CN117074318A - Snapshot-mosaic type multispectral imaging type crop growth sensing device crosstalk information removing method - Google Patents

Snapshot-mosaic type multispectral imaging type crop growth sensing device crosstalk information removing method Download PDF

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CN117074318A
CN117074318A CN202310860144.3A CN202310860144A CN117074318A CN 117074318 A CN117074318 A CN 117074318A CN 202310860144 A CN202310860144 A CN 202310860144A CN 117074318 A CN117074318 A CN 117074318A
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mosaic
wave band
snapshot
sensing device
crop growth
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朱艳
王永贤
张小虎
曹卫星
姚霞
张羽
郑恒彪
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Shennong Intelligent Agricultural Research Institute Nanjing Co ltd
Nanjing Agricultural University
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Nanjing Agricultural University
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformations in the plane of the image
    • G06T3/40Scaling of whole images or parts thereof, e.g. expanding or contracting
    • G06T3/4015Image demosaicing, e.g. colour filter arrays [CFA] or Bayer patterns
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing
    • G06T2207/10036Multispectral image; Hyperspectral image
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30181Earth observation
    • G06T2207/30188Vegetation; Agriculture

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Abstract

The invention discloses a method for removing crosstalk information of a snapshot-mosaic multispectral imaging type crop growth sensing device, which comprises the following steps: s1, a snapshot-mosaic multispectral imaging type crop growth sensing device acquires uniform light source images of different wave bands; s2, extracting the average value of gray values of pixel positions corresponding to each wave band after the wave band of the spectrometer is subjected to stepping light splitting according to the wave band setting of the mosaic filter, and carrying out Gaussian fitting on the gray values of each corresponding position; s3, performing least square fitting on the original data and the Gaussian fitted data, and outputting a correction coefficient matrix; s4, eliminating data crosstalk between the bands of the original spectrum image by using the correction coefficient matrix. The invention effectively solves the problem of spectrum information crosstalk caused by the installation distance between the mosaic filter and the detector, and has the characteristics of universality, simplicity and the like.

Description

Snapshot-mosaic type multispectral imaging type crop growth sensing device crosstalk information removing method
Technical Field
The invention relates to the field of intelligent agriculture, in particular to a method for removing crosstalk information of a snapshot-mosaic multispectral imaging type crop growth sensing device.
Background
The rapid, lossless and efficient perception of crop growth information is critical for intelligent management of crop growth. The conventional crop growth multispectral imaging sensing device is composed of a plurality of groups of narrow-band interference filters, a plurality of groups of imaging lenses and a plurality of detectors, for example: multispectral cameras such as Airphen in France, reedge in America and Parrot Sequoia in Switzerland are complex in optical-mechanical structure, high in map registration difficulty and high in map information processing requirement, and popularization and application of the instrument are limited.
The mosaic filter plates different wave bands on the same mosaic template, has the technical advantage of high integration level, reduces the complexity of an optical-mechanical structure, can acquire the crop map information of a plurality of spectral bands through a single imaging objective lens, and provides a new scheme for the light weight of the multispectral imaging type crop growth sensing device. However, in order to protect the surface integrity of the image sensor, damage to the image sensor itself is reduced to prolong the service life, when the mosaic filter and the detector are designed and integrated, a certain distance is usually kept between the mosaic filter and the detector, and even if the installation distance is smaller, part of wave band information can enter pixels of adjacent or other wave band regions, so that information crosstalk phenomenon occurs between wave bands of the sensor, thereby seriously affecting the accuracy of the acquired crop map information and reducing the monitoring accuracy. At present, a general, simplified and high-efficiency spectral crosstalk information correction method is not found.
Disclosure of Invention
The invention aims to overcome the defects in the background technology and provide a method for removing crosstalk information of a snapshot-mosaic multispectral imaging type crop growth sensing device, which can accurately and efficiently remove the problem of crosstalk information between spectrum bands.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows: s1, a snapshot-mosaic multispectral imaging type crop growth sensing device acquires uniform light source images of different wave bands; s2, extracting the average value of gray values of pixel positions corresponding to each wave band after the wave band of the spectrometer is subjected to stepping light splitting according to the wave band setting of the mosaic filter, and carrying out Gaussian fitting on the gray values of each corresponding position; s3, performing least square fitting on the original data and the Gaussian fitted data, and outputting a correction coefficient matrix; s4, eliminating data crosstalk between the bands of the original spectrum image by using the correction coefficient matrix. The invention effectively solves the problem of spectrum information crosstalk caused by the installation distance between the mosaic filter and the detector, and has the characteristics of universality, simplicity and the like.
Further, the step S1 includes:
s11, arranging a snapshot-mosaic multispectral imaging type crop growth sensing device at the light-emitting end of an integrating sphere of an adjustable monochromatic light source system;
s12, connecting a computer with a snapshot-mosaic type multispectral imaging type crop growth sensing device and an adjustable monochromatic light source system, adjusting the exposure time and the gain value of the snapshot-mosaic type multispectral imaging type crop growth sensing device to be 100ms and 6dB, adjusting the corresponding wave band of the adjustable monochromatic light source system according to the wave band of a mosaic filter, searching the wave band with the highest gray value in the mosaic filter, and then adjusting the gray value of the snapshot-mosaic type multispectral imaging type crop growth sensing device to be 880-920 under the condition of the wave band with the highest gray value, and taking the exposure time and the gain value at the moment as reference values;
s13, adjusting the wave band of the adjustable monochromatic light source system by utilizing a computer, firstly setting the minimum wave band value of the adjustable monochromatic light source system to be smaller than the minimum wave band value of the mosaic filter, setting the maximum wave band value to be larger than the maximum wave band value of the mosaic filter, further enabling the wave band of the adjustable monochromatic light source system to be capable of covering the spectral range set by the snapshot-mosaic multispectral imaging type crop growth sensing device in a whole range, and adjusting the wave band of the spectrometer in a stepping manner at 2nm intervals between the minimum wave band and the maximum wave band of the spectrometer;
s14, a snapshot-mosaic type multispectral imaging crop growth sensing device is controlled by a computer, and uniform light source images of each spectral band which are transmitted to the inside of the adjustable monochromatic light source integrating sphere after the stepped light splitting of the spectrometer band of the adjustable monochromatic light source system is obtained.
Further, the step S2 includes:
s21, taking the wave band arrangement in the mosaic filter as a basis, extracting a spectral image of each wave band obtained by a snapshot-mosaic multispectral imaging type crop growth sensing device after the step light splitting of the spectrometer of the adjustable monochromatic light source system, and extracting a gray value average value of a corresponding pixel position according to each wave band position on the mosaic filter;
s22, drawing a gray value response chart according to the gray value average value of each stepping band extracted from the pixel area corresponding to each band on the mosaic filter, and recording the gray value average value original matrix data of the pixel area corresponding to each band as an original matrix A.
S23, gaussian fitting is carried out on the wave band and gray value average value constructed in the process of step-by-step adjustment of the adjustable monochromatic light source system at the corresponding pixel position of each wave band on the mosaic filter, and Gaussian curve data of each wave band on the mosaic filter are recorded as a target matrix B.
Further, the step S3 includes: performing least square fitting on the original matrix A in the step S22 and the target matrix B in the step S23, and solving a correction coefficient matrix X, wherein the specific calculation formula is as follows: ax=b.
Further, in S4, the crosstalk information of the input original spectrum image may be removed by the correction coefficient matrix X, and the calculation formula is as follows:
wherein P is i Representing an i-th band corrected reflectance value matrix, X ji Correction coefficient indicating the position of the ith row and ith column in the correction coefficient matrix table, O j The matrix of the original reflectivity values of the jth wave band is represented, and n represents the number of the wave bands.
The beneficial effects of the invention are as follows: the snapshot-mosaic multispectral imaging type crop growth sensing device is used for acquiring uniform light source images in different wave bands, so that the influence of illumination change on the uniformity of the gray value average value of the images in different wave bands is overcome; the gray value average value of each stepping band extracted from the pixel area of each band on the mosaic filter is used as an original matrix, a Gaussian curve data matrix after Gaussian fitting of the original matrix is used as a target matrix, a relation between the original matrix and the target matrix is constructed through a least square method, a crosstalk correction coefficient matrix is obtained, and finally the crosstalk correction coefficient is used for correcting the original spectrum information of each band, so that crosstalk among the spectrum information of different bands is eliminated, and the problem of data crosstalk caused by gaps when the mosaic filter and the detector are integrated among the data of different bands is solved.
Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
FIG. 1 is a schematic diagram of a snapshot-mosaic type multispectral imaging crop growth sensor
FIG. 2 is a schematic diagram showing the correspondence of mosaic filter bands of a snapshot-mosaic type multispectral imaging crop growth sensing device
FIG. 3 is a schematic flow chart of a method for removing spectral crosstalk information of a snapshot-mosaic type multispectral imaging crop growth sensing device according to the present invention
FIG. 4 is a statistical chart of actual reflectance values of the calibration cloth before and after removing spectral crosstalk information of a snapshot-mosaic type multispectral imaging crop growth sensing device
Marked in the figure as: 1-imaging objective lens, 2-protective glass, 3-mosaic filter and 4-CMOS detector.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples.
As shown in fig. 1 and 2, the snapshot-mosaic multispectral imaging crop growth sensing device comprises an imaging objective lens 1, a protective glass 2, a mosaic filter 3 and a CMOS detector 4, wherein the mosaic filter 3 is arranged on the surface of the CMOS detector 4, and each wave band area on the mosaic filter 3 corresponds to each pixel of the CMOS detector 4 one by one. Next, a specific embodiment is illustrated with respect to a mosaic filter 3 having bands 458nm, 487nm, 527nm, and 558nm as central bands, the mosaic filter 3 having excellent spatial uniformity and spectral uniformity.
In the invention, in order to ensure that each wave band image acquired by the snapshot-mosaic multispectral imaging type crop growth sensing device is a uniform light source image, an adjustable monochromatic light source system of Beijing Zhuo Lihan light instrument limited company is adopted, the system comprises a wide spectrum light source with the spectrum coverage range of 350-2500nm, a spectrometer with the spectrum range of 350-1100nm, an integrating sphere with the light outlet aperture of 50mm and the uniformity of more than 98 percent, and the snapshot-mosaic multispectral imaging type crop growth sensing device is used for acquiring uniform spectrum images with different wave bands.
As shown in fig. 3, a method for removing crosstalk information of a snapshot-mosaic multispectral imaging type crop growth sensing device includes the following steps:
step S1: a computer is used for controlling a snapshot-mosaic multispectral imaging type crop growth sensing device to acquire uniform light source images of different wave bands; the step S1 is specifically divided into the following 3 small steps:
step S11, arranging a snapshot-mosaic multispectral imaging type crop growth sensing device at the light-emitting end of an integrating sphere of an adjustable monochromatic light source system;
step S12: the method comprises the steps of connecting a computer with a snapshot-mosaic type multispectral imaging type crop growth sensing device and an adjustable monochromatic light source system, firstly adjusting the exposure time and gain value of the snapshot-mosaic type multispectral imaging type crop growth sensing device to be 100ms and 6dB respectively through the computer, then adjusting the wave bands of a spectrometer of the adjustable monochromatic light source system to be 458nm, 487nm, 527nm and 558nm respectively, wherein the gray value of an image is the maximum value under the wave band setting of 558nm, and then adjusting the gray value of the snapshot-mosaic type multispectral imaging type crop growth sensing device to be 880-920 under the wave band setting of 558nm, and taking the exposure time 950ms and the gain value 4dB at the moment as reference values.
Step S13: the wave band of the adjustable monochromatic light source system spectrometer is adjusted to 350nm by a computer (the minimum wave band value of the adjustable monochromatic light source system is set to be the minimum wave band value of the mosaic filter minus 108 nm), the wave band value of the adjustable monochromatic light source system spectrometer is stepped at intervals of 2nm, the range of step adjustment is 350-700nm (the maximum wave band value of the adjustable monochromatic light source system is set to be the maximum wave band value of the mosaic filter plus 142 nm), and the spectral range of the snapshot-mosaic multispectral imaging type crop growth sensing device can be covered on the whole;
step S14: the snapshot-mosaic type multispectral imaging type crop growth sensing device is controlled by a computer to obtain uniform light source images of each spectral band which are transmitted to the inside of the integrating sphere after the light of the stepping band of the spectrometer of the adjustable monochromatic light source system is split.
Step S2: extracting the gray value average value of the pixel positions corresponding to each wave band after the wave band of the spectrometer is subjected to stepping light splitting according to the wave band setting of the mosaic filter, and carrying out Gaussian fitting on the gray values of the corresponding positions; the step S2 is specifically divided into the following 3 small steps:
step S21: based on the wave bands (458 nm, 487nm, 527nm and 558 nm) in the mosaic filter 3, extracting each wave band spectrum image obtained by the snapshot-mosaic multispectral imaging type crop growth sensing device after the step of the adjustable monochromatic light source system spectrometer, and extracting the corresponding gray value average value according to each wave band position on the mosaic filter 3;
step S22: according to the average value of gray values of each stepping band extracted by the pixel areas of each band of the mosaic filter 3, a gray value response graph (shown in fig. 3 (a)) is drawn by utilizing MATLAB software, and the original matrix data of the response gray value average value of the pixel areas of each band is recorded as an original matrix a.
Step S23, performing Gaussian fitting on a response curve graph of the average value of the wave band and the gray value constructed in the process of step-by-step adjustment of the spectrum instrument of the adjustable monochromatic light source system on the pixel position of each wave band on the mosaic filter 3 by utilizing MATLAB software, and extracting a data value of the Gaussian curve (shown in fig. 3 (B)) of each wave band as a target matrix B.
Step S3: performing least square fitting on the original matrix a in the step S22 and the target matrix B in the step S23, and solving a crosstalk correction coefficient matrix X (table 1 and fig. 3 (c)), where a specific calculation formula is as follows: ax=b. The response curve after correction of the original matrix a of response values is shown in fig. 3 (d).
TABLE 1 Crosstalk correction coefficient matrix Table
In the invention, the proposed method for removing crosstalk information of the snapshot-mosaic type multispectral imaging crop growth sensing device is verified by using 25% reflectance calibration cloth of American Group 8Technology company. Converting an image DN value acquired by a snapshot-mosaic multispectral imaging type crop growth sensing device into a reflectivity value by using black-white calibration, and calculating by the following formula:
wherein R is the reflectivity value of the target object obtained by calculation, DN raw Original D for the acquired target imageN, DN d For dark background DN value, DN w For obtaining DN value of image of reference calibration plate, R w Is the reflectance value of the reference calibration plate.
Step S4: and eliminating data crosstalk between the bands of the original spectrum image by using the correction coefficient matrix. Based on the calculated crosstalk correction coefficient matrix X of each wave band, calculating the reflectivity value of each wave band after removing crosstalk of the reflectivity original matrix O of the obtained 25% reflectivity calibration cloth by the following formula:
wherein P is i Representing an i-th band corrected reflectance value matrix, X ji Correction coefficient indicating the position of the ith row and ith column in the correction coefficient matrix table, O j Representing the original reflectivity value matrix of the jth wave band.
In the invention, the implementation effect of the method for removing crosstalk information of the snapshot-mosaic multispectral imaging type crop growth sensing device is shown in fig. 4, the reflectivity of each wave band before crosstalk removal in fig. 4 has a larger difference from the actual reflectivity value, the error value range is 2% -14%, the difference between the actual reflectivity value and the actual reflectivity value after the information crosstalk is removed is greatly reduced, the error value is less than 2.3%, the method completely meets the actual requirement, and the method for removing the crosstalk of the wave band information has a very good effect.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It should be understood by those skilled in the art that the above embodiments do not limit the scope of the present invention in any way, and all technical solutions obtained by equivalent substitution and the like fall within the scope of the present invention.
The invention is not related in part to the same as or can be practiced with the prior art.

Claims (5)

1. A method for removing crosstalk information of a snapshot-mosaic multispectral imaging type crop growth sensing device is characterized by comprising the following steps:
s1, a snapshot-mosaic multispectral imaging type crop growth sensing device acquires uniform light source images of different wave bands;
s2, extracting the average value of gray values of pixel positions corresponding to each wave band after the wave band of the spectrometer is subjected to stepping light splitting according to the wave band setting of the mosaic filter, and carrying out Gaussian fitting on the gray values of each corresponding position;
s3, performing least square fitting on the original data and the Gaussian fitted data, and outputting a correction coefficient matrix;
s4, eliminating data crosstalk between the bands of the original spectrum image by using the correction coefficient matrix.
2. The method for removing crosstalk information from a snapshot-mosaic multispectral imaging type crop growth sensing device according to claim 1, wherein S1 comprises:
s11, arranging a snapshot-mosaic multispectral imaging type crop growth sensing device at the light-emitting end of an integrating sphere of an adjustable monochromatic light source system;
s12, connecting a computer with a snapshot-mosaic type multispectral imaging type crop growth sensing device and an adjustable monochromatic light source system, adjusting the exposure time and the gain value of the snapshot-mosaic type multispectral imaging type crop growth sensing device to be 100ms and 6dB, adjusting the corresponding wave band of the adjustable monochromatic light source system according to the wave band of a mosaic filter, searching the wave band with the highest gray value in the mosaic filter, and then adjusting the gray value of the snapshot-mosaic type multispectral imaging type crop growth sensing device to be 880-920 under the condition of the wave band with the highest gray value, and taking the exposure time and the gain value at the moment as reference values;
s13, adjusting the wave band of the adjustable monochromatic light source system by using a computer, firstly setting the minimum wave band value of the adjustable monochromatic light source system to be smaller than the minimum wave band value of the mosaic filter, setting the maximum wave band value to be larger than the maximum wave band value of the mosaic filter, and adjusting the wave band of the spectrometer in a stepping way at 2nm intervals between the minimum wave band and the maximum wave band of the spectrometer;
s14, a snapshot-mosaic type multispectral imaging crop growth sensing device is controlled by a computer, and uniform light source images of each spectral band which are transmitted to the inside of the adjustable monochromatic light source integrating sphere after the stepped light splitting of the spectrometer band of the adjustable monochromatic light source system is obtained.
3. The method for removing crosstalk information from a snapshot-mosaic multispectral imaging type crop growth sensing device according to claim 1, wherein S2 comprises:
s21, taking the wave band setting in the mosaic filter as a basis, extracting spectral images of each wave band obtained by a snapshot-mosaic multispectral imaging type crop growth sensing device after the step light splitting by a spectrometer of an adjustable monochromatic light source system, and extracting gray value average values of corresponding pixel positions according to each wave band position on the mosaic filter;
s22, drawing a gray value response chart according to the gray value average value of each stepping band extracted from the pixel area corresponding to each band on the mosaic filter, and recording the gray value average value original matrix data of the pixel area corresponding to each band as an original matrix A;
s23, gaussian fitting is carried out on the wave band and gray value average value constructed in the process of step-by-step adjustment of the adjustable monochromatic light source system at the corresponding pixel position of each wave band on the mosaic filter, and Gaussian curve data of each wave band on the mosaic filter are recorded as a target matrix B.
4. A snapshot-mosaic multispectral imaging type crop growth sensing device crosstalk information removal method according to claim 3, wherein S3 comprises: performing least square fitting on the original matrix A in the step S22 and the target matrix B in the step S23, and solving a correction coefficient matrix X, wherein the specific calculation formula is as follows: ax=b.
5. The method for removing crosstalk information of a snapshot-mosaic type multispectral imaging type crop growth sensing device according to claim 1, wherein in S4, the crosstalk information of the input original spectral image is removed by a correction coefficient matrix X, and the calculation formula is as follows:
wherein P is i Representing an i-th band corrected reflectance value matrix, X ji Correction coefficient representing the ith row and ith column position in correction coefficient matrix X, O j The j-th band original reflectance value matrix of the original spectrum image to be corrected is represented, and n represents the number of bands.
CN202310860144.3A 2023-07-13 2023-07-13 Snapshot-mosaic type multispectral imaging type crop growth sensing device crosstalk information removing method Pending CN117074318A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118032672A (en) * 2024-02-06 2024-05-14 南京农业大学 Handheld snapshot type multispectral imaging crop growth sensing device

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118032672A (en) * 2024-02-06 2024-05-14 南京农业大学 Handheld snapshot type multispectral imaging crop growth sensing device
CN118032672B (en) * 2024-02-06 2024-08-16 南京农业大学 Handheld snapshot type multispectral imaging crop growth sensing device

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