CN101692037A - Method for analyzing chlorophyll distribution on surface of leaves of plant by hyperspectral image and independent component - Google Patents
Method for analyzing chlorophyll distribution on surface of leaves of plant by hyperspectral image and independent component Download PDFInfo
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Abstract
A method for analyzing chlorophyll distribution on surface of leaves of a plant by hyperspectral image and independent component relates to a prediction method of chlorophyll distribution on surface of leaves of a plant. The method is implemented by the following steps: processing of hyperspectral image, analyzing and selecting of independent component, and calculating of chlorophyll distribution on surface of leaves of the plant. The processing of hyperspectral image comprises marking hyperspectral image and extracting spectrum; the analyzing and selecting of independent component comprises: analyzing and calculating the independent component by independent component method, and selecting the optimal independent component according to the regression analysis result; the calculating of chlorophyll distribution on surface of leaves of the plant means using the selected optimal independent component and the model to calculate chlorophyll content value of each point on the surface of leaves to constitute a chlorophyll distribution graph. Under the prerequisite of not damaging the surface of leaves, the chlorophyll content distribution graph obtained in the invention not only can indicate the local chlorophyll content of the leaves, but also can obtain the distribution situation of chlorophyll on the whole surface of the leaves, thus providing basis for intelligent judgment of nutrition situation of the plant.
Description
Technical field
The present invention relates to the Forecasting Methodology that a kind of plant leaf surface chlorophyll distributes; Refer in particular to a kind of method based on high spectrum image and the distribution of independent component analysis plant leaf surface chlorophyll.
Background technology
The phenomenon that crop lacks certain nutrient often appears in the soilless culture, and particularly serious during yielding positive results, usually can only be when the nutritional deficiency phenomenon be obvious, by expert diagnosis nutritional deficiency situation.At the nutritional deficiency initial stage, the nutritional deficiency blade is similar with normal blade, and faint illness is subtle, and the expert also is difficult to make a definite diagnosis, and can have a strong impact on like this to make amount and output, and it is significant therefore to study the plain early stage intelligent diagnostics that lacks of soilless culture crop alimentary.The chlorophyll content of crop is main biochemical parameter, has represented the nutrition condition of plant, and it is significant for correct diagnosis crop alimentary shortage situation that it is carried out dynamic monitoring.
The common method that chlorophyll is measured in the agricultural is a spectrophotometer method, and at 645nm, 663nm measures absorbance down, is converted into chlorophyll content according to formula behind the extraction chlorophyll.Quantitative lossless detection method at leaf chlorophyll, existing relevant patent is as Chinese invention patent at present, application number is 200620135939.X, open day: 2007.10.24, the title of innovation and creation is " chlorophyll measuring apparatus ", this application discloses a kind of portable chlorophyll measuring apparatus, utilizes the transmitted light of blade to detect chlorophyll content, but it can only a bit detect on the blade face certain; Chinese invention patent, application number is 200510085468.6, open day: 2007.1.24, the title of innovation and creation is " based on cotton leaf chlorophyll measuring methods of image technique ", and this application discloses a kind of image technique that utilizes, and carries out chlorophyllous method for measuring at the blade of cotton, but it has utilized two kinds of color signals in the image, accuracy is not high, and only at cotton leaf mensuration, its general applicability is not described.
Hyper-spectral image technique is a kind of light harvesting spectrum information and image information new technology, and this technology is started in military field, has now expanded to earth remote sensing, medical diagnosis and crops growing way remote sensing monitoring aspect.Can think like this, hyper-spectral image technique is spectral analysis technique and the image processing techniques integration technology in minimum data level aspect, have the advantage of these two kinds of technology concurrently, can carry out visual analyzing, also can carry out quantitative forecast inner effective constituent to the surface of research object.
Summary of the invention
The present invention has overcome conventional art and can only detect certain any chlorophyll content and image technique and detect the low problem of chlorophyll content precision, has invented a kind of isolated component method of utilizing and has analyzed the plant leaf surface high spectrum image, predicts the method that its chlorophyll distributes.Under the prerequisite of not damaging the blade face, not only can obtain the chlorophyll content of blade part, and can obtain the chlorophyllous distribution situation in whole blade face, precision of prediction is higher.
The method that high spectrum image of the present invention and independent component analysis plant leaf surface chlorophyll distribute is carried out according to subordinate's step: the calculating that high spectrum image pre-service, independent component analysis and selection, plant leaf surface chlorophyll distribute.
Wherein said high spectrum image pre-service comprises that high spectrum image is demarcated and spectrum extracts.
Wherein said independent component analysis and selection comprise: utilize isolated component method analysis meter to calculate isolated component, select best isolated component according to the regretional analysis result then.
The calculating that wherein said plant leaf surface chlorophyll distributes refers to utilize the best isolated component and the model of selection, calculates the chlorophyll content value of blade face each point, forms the chlorophyll distribution plan; The computing method that described plant leaf surface chlorophyll distributes comprise the steps:
(1) at first original high spectrum image I is demarcated with spectrum and extract.Under the system condition identical with sample collecting, scanning standard white correction plate obtains complete white uncalibrated image W, and close camera shutter and carry out image acquisition and obtain black full uncalibrated image B, according to formula:
After finishing demarcation, obtain image R.Ignore image space information, high spectrum image R can be expressed as a two-dimensional matrix X={x
1, x
2..., x
λ, wherein xi (i=1 ..., λ) be vector with m element, represented all pixels under i the wavelength (m 's) absorption value.The spectrum of a picked at random n pixel among the X is formed two-dimensional matrix i*n * λ, and wherein λ represents spectral range.
(2) above-mentioned two-dimensional matrix is carried out independent component analysis as observing matrix, by preestablishing the isolated component number, output isolated component S={s
1, s
2..., s
k.
(3) measure the chlorophyll content of one group of blade and the curve of spectrum of corresponding high spectrum image thereof, with isolated component S
i(i=1 ..., k) matrix multiple of forming with the curve of spectrum is one by one set up regression model M with chlorophyll content again, selects the highest isolated component of its related coefficient to be designated as S
m
(4) with the isolated component S of above-mentioned selection
m, the substitution formula
C
im′＝S
m·X′
Wherein, X represents high-spectrum sheet data (m * λ), S
mFor isolated component (1 * λ), the C that obtains
ImFor isolated component figure (m * 1), with C
ImCalculate chlorophyll concentration among each element substitution regression model M, at last data conversion is returned the picture signal of two dimension, just obtained the chlorophyll distribution plan, at last image is strengthened with pseudo-colours, improve the expressive force of chlorophyll distributed intelligence.
Beneficial effect of the present invention: the present invention is under the prerequisite of not damaging the blade face, the distribution plan of the chlorophyll content that obtains, not only can embody the chlorophyll content of blade part, and can acquire the chlorophyllous distribution situation in whole blade face, for the nutrition condition intelligent decision of plant provides foundation.
Description of drawings
Fig. 1 blade high spectrum image block data structure figure wherein;
The process flow diagram of Fig. 2 blade face chlorophyll forecast of distribution;
The process flow diagram that Fig. 3 isolated component is selected;
The pcolor that the blade face chlorophyll that Fig. 4 calculates distributes.
Embodiment
Below in conjunction with accompanying drawing the present invention is explained in further detail.
Fig. 1 is the structural drawing of blade high spectrum image data block.Any one pixel for image all has λ
1..., λ
nAbsorption value under the wavelength is the curve of spectrum of the some pixels of high spectrum image as Fig. 1 lower left corner; Any one wavelength X for image
iAll having the complete image of a back blades under this wavelength, is leaf image under a certain wavelength of high spectrum image as Fig. 1 lower right corner.
Gather n high spectrum image data as shown in Figure 1, carry out blade face chlorophyll forecast of distribution according to process flow diagram shown in Figure 2.All blade high spectrum images (Fig. 1) extract spectral signal through demarcating, and spectral signal is carried out independent component analysis.The isolated component S of the best in several isolated components that selection calculates
m, multiplying each other with the high spectrum image signal matrix, the data substitution model that obtains can calculate the chlorophyllous distribution plan in blade face.Utilize pseudo-colours to strengthen image at last, improve the expressive force of information.
Wherein, the method for isolated component selection as shown in Figure 3.From the raw data of gathering, separate one group of data in advance, measure the curve of spectrum X of its chlorophyll content C and corresponding high spectrum image thereof
CWith k isolated component successively with X
CMultiply each other, the result who obtains sets up linear regression model (LRM) with corresponding chlorophyll content C again, calculates coefficient R, until R＞0.75, and output S at this moment
mAs best isolated component and model M thereof.
The pcolor that the page chlorophyll that utilizes the present invention to calculate distributes, as shown in Figure 4.Though the vein chlorophyll content is less as seen from the figure, near the mesophyll chlorophyll content the vein is very high, is about about 2.0mg/g, can well distinguish vein; The chlorophyllous distribution uniform of mesophyll, chlorophyll content is about 1.5mg/g; Blade edge purple part is for because of the withered partial blade of nutritional deficiency among Fig. 4, and chlorophyll content also can significantly distinguish near 0mg/g.
Claims (2)
1. the method for high spectrum image and independent component analysis plant leaf surface chlorophyll distribution is carried out according to subordinate's step: the calculating that high spectrum image pre-service, independent component analysis and selection, plant leaf surface chlorophyll distribute; It is characterized in that described high spectrum image pre-service comprises that high spectrum image is demarcated and spectrum extracts; Described independent component analysis and selection comprise: utilize isolated component method analysis meter to calculate isolated component, select best isolated component according to the regretional analysis result then; The calculating that described plant leaf surface chlorophyll distributes refers to utilize the best isolated component and the model of selection, calculates the chlorophyll content value of blade face each point, forms the chlorophyll distribution plan.
2. the method that high spectrum image according to claim 1 and independent component analysis plant leaf surface chlorophyll distribute is characterized in that the computing method that described plant leaf surface chlorophyll distributes comprise the steps:
(1) at first original high spectrum image I is demarcated with spectrum and extract, under the system condition identical with sample collecting, scanning standard white correction plate obtains complete white uncalibrated image W, and close camera shutter and carry out image acquisition and obtain black full uncalibrated image B, according to formula:
After finishing demarcation, obtain image R; Ignore image space information, high spectrum image R can be expressed as a two-dimensional matrix X={x
1, x
2..., x
λ, wherein xi (i=1 ..., λ) be vector with m element, represented all pixels under i the wavelength (m 's) absorption value.The spectrum of a picked at random n pixel among the X is formed two-dimensional matrix i*n * λ, and wherein λ represents spectral range;
(2) above-mentioned two-dimensional matrix is carried out independent component analysis as observing matrix, by preestablishing the isolated component number, output isolated component S={s
1, s
2..., s
k;
(3) measure the chlorophyll content of one group of blade and the curve of spectrum of corresponding high spectrum image thereof, with isolated component S
i(i=1 ..., k) matrix multiple of forming with the curve of spectrum is one by one set up regression model M with chlorophyll content again, selects the highest isolated component of its related coefficient to be designated as S
m
(4) with the isolated component S of above-mentioned selection
m, the substitution formula
C
im′＝S
m·X′
Wherein, X represents high-spectrum sheet data (m * λ), S
mFor isolated component (1 * λ), the C that obtains
ImFor isolated component figure (m * 1), with C
ImCalculate chlorophyll concentration among each element substitution regression model M, at last data conversion is returned the picture signal of two dimension, just obtained the chlorophyll distribution plan, at last image is strengthened with pseudo-colours, improve the expressive force of chlorophyll distributed intelligence.
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