A method, system, device and medium for characterizing plant leaf water content using polarization information

Abstract

The present invention belongs to the field of polarization detection technology, and specifically relates to a method for characterizing the water content of plant leaves using polarization information, comprising the following steps: S1, using a polarization imaging system to obtain a polarization image of a target leaf; S2, obtaining a Mueller matrix of each pixel of the target leaf based on the polarization image of the target leaf; S3, calculating the covariance matrix corresponding to the Mueller matrix of each pixel, and obtaining an eigenvalue from the covariance matrix; S4, calculating the depolarization index of the target leaf based on the eigenvalue, and displaying the image using the depolarization index value as a grayscale value to obtain a depolarized image. The depolarized image can clearly show the area and range of changes in the microscopic structure of the target leaf, and can obtain more information about the target leaf.

Description

Technical Field

[0001] The present invention belongs to the field of polarization detection technology, and in particular relates to a method, system, device and medium for characterizing the water content of plant leaves using polarization information. Background Art

[0002] Polarization information carries multidimensional vector information and can be used as a carrier to convey richer information. During light propagation, it interacts with and scatters particles in the environment, altering its distribution and the information it carries. Current research on polarization imaging in agriculture and forestry focuses primarily on improving its effectiveness, but has not yet enabled the use of polarization information to detect early changes in plant moisture content.

[0003] Currently, plant moisture content detection methods are mainly divided into two categories. The first category includes methods such as drying and resistance methods. However, since the measurement process requires removing plant leaves or drilling holes in plant stems, it will cause damage to the plants, and therefore has significant limitations in their use scenarios. The second category is non-contact measurement such as spectroscopy and imaging methods. Only by collecting the plant's spectral curve, optical image, etc., can the plant's moisture content be analyzed. However, these methods can only detect changes in moisture content when the plant is in a state of obvious water shortage, and cannot achieve early detection of changes in plant water content.

[0004] Currently, commonly used methods based on light intensity polarization detection capture the average light intensity of the target. However, polarization imaging technology utilizes image processing to transform conventional optical images captured by a camera into polarization images. This polarization image acquisition method can achieve single-pixel polarization imaging detection accuracy. Subsequent calculations produce a Mueller matrix image and a depolarization index image containing the target's polarization information. Compared to traditional optical imaging, polarization imaging technology offers a more comprehensive ability to characterize changes in the target's microstructure, potentially enabling early detection of plant health.

[0005] Currently, research on polarized light imaging technology in agriculture and forestry mainly focuses on how to improve the effect of polarized light imaging to distinguish plant species, and it is still unable to achieve non-destructive detection of early changes in plant moisture content. Summary of the Invention

[0006] The purpose of the present invention is to provide a method, system, device and medium for characterizing the water content of plant leaves using polarization information, thereby solving the problem of early non-destructive detection of plant water content.

[0007] The present invention is achieved through the following technical solutions:

[0008] A method for characterizing the water content of plant leaves using polarization information comprises the following steps:

[0009] S1. Obtain a polarization image of the target blade using a polarization imaging system;

[0010] S2, obtaining the Mueller matrix of each pixel point of the target leaf according to the polarization image of the target leaf;

[0011] S3, calculating the covariance matrix corresponding to the Mueller matrix of each pixel point, and obtaining the eigenvalue from the covariance matrix;

[0012] S4. Calculate the depolarization index of the target leaf according to the characteristic value, and display the image using the depolarization index as a grayscale value to obtain a depolarized image; the depolarized image can intuitively display the early changes in the water content of the plant leaf.

[0013] Furthermore, in S1, the polarization imaging system includes a light source, a collimation system, a polarizer, a sample stage, an analyzer, and a detector; the polarizer includes a first polarizer and a first quarter-wave plate, and the analyzer includes a second quarter-wave plate and a second polarizer;

[0014] The light source emits non-polarized light with stable light intensity. After being collimated by the collimation system, the generated parallel light is incident on the polarization system. After passing through the first polarizer and the first 1 / 4 wave plate, the non-polarized light is modulated into a specific polarization state before being emitted. After the polarized light irradiates the surface of the target leaf to be measured on the sample stage 5, the diffusely reflected light after interacting with the target leaf passes through the second 1 / 4 wave plate and finally passes through the second polarizer and is received by the detector.

[0015] During the measurement process, the first quarter wave plate in the polarizer rotates by an angle of θ each time, while the second quarter wave plate in the analyzer rotates by 5θ in the same direction. N images are obtained by rotating N times.

[0016] Furthermore, S2 specifically includes the following steps:

[0017] 2.1. First, extract the grayscale values ​​of the pixels at the same position in the N collected images to form a column vector I with N columns and one row;

[0018] 2.2, then according to the formula F=(D T D) -1 D T I calculates 25 Fourier coefficients, and then uses the 25 Fourier coefficients to obtain the Mueller matrix of the pixel; thus, x×y Mueller matrices are obtained, where x×y is the size of the acquired polarization image;

[0019] Where D is the wave plate rotation angle correlation matrix, which has N rows and 25 columns; F is the Fourier coefficient matrix to be solved.

[0020] Furthermore, in S4, the depolarization index is given by P Δexpress,

[0021] Among them, P1, P2, and P3 are three components related to the depolarization index.

[0022] Furthermore, the expressions of the three components are:

[0023]

[0024] Among them, λ0, λ1, λ2, and λ3 are the four eigenvalues ​​of the covariance matrix H.

[0025] Furthermore, in S4, the higher the depolarization index, the lower the leaf water content.

[0026] The present invention also discloses a system for implementing the method and using polarization information to characterize the water content of plant leaves, comprising:

[0027] Polarization imaging system, used to obtain polarization images of the target blades;

[0028] A Mueller matrix acquisition module is used to acquire the Mueller matrix of each pixel point of the target blade according to the polarization image of the target blade under test;

[0029] The eigenvalue calculation module is used to calculate the covariance matrix corresponding to the Mueller matrix of each pixel point and obtain the eigenvalue from the covariance matrix;

[0030] The output module is used to calculate the depolarization index of the target leaf according to the characteristic value, and display the image using the depolarization index value as the grayscale value to obtain a depolarized image; the depolarized image can show the early changes in the water content of the plant leaves.

[0031] The present invention also discloses a computer device, including a polarization imaging system, a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, the steps of the method for characterizing the water content of plant leaves using polarization information are implemented.

[0032] The present invention also discloses a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the method for characterizing the water content of plant leaves using polarization information are implemented.

[0033] Compared with the prior art, the present invention has the following beneficial technical effects:

[0034] The present invention discloses a method for characterizing plant leaf moisture content using polarization information. The method obtains the Mueller matrix of each pixel of the target leaf based on a polarized image of the target leaf. The method calculates the covariance matrix H corresponding to the Mueller matrix of each pixel and obtains eigenvalues ​​from the covariance matrix H. The depolarization index of the target leaf is then calculated based on the eigenvalues. The depolarization index value is used as a grayscale value to display the image, thereby obtaining a depolarized image. The depolarized image can reveal early changes in plant leaf moisture content. Compared with existing plant moisture content measurement methods, such as drying and electrical resistance methods, the method can achieve non-destructive testing of plant moisture content without removing the plant leaves or drilling holes in the plant stem. The method only requires fixing the polarization imaging system and capturing images for analysis. Furthermore, a comparison of moisture content measurement results reveals that, during the early stages of leaf moisture content change, the leaf moisture content changes slightly, but characteristic changes are clearly visible on the depolarized image.

[0035] The polarization image acquisition method can reflect the polarization imaging detection accuracy at a single pixel. Currently, the commonly used methods based on light intensity polarization detection only detect the average light intensity of the target, and the methods based on spectral polarization detection obtain the total spectral characteristic curve of the target. Although these methods can show the overall trend of the target to a certain extent, they cannot detect the changes in the microscopic structure of the target. The depolarized image finally obtained by the present invention can clearly show the area and range of changes in the microscopic structure of the target, and can obtain more information about the target. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Schematic diagram of the structure of the polarization imaging system;

[0037] Among them, 1. Light source; 2. Collimation system; 3. First polarizer; 4. First 1 / 4 wave plate; 5. Sample stage; 6. Second 1 / 4 wave plate; 7. Second polarizer; 8. Detector;

[0038] Figure 2 Schematic diagram of the process of obtaining the Mueller matrix image of the target leaf;

[0039] Figure 3 9 ordinary optical images acquired by ordinary optical instruments;

[0040] Figure 4 The Mueller matrix image obtained by the plant moisture content detector is Figure 3 There is a one-to-one correspondence between the two;

[0041] Figure 5 for Figure 4 The depolarized images corresponding to the 9 images in the figure. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solutions and advantages of the present invention more clear, the following is a further detailed description with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. That is, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments.

[0043] The components described and illustrated in the drawings and embodiments of the present invention may be arranged and designed in a variety of different configurations. Therefore, the detailed description of the embodiments of the present invention provided in the following drawings is not intended to limit the scope of the claimed invention, but merely represents a selected embodiment of the present invention. All other embodiments derived by those skilled in the art based on the drawings and embodiments of the present invention without inventive effort shall fall within the scope of protection of the present invention.

[0044] It should be noted that the terms "comprises", "includes" or any other variations are intended to cover non-exclusive inclusion, so that a process, element, method, article or apparatus that includes a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to the process, element, method, article or apparatus.

[0045] The features and performance of the present invention are further described in detail below with reference to the embodiments.

[0046] The present invention discloses a method for characterizing the water content of plant leaves using polarization information, comprising the following steps:

[0047] S1. Use the polarization imaging system to obtain the polarization image of the target leaf:

[0048] like Figure 1 As shown, the polarization imaging system used in the present invention includes a light source 1, a collimation system 2, a polarizer, an analyzer, and a detector 8. The polarizer and the analyzer are both composed of a quarter wave plate and a polarizer. The polarizer includes a first polarizer 3 and a first 1 / 4 wave plate 4, and the analyzer includes a second 1 / 4 wave plate 6 and a second polarizer 7.

[0049] The light first passes through the first polarizer 3 and then the first quarter-wave plate 4 in the polarizer. When reaching the analyzer, it passes through the second quarter-wave plate 6 and then the second polarizer 7. During the measurement process, the first quarter-wave plate 4 in the polarizer is rotated by θ = 6° each time, while the second quarter-wave plate 6 in the analyzer is rotated in the same direction by 5θ = 30°. A total of 30 rotations are performed to obtain 30 images.

[0050] S2, obtaining the Mueller matrix of each pixel point of the target leaf according to the polarization image of the target leaf;

[0051] The solution process of the Mueller matrix is ​​as follows:

[0052] Since the change in polarization state of light after passing through different optical elements can be regarded as the product of the Mueller matrices of all the optical elements it passes through, the polarizers in the polarizer and analyzer in this system are fixed, and their Mueller matrices are known. The Mueller matrix of the first polarizer 3 is recorded as P1, and the Mueller matrix of the second polarizer 7 is recorded as P2; the Mueller matrix of the wave plate is determined by the rotation angle in the technical solution 1, and the Mueller matrix of the first 1 / 4 wave plate 4 is recorded as R1, and the Mueller matrix of the second 1 / 4 wave plate 6 is recorded as R2;

[0053] The Stokes vectors of the incident light and the outgoing light are also known. The Stokes vector of the incident light is denoted as S in , the Mueller matrix of the sample to be tested is recorded as M, and the Stokes matrix of the emitted light is recorded as S out .

[0054] S out =P2R2MR1P1S in (1)

[0055] Since the signal received by the detector 8 is the light intensity value, the Stokes matrix of the incident light and the outgoing light is:

[0056]

[0057]

[0058] The Mueller matrices of the polarizers in the polarizer and analyzer are:

[0059]

[0060] The Mueller matrix of the wave plate is

[0061]

[0062] Where θ is the angle of rotation of the wave plate fast axis relative to the horizontal direction, is the phase delay of the quarter wave plate, so the Mueller matrix R1(θ) of the first quarter wave plate 4 in the polarizer and the Mueller matrix R2(5θ) of the second quarter wave plate 6 in the analyzer are respectively:

[0063]

[0064]

[0065] Combining equations (1) and (7), we can obtain:

[0066]

[0067] Formula (8) can be rewritten as:

[0068]

[0069] In formula (9), m ij is the Mueller matrix element of the target being measured, u ij is the element in the matrix u of the angle-related quantity, u can be written as follows:

[0070]

[0071] Equation (9) can be rewritten into Fourier series form using Equation (10):

[0072]

[0073] The rotation angle of the wave plate is known, and S1 is the light intensity value in the Stokes vector of the outgoing light received by the detector 8. Therefore, the Mueller of the target can be inverted by the Fourier coefficient of formula (11). The relationship between the Fourier coefficient and the Mueller matrix element is as follows:

[0074]

[0075] Solving the 25 Fourier coefficients requires at least 25 data acquisitions, including the light intensity values ​​received by detector 8 and the angle values ​​for each rotation. The waveplate in the polarizer rotates a total of 180°, and detector 8 collects data 25 times. The waveplate angle variation in each set of data is 7.2°. Typically, to improve detection accuracy, the number of measurements is increased to reduce experimental error. When 30 light intensity measurements are used to solve the Fourier coefficients, the maximum angle increment for waveplate R1 is 6°, while that for R2 is 30°. To improve measurement accuracy and reduce error, the number of measurements and the amount of data can also be increased.

[0076] The present invention collects 30 light intensity measurements received by the detector 8, wherein the wave plate angle in the polarizer is varied by 6° and the wave plate angle in the analyzer is varied by 30°. 30 light intensity values ​​yield 30 equations, which are combined to form the following equation:

[0077]

[0078] Simplify formula (13) to the following formula:

[0079] I=DF (14)

[0080] Where I is the light intensity matrix received by the detector 8, which is a column matrix with 30 rows; D is the wave plate rotation angle correlation matrix, which is 30 rows and 25 columns; F is the Fourier coefficient matrix to be solved, which is a column matrix with 25 rows.

[0081] There are 30 equations and 25 unknowns in formula (13), so formula (13) is an overdetermined system of equations, which generally has finite solutions or no solutions. The present invention uses a pseudo-inverse matrix to solve the Fourier coefficients and rewrites formula (14) as follows:

[0082] F=(D T D) -1 D T I (15)

[0083] The relationship between the solved Fourier coefficients and the Mueller matrix elements is shown in the following table.

[0084] a0-a 12 , b1-b 12 Relationship with Mueller matrix elements

[0085]

[0086] In a polarized light imaging system, the detector 8 is generally a CCD, and what is obtained is a polarized image of the target being measured. Since the light intensity is always proportional to the grayscale value of the image, the grayscale value in the image can be directly substituted into the equation for solution.

[0087] By combining the grayscale values ​​of the pixels at the same position in the 30 images into a column vector I, the Mueller matrix of each pixel can be solved. The combination of pixels in the same array element can obtain the Mueller matrix image. Figure 2 As shown, specifically:

[0088] 2.1. First, the grayscale values ​​of the pixels at the same position in the 30 images are extracted to form a column vector I with 30 columns and one row. The image size captured by the camera is 4096×3000.

[0089] 2.2, then according to the formula F=(D T D) -1 D T I calculates 25 Fourier coefficients, and then uses the 25 Fourier coefficients to get the Mueller matrix of the pixel; a total of 4096×3000 Mueller matrices can be obtained;

[0090] Where T is the transpose sign of the matrix; D is the wave plate rotation angle correlation matrix, which is 30 rows and 25 columns; F is the Fourier coefficient matrix to be solved.

[0091] The values ​​of the same array element in all Mueller matrices are combined according to their corresponding pixel points to obtain an image of 16 array elements, and the Mueller matrix image of the target leaf can be obtained.

[0092] like Figure 2 As shown, each pixel can obtain a Mueller matrix. i starts from 1 and goes up to 4096, and j starts from 1 and goes up to 3000. The M(1,1) element of the Mueller matrix of the pixel at position (i,j) is sequentially extracted and the extracted value is placed in the corresponding (i,j) position in the new image until all 4096×3000 points are extracted. At this point, the values ​​of all pixels in the new image are the values ​​of the M(1,1) element. These values ​​are used as grayscale values ​​to obtain the image of the M(1,1) element of the Mueller matrix. The other elements are obtained in the same way.

[0093] S3. Calculate the covariance matrix H of the Mueller matrix and obtain the eigenvalues ​​from the covariance matrix H; the covariance matrix H has four eigenvalues, namely λ0, λ1, λ2, and λ3.

[0094] S4. Calculate the depolarization index of the target blade based on the characteristic value, display the image using the depolarization index value as a grayscale value, and obtain a depolarized image. The depolarized image finally obtained by the present invention can clearly show the area and range of changes in the microscopic structure of the measured target, and can obtain more information about the measured target.

[0095] The depolarization index is given by P Δ The three components of the depolarization index, P1, P2, and P3, can be obtained from the eigenvalues ​​of the covariance matrix of the Mueller matrix image. Then, the parameter P that can characterize the early changes in leaf water content is calculated from these three components. Δ .

[0096]

[0097]

[0098] The higher the depolarization index, the lower the leaf water content.

[0099] The present invention also discloses a system for characterizing the water content of plant leaves using polarization information, comprising:

[0100] Polarization imaging system, used to obtain polarization images of the target blades;

[0101] A Mueller matrix acquisition module is used to acquire the Mueller matrix of each pixel point of the target blade according to the polarization image of the target blade under test;

[0102] The eigenvalue calculation module is used to calculate the covariance matrix H corresponding to the Mueller matrix of each pixel point and obtain the eigenvalue from the covariance matrix H;

[0103] The output module is used to calculate the depolarization index of the target leaf according to the characteristic value, and display the image using the depolarization index value as the grayscale value to obtain a depolarized image; the depolarized image can show the early changes in the water content of the plant leaves.

[0104] like Figure 3 As shown, when there is no polarization information in the image, it is an ordinary optical image, and plant leaves with different water contents cannot be distinguished.

[0105] like Figure 4 As shown in FIG, when the collected image carries polarization information, the Mueller image obtained based on the polarization information has a certain ability to distinguish the water content of plant leaves, but the recognition ability is not strong.

[0106] like Figure 5 As shown in the figure, the depolarized image obtained by Mueller image processing can clearly distinguish plant leaves with different water contents: as the leaf water content gradually decreases, the area of ​​the red area in the mesophyll tissue gradually increases. In other words, the larger the depolarization index value of the image, the lower the water content of the corresponding plant leaf.

[0107] The method for characterizing plant leaf water content using polarization information according to the present invention can be implemented entirely in hardware, entirely in software, or in a combination of software and hardware. Furthermore, the present invention can be implemented as a computer program product embodied on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0108] If the method for characterizing plant leaf water content using polarization information is implemented as a software functional unit and sold or used as a standalone product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the process steps in the above-mentioned method embodiments by using a computer program to instruct the relevant hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and can use any method or technology to store information. The information can be computer-readable instructions, data structures, program modules, or other data. It should be noted that the content of the computer-readable medium can be appropriately expanded or reduced based on the requirements of legislation and patent practice within a jurisdiction. For example, in some jurisdictions, legislation and patent practice do not require that computer-readable media include electric carrier signals and telecommunications signals. Among them, the computer storage medium can be any available medium or data storage device that can be accessed by the computer, including but not limited to magnetic storage (such as floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO)), optical storage (such as CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (such as ROM, EPROM, EEPROM, non-volatile memory (NANDFLASH), solid-state drives (SSDs)), etc.

[0109] In an exemplary embodiment, a computer device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for characterizing the water content of plant leaves based on the use of polarization information are implemented. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0110] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. A method for characterizing the water content of plant leaves using polarization information, characterized in that: The following steps are involved: S1. Obtain a polarization image of the target blade using a polarization imaging system; S2, obtaining the Mueller matrix of each pixel point of the target leaf according to the polarization image of the target leaf; S3, calculating the covariance matrix corresponding to the Mueller matrix of each pixel point, and obtaining the eigenvalue from the covariance matrix; S4. Calculating a depolarization index of the target leaf based on the characteristic value, and displaying the image using the depolarization index as a grayscale value to obtain a depolarized image; the depolarized image can intuitively display early changes in water content of the plant leaf; S2 specifically includes the following steps: 2.

1. First, extract the grayscale values ​​of the pixels at the same position in the N collected images to form a column vector I with N columns and one row; 2.2, then according to the formula Calculate 25 Fourier coefficients, and then use the 25 Fourier coefficients to get the Mueller matrix of the pixel point; then get x×y Mueller matrices, where x×y is the size of the acquired polarization image; Where D is the wave plate rotation angle correlation matrix, which is N rows and 25 columns; F is the Fourier coefficient matrix to be solved; In S4, the depolarization index is given by express, ; Among them, P1, P2, and P3 are three components related to the depolarization index; The expressions of the three components are: ； in, 、 、 、 are the four eigenvalues ​​of the covariance matrix H; In S4, the higher the depolarization index, the lower the leaf water content.

2. The method for characterizing the water content of plant leaves using polarization information according to claim 1, characterized in that: In S1, the polarization imaging system includes a light source (1), a collimation system (2), a polarizer, a sample stage (5), an analyzer, and a detector (8); the polarizer includes a first polarizer (3) and a first quarter wave plate (4); the analyzer includes a second quarter wave plate (6) and a second polarizer (7); The light source (1) emits non-polarized light with stable light intensity. After being collimated by the collimation system (2), the generated parallel light is incident on the polarization system and passes through the first polarizer (3) and the first 1 / 4 wave plate (4). The non-polarized light is modulated into a specific polarization state and then emitted. After the polarized light is irradiated on the surface of the target leaf to be measured on the sample stage (5), the diffuse reflected light after interacting with the target leaf passes through the second 1 / 4 wave plate (6) and finally passes through the second polarizer (7) and is received by the detector (8). During the measurement process, the first quarter wave plate (4) in the polarizer rotates by an angle , while the second quarter wave plate (6) in the analyzer rotates in the same direction , rotating N times will get N images.

3. A system for characterizing plant leaf water content using polarization information, implementing the method of any one of claims 1 or 2, characterized in that: include: Polarization imaging system, used to obtain polarization images of the target blades; A Mueller matrix acquisition module is used to acquire the Mueller matrix of each pixel point of the target blade according to the polarization image of the target blade under test; The eigenvalue calculation module is used to calculate the covariance matrix corresponding to the Mueller matrix of each pixel point and obtain the eigenvalue from the covariance matrix; The output module is used to calculate the depolarization index of the target leaf according to the characteristic value, and display the image using the depolarization index value as the grayscale value to obtain a depolarized image; the depolarized image can show the early changes in the water content of the plant leaves.

4. A computer device comprising a polarization imaging system, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method for characterizing the water content of plant leaves using polarization information as claimed in claim 1 or 2 are implemented.

5. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for characterizing the water content of plant leaves using polarization information as claimed in claim 1 or 2 are implemented.

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