weighting, thereby obtaining a more accurate original brightness based on the weighted results, and thus improving the accuracy of the calculated refractive index.

[0134] It is understandable that the signal-to-noise ratio (SNR) of the data from each channel sensed by the image sensor is band-dependent. For example, for light in the first band, the blue channel in the raw image data sensed by the image sensor has a higher SNR, while the other color channels have a lower SNR. For light in the second band, the red channel in the raw image data sensed by the image sensor has a higher SNR, while the other color channels have a lower SNR.

[0135] Based on this, in one possible embodiment, for each color channel, the weight corresponding to the target band can be determined according to the correspondence between the preset band and the weight for that color channel, and this weight can be used as the preset weight for that color channel.

[0136] The representation of the correspondence can vary depending on the application scenario, and may include, but is not limited to, functions, tables, and linked lists. For ease of description, the following text uses a table as an example to illustrate the correspondence, as shown in Table 1:

[0137] 450nm 560nm 660, 720, 750nm 850nm Blue Channel 1 0 0 0.25 Green Channel 1 0 0.5 0 0.25 Green Channel 2 0 0.5 0 0.25 Red Channel 0 0 1 0.25

[0138] Table 1 shows the mapping relationship between bands and weights for different color channels.

[0139] In Table 1, the 1 in the second row and second column indicates that the weight of the 450nm band is 1 for the blue channel. Similarly, the 1 in the third row and second column indicates that the weight of the 450nm band is 0 for the green channel, and so on. It is understood that Table 1 is merely an example of the correspondence provided in this application. In other possible embodiments, the band division, the number of color channels, and the weights corresponding to each band can be different, and Table 1 does not impose any limitations on this.

[0140] For scaling, the original image data can be scaled to a preset size, such as 800*600, to facilitate subsequent unified processing.

[0141] For situations requiring multiple preprocessing steps, the order of each preprocessing step can be set according to actual needs. For example, assuming that the preprocessing includes dark noise correction, channel weighting, and scaling, the original image data can be dark noise corrected first, then the dark noise corrected result can be channel weighted, and then the channel weighted result can be scaled. Alternatively, the original image data can be scaled first, the scaled result can be dark noise corrected, and then the dark noise corrected result can be channel weighted. Other orders are also possible, and this application does not impose any restrictions on them.

[0142] In S103, the compensation method can be viewed as a function with the original brightness and target magnification as independent variables and the corrected brightness as the dependent variable. The corrected brightness can be determined by substituting the original brightness and target magnification. For the original brightness, this function can be either a linear function or a nonlinear function.

[0143] For example, in one possible embodiment, the compensation can be carried out in the following manner: Figure 2 As shown, Figure 2 A schematic flowchart of the original brightness compensation method provided in an embodiment of the present invention includes:

[0144] S1031, according to the preset correspondence between magnification and compensation coefficient, determine the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system.

[0145] S1032, calculate the product of the compensation coefficient and the original brightness to obtain the corrected brightness.

[0146] In S1031, the relationship between magnification and compensation coefficient can be represented in any form, such as a function, table, or linked list. For ease of description, the following text will only use a table as an example. This relationship can be represented as shown in Table 2:

[0147] Magnification Z1 Z2 ... Zn compensation coefficient k1 k2 … kn

[0148] Table 2. Correspondence between magnification and compensation coefficient

[0149] The second column in Table 2 indicates that the compensation coefficient for magnification Z1 is k1, the third column indicates that the compensation coefficient for magnification Z2 is k2, and so on. It is understandable that the magnification of the optical subsystem may differ in different application scenarios. For tables or other methods that can only represent discrete magnification and compensation coefficient relationships, if the relationship includes compensation coefficients for all magnifications, a large number of compensation coefficients for each magnification would need to be recorded, consuming significant system resources.

[0150] Based on this, in one possible embodiment, multiple standard magnifications and compensation coefficients are recorded only in the correspondence relationship. When the target magnification is the standard magnification, the compensation coefficient corresponding to the standard magnification equal to the target magnification is determined according to the correspondence relationship and used as the target compensation coefficient. When the target magnification is not the standard magnification, the compensation coefficients corresponding to each standard magnification are fitted to obtain the target compensation coefficient corresponding to the target magnification.

[0151] Using this embodiment only requires recording a small number of standard magnifications and corresponding compensation coefficients in the correspondence, which can reduce the system resources occupied by the correspondence.

[0152] Fitting methods include, but are not limited to, linear interpolation, polynomial fitting, etc. For example, in one possible embodiment, the maximum value among all standard magnifications less than the target magnification is determined as the first standard magnification, and the minimum value among all standard magnifications greater than the target magnification is determined as the second standard magnification. For example, taking Table 2 as an example, assuming Z1 < Z2 < ... < Zn, and the target magnification is between Z2 and Z3, then the standard magnifications less than the target magnification are Z1 and Z2, with the maximum value being Z2, while the standard magnifications greater than the target magnification are Z3, Z4, ..., Zn, with the minimum value being Z3. Therefore, the first standard magnification is Z2, and the second standard magnification is Z3.

[0153] After determining the first and second standard magnifications, interpolation is performed according to formula (3) to obtain the target compensation coefficient:

[0154]

[0155] Where k is the target compensation coefficient, Z is the target magnification, Za is the first standard magnification, Zb is the second standard magnification, ka is the compensation coefficient corresponding to the first standard magnification, and kb is the compensation coefficient corresponding to the second standard magnification.

[0156] In S104, the ambient light intensity can be obtained by a multispectral light intensity sensor located in the environment of the target object. The multispectral light intensity sensor and the multispectral imaging system can be two independent devices or they can be integrated together, for example, the multispectral light intensity sensor and the multispectral imaging system can be integrated on a multispectral camera.

[0157] Furthermore, the original image data can be obtained by first capturing the target object through a multispectral imaging system, and then the ambient light intensity can be obtained by sensing the multispectral light intensity sensor. Alternatively, the ambient light intensity can be obtained by first sensing the ambient light intensity through a multispectral light intensity sensor, and then the original image data can be obtained by capturing the target object through a multispectral imaging system.

[0158] For ease of description, ambient light intensity will be denoted as I. e Then, the reflectivity of the target object to the target wavelength can be calculated according to formula (4):

[0159]

[0160] Where P is the reflectivity of the target object to light in the target wavelength band, and I... cTo correct the brightness, for the aforementioned scenario where brightness is linearly corrected, the corrected brightness is equal to the product of the original brightness and the target compensation coefficient. Therefore, formula (4) can be rewritten as formula (5):

[0161]

[0162] Where k is the aforementioned target compensation coefficient, I i The original brightness. And corresponding to the aforementioned preprocessing, which includes at least channel weighting, since the pixel value of each pixel in the processed image data is the brightness, the original brightness is the pixel value of the target object in the processed image data. Therefore, formula (5) can be rewritten as formula (6):

[0163]

[0164] Where B(x, y) is the pixel value of the pixel located at image coordinates (x, y) in the processed image data, and this pixel should be the pixel where the target object is located. Furthermore, the reflectivity of different regions of the target object may differ. For example, when the target object is a region, the reflectivity of different sub-regions may differ due to different vegetation conditions. Therefore, reflectivity can be represented using reflectivity image data. Each pixel in the reflectivity image data corresponds to a location in real space, and this pixel represents the reflectivity of the sub-region of the target object located at that location. For this embodiment, the aforementioned formula (6) can be rewritten as formula (7).

[0165]

[0166] Where P(i,j) is the pixel value of the pixel located at image coordinates (i,j) in the reflectance image data, and B(i,j) is the pixel value of the pixel located at image coordinates (i,j) in the processed image data.

[0167] In one possible embodiment, considering that ambient light may change over time, raw image data is captured and ambient light intensity is sensed as synchronously as possible. It is understood that, for cases where a multispectral light intensity sensor and a multispectral imaging system are integrated into a multispectral camera, to simultaneously capture raw image data and sense ambient light intensity, the light inlet of the multispectral light intensity sensor needs to face the incident direction of the ambient light, while the light inlet of the optical subsystem of the multispectral imaging system needs to face the target object.

[0168] However, the direction of ambient light incident on the target object is often opposite to the direction of the light reflected by the target object. Therefore, only when the light inlet of the multispectral light intensity sensor and the light inlet of the optical subsystem are located on opposite sides of the multispectral camera can the light inlet of the multispectral light intensity sensor face the direction of incident ambient light while the light inlet of the optical subsystem of the multispectral imaging system faces the target object.

[0169] Based on this, in one possible embodiment, the light inlet of the multispectral light intensity sensor and the light inlet of the optical subsystem are located on two opposite surfaces of the multispectral camera, so as to simultaneously capture raw image data and sense ambient light brightness, thereby making the calculated reflectance more accurate.

[0170] In this article, "opposite faces" does not mean that the normals of the two faces are completely opposite, but rather that the inner product of the normals of the two faces is negative. For an example, see [link to example]. Figure 3 , Figure 3 This is a schematic diagram of the light inlet of a multispectral camera provided in an embodiment of the present invention. Figure 3 The two light inlets shown are located on two opposite surfaces, and the normals of the two surfaces are not completely opposite.

[0171] To more clearly illustrate the reflectance determination method provided in this application, the following will provide an illustrative example based on a specific application scenario, taking the calculation of the vegetation index of a target surface area as an example:

[0172] In this application scenario, the target object is the target surface area. The multispectral camera can be mounted on a high frame or tower, or an aircraft carrying the multispectral camera can be flown to the airspace above the target surface area to position the multispectral camera at a high altitude capable of capturing images of the target surface. In this text, "higher" refers to an altitude exceeding a preset altitude threshold. The multispectral camera is adjusted so that the entrance port of the optical subsystem is aligned with the target surface area, and the entrance port of the multispectral light intensity sensor is aligned with the sky. For example,... Figure 4 As shown, Figure 4 This is a schematic diagram illustrating the placement of a multispectral camera according to an embodiment of the present invention.

[0173] A multispectral camera captures image data of the target surface area, obtains raw image data of the target band collected by the image sensor, and simultaneously senses the intensity of ambient light to obtain spectral response data. The intensity corresponding to the target band is read from the spectral response data as the ambient light brightness.

[0174] Based on the raw image data and ambient light intensity acquired by the multispectral camera, combined with the target magnification of the optical subsystem, the reflectance of the target surface area to light of each target wavelength is obtained according to any of the aforementioned reflectance determination methods. The calculated reflectance is then substituted into the preset vegetation index calculation formula to calculate the vegetation index of the target surface area.

[0175] It is understandable that the vegetation index calculation formula may be different in different application scenarios, and different vegetation index calculation formulas require different target surface areas to reflect light of different wavelengths. For example, the aforementioned NDVI calculation formula is shown in formula (8):

[0176]

[0177] Among them, P nir P represents the reflectivity of the target surface area to near-infrared light. red This represents the reflectivity of the target surface area for light in the red wavelength range. Therefore, the NDVI calculation formula requires the reflectivity of the target surface area for light in both the near-infrared and red wavelength ranges.

[0178] For ease of description, the band required by the vegetation index calculation formula is referred to as the preset standard band. Since it is difficult to determine the preset standard band when collecting data, the preset standard band may be different from the target band. The reflectance calculated by the aforementioned reflectance calculation method is the reflectance of the target band, which is different from the reflectance required by the formula.

[0179] In one possible embodiment, the target band can include as many bands as possible to reduce the possibility that the preset standard band does not belong to the target band. In another possible embodiment, for each preset standard band, a target band that matches the preset standard band can be determined from the target bands as the matching band corresponding to the preset standard band, and the reflectance of the target area to the light of the matching band can be determined as the target reflectance of the target surface area to the light of the preset standard band, and then substituted into the vegetation index calculation formula to calculate the vegetation index.

[0180] The target band that matches the preset standard band should overlap with the preset standard band as much as possible. For example, assuming the preset standard band includes 780nm-1100nm, and the target band includes 660-750nm and 750-850nm, then the 750-850nm band can be determined as matching the preset standard band. The reflectance of the target surface area to the light in the 750-850nm band is then used as the reflectance of the target surface area to the light in the preset standard band, and the vegetation index is calculated by substituting it into the vegetation index calculation formula.

[0181] Corresponding to the above method embodiments, this application provides a reflectivity determination device, such as... Figure 5 As shown, Figure 5 This is a schematic diagram of a reflectance determination device provided in an embodiment of this application. The device may include the following modules:

[0182] The data acquisition module 501 is used to acquire the original image data of the target band collected by the image sensor in the multispectral imaging system when the multispectral imaging system captures the target object;

[0183] Brightness determination module 502 is used to determine the original brightness of the target object based on the pixel value of the target pixel point in the original image data, wherein the original brightness is positively correlated with the pixel value;

[0184] The brightness compensation module 503 is used to compensate the original brightness according to the target magnification of the optical subsystem of the multispectral imaging system to obtain the corrected brightness;

[0185] The reflectivity determination module 504 is used to determine the reflectivity of the target object to the light of the target wavelength band based on the corrected brightness and the ambient light brightness of the target wavelength band in the environment where the target object is located, wherein the reflectivity is positively correlated with the corrected brightness and negatively correlated with the ambient light brightness.

[0186] In the embodiments of this application, since the image sensor in the multispectral imaging system is used to convert the sensed light signal into image data, the pixel value of the target pixel in the original image data is obtained by the image sensor sensing the light signal reflected by the target object. This reflects the intensity of the target wavelength light in the light reflected from the target object to the image sensor. Furthermore, since not all the light reflected from the target object illuminates the image sensor, and different proportions of the light reflected from the target object will illuminate the image sensor depending on the target magnification of the optical subsystem, the intensity of the target wavelength light in the light reflected from the target object can be determined by compensating the original brightness in conjunction with the target magnification. Since the light reflected from the target object is ambient light and its frequency does not change during reflection, the ambient light brightness of the target wavelength light can be considered as the intensity of the light incident on the target object. According to the definition of reflectivity, the reflectivity of the target object can be determined when the intensity of the incident light and the intensity of the reflected light are known. Therefore, the reflectivity of the target object for the target wavelength light can be calculated based on the corrected brightness and the ambient light brightness. Furthermore, since the process calculates reflectance based on the definition of reflectance, there is no need to set up a diffuse reflector with a known reflectance for calibration, thus making it highly efficient.

[0187] On the other hand, in the reflectivity determination method provided in this application, the reflectivity is calculated based on the raw image data sensed by the image sensor. Unlike the DN value, the raw image data is RAW data without ISP. Therefore, the pixel values ​​of the pixels in the raw image data are not affected by ISP, and can relatively accurately reflect the true brightness of the light reflected by the target object. The reflectivity determined by the reflectivity determination method provided in this application is more accurate.

[0188] In one possible embodiment, the brightness determination module includes:

[0189] The brightness determination first submodule is used to obtain the pixel value of the target pixel point where the target object is located in each color channel from the original image data;

[0190] The second submodule for determining brightness is used to perform a weighted summation of the components of each color channel according to the preset weights set for each color channel to obtain the original brightness of the target object, wherein the preset weights of each color channel are positively correlated with the signal-to-noise ratio of each color channel;

[0191] The device further includes:

[0192] The weight determination module is used to determine the weight corresponding to the target band for each color channel according to the preset correspondence between the bands and weights for the color channel, and use it as the preset weight of the color channel.

[0193] The brightness determination module includes:

[0194] The third submodule for brightness determination is used to perform dark noise correction on the original image data to obtain corrected image data;

[0195] The fourth submodule for determining brightness is used to determine the original brightness of the target object based on the pixel value of the target pixel point in the corrected image data.

[0196] The brightness determination module includes:

[0197] The fifth submodule for brightness determination is used to scale the original image data to obtain processed image data;

[0198] The sixth brightness determination submodule is used to determine the original brightness of the target object based on the pixel value of the target pixel point in the processed image data.

[0199] The brightness compensation module includes:

[0200] The brightness compensation first submodule is used to determine the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system according to the preset correspondence between magnification and compensation coefficient.

[0201] The second submodule for brightness compensation is used to calculate the product of the compensation coefficient and the original brightness to obtain the corrected brightness;

[0202] The correspondence is used to record multiple standard magnifications and compensation coefficients;

[0203] The first submodule for brightness compensation includes:

[0204] The first brightness compensation unit is used to fit the compensation coefficients corresponding to each of the standard magnifications to obtain the target compensation coefficients corresponding to the target magnification of the optical subsystem of the multispectral imaging system.

[0205] The first brightness compensation unit includes:

[0206] A brightness compensation first subunit is used to determine a first standard magnification and a second standard magnification from each of the standard magnifications based on the target magnification of the optical subsystem of the multispectral imaging system, wherein the first standard magnification is the maximum value among all the standard magnifications that are less than the target magnification, and the second standard magnification is the minimum value among all the standard magnifications that are greater than the target magnification.

[0207] The second brightness compensation subunit is used to interpolate the compensation coefficient corresponding to the first standard magnification and the compensation coefficient corresponding to the second standard magnification to obtain the target compensation coefficient corresponding to the target magnification.

[0208] The device further includes:

[0209] An ambient light intensity acquisition module is used to acquire the brightness of the light signal of the target band sensed by the multispectral light intensity sensor during the process of the multispectral imaging system capturing the target object, as the ambient light intensity, wherein the multispectral light intensity sensor is set in the environment where the target object is located.

[0210] The ambient light intensity acquisition module includes:

[0211] The first sub-module for acquiring ambient light brightness is used to acquire spectral response data generated by the multispectral light intensity sensor in response to ambient light during the process of the multispectral imaging system capturing the target object;

[0212] The second sub-module for acquiring ambient light intensity is used to acquire the intensity corresponding to the target band in the spectral response data as ambient light intensity.

[0213] The multispectral light intensity sensor and the multispectral imaging system are integrated into the multispectral camera, and the light inlet of the multispectral light intensity sensor and the light inlet of the optical subsystem are located on two opposite surfaces of the multispectral camera.

[0214] The target object is a target surface area, and the device further includes:

[0215] The index calculation module is used to calculate the vegetation index of the target surface area based on the reflectivity of the target surface area to the light of the target wavelength band.

[0216] The target band includes multiple different bands;

[0217] The index calculation module includes:

[0218] The index calculation first module is used to determine, for each preset standard band, a target band that matches the preset standard band from each target band, as the matching band corresponding to the preset standard band;

[0219] The second index calculation module is used to determine the reflectance of the target surface area to the light of the matching band as the target reflectance of the target surface area to the light of the preset standard band for each preset standard band.

[0220] The third module for index calculation is used to determine the vegetation index corresponding to the target reflectance based on the correspondence between the reflectance of the surface area to the light of the preset standard band and the vegetation index, and use it as the vegetation index of the target surface area.

[0221] Corresponding to the above method embodiments, this application also provides an electronic device, such as... Figure 6 As shown, the system includes a memory 601 and a processor 602. The memory 601 is used to store computer programs; the processor 602 is used to execute the computer programs stored in the memory, implementing the following steps:

[0222] Acquire the raw image data of the target band collected by the image sensor in the multispectral imaging system when the multispectral imaging system captures the target object;

[0223] The original brightness of the target object is determined based on the pixel value of the target pixel point in the original image data, wherein the original brightness is positively correlated with the pixel value;

[0224] The original brightness is compensated to obtain the corrected brightness based on the target magnification of the optical subsystem of the multispectral imaging system.

[0225] Based on the corrected brightness and the ambient light brightness of the target band in the environment where the target object is located, the reflectivity of the target object to the light of the target band is determined, wherein the reflectivity is positively correlated with the corrected brightness and negatively correlated with the ambient light brightness.

[0226] The aforementioned memory may include RAM (Random Access Memory) or NVM (Non-volatile Memory), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0227] The processors mentioned above can be general-purpose processors, including CPUs (Central Processing Units), NPs (Network Processors), etc.; they can also be DSPs (Digital Signal Processors), ASICs (Application Specific Integrated Circuits), FPGAs (Field-Programmable Gate Arrays), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0228] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores a computer program that, when executed by a processor, implements the steps of any of the above-described reflectivity determination methods.

[0229] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute any of the reflectance determination methods described in the above embodiments.

[0230] In the above embodiments, implementation can be achieved entirely or partially through software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented entirely or partially in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a solid-state drive (SSD), etc.

[0231] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0232] The various embodiments in this specification are described in a related manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0233] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application are included within the scope of protection of this application.

Claims

1. A method for determining reflectivity, characterized in that, The method includes: Acquire the raw image data of the target band collected by the image sensor in the multispectral imaging system when the multispectral imaging system captures the target object; The original brightness of the target object is determined based on the pixel value of the target pixel point in the original image data, wherein the original brightness is positively correlated with the pixel value; The original brightness is compensated to obtain the corrected brightness based on the target magnification of the optical subsystem of the multispectral imaging system. Based on the corrected brightness and the ambient light brightness of the target band in the environment where the target object is located, the reflectivity of the target object to the light of the target band is determined, wherein the reflectivity is positively correlated with the corrected brightness and negatively correlated with the ambient light brightness.

2. The method according to claim 1, characterized in that, Determining the original brightness of the target object based on the pixel value of the pixel point where the target object is located in the original image data includes: Obtain the pixel values ​​of the target pixel point where the target object is located in each color channel from the original image data; The components of each color channel are weighted and summed according to the preset weights set for each color channel to obtain the original brightness of the target object. The preset weights of each color channel are positively correlated with the signal-to-noise ratio of each color channel.

3. The method according to claim 2, characterized in that, The method further includes: For each color channel, the weight corresponding to the target band is determined according to the preset correspondence between the bands and weights for the color channel, and is used as the preset weight of the color channel.

4. The method according to claim 1, characterized in that, Determining the original brightness of the target object based on the pixel value of the target pixel point in the original image data includes: The original image data is subjected to dark noise correction to obtain corrected image data; The original brightness of the target object is determined based on the pixel value of the target pixel point in the corrected image data.

5. The method according to claim 1, characterized in that, Determining the original brightness of the target object based on the pixel value of the target pixel point in the original image data includes: The original image data is scaled to obtain processed image data; The original brightness of the target object is determined based on the pixel value of the target pixel point in the processed image data.

6. The method according to claim 1, characterized in that, The step of compensating the original brightness to obtain corrected brightness based on the target magnification of the optical subsystem of the multispectral imaging system includes: According to the preset correspondence between magnification and compensation coefficient, the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system is determined. The corrected brightness is obtained by multiplying the compensation coefficient by the original brightness.

7. The method according to claim 6, characterized in that, The correspondence is used to record multiple standard magnifications and compensation coefficients; The step of determining the target compensation coefficient corresponding to the target magnification of the optical subsystem of the multispectral imaging system according to the preset correspondence between magnification and compensation coefficient includes: By fitting the compensation coefficients corresponding to each of the standard magnifications, the target compensation coefficients corresponding to the target magnification of the optical subsystem of the multispectral imaging system are obtained.

8. The method according to claim 7, characterized in that, The process of fitting the compensation coefficients corresponding to each of the standard magnifications to obtain the target compensation coefficients corresponding to the target magnification of the optical subsystem of the multispectral imaging system includes: Based on the target magnification of the optical subsystem of the multispectral imaging system, a first standard magnification and a second standard magnification are determined from each of the standard magnifications, wherein the first standard magnification is the maximum value among all the standard magnifications that are less than the target magnification, and the second standard magnification is the minimum value among all the standard magnifications that are greater than the target magnification. Interpolate the compensation coefficients corresponding to the first standard magnification and the second standard magnification to obtain the target compensation coefficient corresponding to the target magnification.

9. The method according to claim 1, characterized in that, The method further includes: The brightness of the light signal in the target band sensed by the multispectral light intensity sensor during the process of the multispectral imaging system capturing the target object is obtained as the ambient light brightness, wherein the multispectral light intensity sensor is set in the environment where the target object is located.

10. The method according to claim 8, characterized in that, The acquisition of the brightness of the light signal in the target band sensed by the multispectral light intensity sensor during the process of the multispectral imaging system capturing the target object includes: Acquire spectral response data generated by the multispectral light intensity sensor in response to ambient light during the process of the multispectral imaging system capturing the target object; The intensity corresponding to the target band in the spectral response data is obtained as the ambient light intensity.

11. The method according to claim 9, characterized in that, The multispectral light intensity sensor and the multispectral imaging system are integrated into the multispectral camera, and the light inlet of the multispectral light intensity sensor and the light inlet of the optical subsystem are located on two opposite surfaces of the multispectral camera.

12. The method according to claim 1, characterized in that, The target object is a target surface area, and the method further includes: The vegetation index of the target surface area is calculated based on the reflectivity of the target surface area to the target wavelength.

13. The method according to claim 12, characterized in that, The target band includes multiple different bands; The step of calculating the vegetation index of the target surface area based on the reflectivity of the target surface area to the target wavelength includes: For each preset standard band, a target band that matches the preset standard band is determined from each of the target bands and used as the matching band corresponding to the preset standard band; For each of the preset standard bands, the reflectivity of the target surface area to the light of the matching band is determined as the target reflectivity of the target surface area to the light of the preset standard band. Based on the correspondence between the reflectance of the surface area to the light of the preset standard band and the vegetation index, the vegetation index corresponding to the target reflectance is determined as the vegetation index of the target surface area.

Images