CN102331402A - Chemical gas detection and identification method by hyperspectral imaging - Google Patents

Chemical gas detection and identification method by hyperspectral imaging Download PDF

Info

Publication number
CN102331402A
CN102331402A CN201110146379A CN201110146379A CN102331402A CN 102331402 A CN102331402 A CN 102331402A CN 201110146379 A CN201110146379 A CN 201110146379A CN 201110146379 A CN201110146379 A CN 201110146379A CN 102331402 A CN102331402 A CN 102331402A
Authority
CN
China
Prior art keywords
chemical gas
pixel
execution
gas
sigma
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201110146379A
Other languages
Chinese (zh)
Other versions
CN102331402B (en
Inventor
谷延锋
王师哲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin University of technology high tech Development Corporation
Original Assignee
Harbin Institute of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Harbin Institute of Technology filed Critical Harbin Institute of Technology
Priority to CN 201110146379 priority Critical patent/CN102331402B/en
Publication of CN102331402A publication Critical patent/CN102331402A/en
Application granted granted Critical
Publication of CN102331402B publication Critical patent/CN102331402B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

The invention discloses a chemical gas detection and identification method by hyperspectral imaging and relates to the chemical gas detection and identification method. By the chemical gas detection and identification method, the technical problems that on-site sampling is required and the detection speed is low in the conventional chemical gas detection and identification method based on a chemical method can be solved. The chemical gas detection and identification method comprises the following steps of: shooting a spectral image of a detected place when any chemical gas does not exist in the detected place so as to acquire a pixel vector of a background; acquiring a spectral vector of a detected chemical gas from a chemical gas spectrum library; shooting another spectral image of the detected place and filtering the second spectral image by using a filter; sequencing output values of the filter from large to small; setting a threshold of the chemical gas; inputting the output values of the filter and the threshold of the chemical gas into a judger; recording the output values, greater than the threshold, of the filter so as to acquire a chemical gas-containing pixel set; and judging pixels containing the chemical gas by using a minimum markov distance method so as to identify the type of the gas. The chemical gas detection and identification method can be used in the fields of detection for pollution gas emission of chemical factories and environment monitoring.

Description

A kind of high light spectrum image-forming chemical gas detects recognition methods
Technical field
The invention belongs to chemical gas and detect recognition methods.
Background technology
High light spectrum image-forming is a process of obtaining the image information of high spectral resolution at the spectral band of electromagnetic spectrum.High spectrum image has comprised spatial information and the spectral information in the observation scene simultaneously, has the characteristic of " collection of illustrative plates unification ".Each pixel in the image all is a high dimension vector, and each dimension of vector is illustrated in a spectral band.Because the high spectrum image advantage that has the spectral resolution height, contain much information, can improve in the target detection process ability of target being carried out qualitative and quantitative analysis greatly, aspect civilian and military field many, embodied huge using value.The chemical gas incident of leakage happens occasionally all over the world; Existing based on the method for chemical method to the detection and Identification of chemical gas, all to arrive leak scene sampling, staff's health is damaged; And detection speed is slow, is unfavorable for the timely processing to accident.
Summary of the invention
The present invention will solve existingly need arrive on-site sampling and the slow technical matters of detection speed based on chemical method to the method for the detection and Identification of chemical gas, and provides a kind of high light spectrum image-forming chemical gas to detect recognition methods.
A kind of high light spectrum image-forming chemical gas of the present invention detects recognition methods to carry out according to the following steps:
Step 1: in area to be detected during no chemical gas; Using the infrared pick-up device to adopt wavelength is at least three images that the different-wavebands shooting has K pixel in 8 μ m~13 μ m; Each wave band is taken an image, is obtained K pixel vectors x of background by the pixel of the correspondence of these images k, k=1 wherein, 2,3 ..., K; K is the number of pixels of entire image;
Step 2: use
Figure BDA0000065648150000011
Calculate the pixel vectors x of background kThe maximum likelihood estimated value of average Use again
Figure BDA0000065648150000013
Calculate the pixel vectors x of background kThe maximum likelihood estimated matrix of variance
Figure BDA0000065648150000014
, wherein
Figure BDA0000065648150000015
Be pixel vectors x kTransposed vector;
Step 3: the target chemical gas for N kind needs detect according to the data in the chemical gas library of spectra, obtains chemical gas spectrum vector s in the gaseous spectrum storehouse i, i=1 wherein, 2,3 ..., N;
Step 4: in area to be detected; Using the infrared pick-up device to adopt wavelength is at least three images that the different-wavebands shooting has K pixel in 8 μ m~13 μ m; Each wave band is taken an image, is obtained K the pixel vectors z in area to be detected by the pixel of the correspondence of these images j, j=1 wherein, 2,3 ..., K;
Step 5: shilling i=1;
Step 6: utilize y i , j = s i T Σ ^ b - 1 ( z j - μ ^ b ) s i T Σ ^ b - 1 s i K the pixel vectors z that step 4 is obtained jThe output valve y of calculating filter I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kAnd pressing series arrangement from big to small, the maximum likelihood estimated value E [Y] of the average of [α K] individual output valve and the maximum likelihood estimated value Var [Y] of variance are designated as u with [α K] individual output valve simultaneously before calculating again iWherein
Figure BDA0000065648150000022
Be matrix
Figure BDA0000065648150000023
Inverse matrix; α=5%~10%;
Step 7: utilize E [ Y ] = σ 1 - ξ With Var [ Y ] = σ 2 ( 1 - ξ ) 2 ( 1 - 2 ξ ) Calculate parameter σ and ξ; Be used further to detect the thresholding of i kind chemical gas η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] ; P wherein FABe false-alarm probability, P FA=10 -3~10 -5
Step 8: the output valve y of each wave filter that step 6 is calculated I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kThe thresholding of the i kind chemical gas that calculates with step 7 η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] Together import decision device and compare, judge whether output valve, if not, then make i add 1, execution in step six greater than the wave filter of thresholding; If, execution in step nine;
Step 9: record is greater than the corresponding pixel vectors z of the output valve of thresholding iAnd corresponding i kind chemical gas;
Step 10: judge then whether i equals N, if not, make i add 1, execution in step six; If then execution in step 11;
Step 11: that writes down in the step 8 uses z greater than the corresponding pixel vectors of the output valve of thresholding cExpression, c=1,2 ..., C; The corresponding spectrum vector of chemical gas in the gaseous spectrum storehouse used s dExpression, d=1 wherein, 2,3 ..., D; Make c=1, d=1; Wherein C representes that D representes the maximal value of corresponding chemical gas kind greater than the maximal value of the number of the corresponding pixel vectors of the output valve of thresholding;
Step 12: calculate Δ c , d = ( z c - μ ^ b - a ^ d S d ) T Σ ^ b - 1 ( z c - μ ^ b - a ^ d s d ) Calculate horse formula distance, delta C, d, wherein, a ^ d = s d T Σ ^ b - 1 ( z c - μ ^ b ) s d T Σ ^ b - 1 s d ,
Figure BDA0000065648150000032
Be the maximum likelihood estimated value of the average of background,
Figure BDA0000065648150000033
The maximum likelihood estimated matrix of the variance of background
Figure BDA0000065648150000034
Inverse matrix,
Figure BDA0000065648150000035
The transposition of the spectrum vector of d kind chemical gas in the gaseous spectrum storehouse;
Step 13: judge whether d is 1, if make d add 1, execution in step 12; If not, execution in step 14 then;
Step 14: judge Δ C, d≤Δ C, d-1If,, record d gas; If not, execution in step 15;
Step 15: judge whether d equals D, if not, then make d add 1, return step 12; If, execution in step 16;
Step 10 six: c gas that monitors threat is judged into the chemical gas of last record and made c add 1;
Step 10 seven: judge whether c equals C, if not, make c add 1, execution in step 12; If then execution in step 18;
Step 10 eight: calculate the pairing volume coordinate of each pixel that detects chemical gas, accomplish the detection identification of chemical gas.
Because atmosphere is transparent relatively in LONG WAVE INFRARED zone (8-13 μ m), utilize the high spectrum image of this wave band to carry out remote detection and Identification to the chemical gas of leakage or discharge in violation of regulations.Gas detection with based on chemical method is compared, and utilizes the high light spectrum image-forming technology that gas is detected and has more real-time and more secure to personal safety.In long wave infrared region, the imaging model of chemical gas can be constructed as x=as+v, and wherein x is a pixel vectors in the high spectrum image, and s is the spectrum vector of chemical gas, and v is the background vector, and a is the coefficient relevant with thickness with the concentration of this gas.Therefore,, design a matched filter and evade this interference, and whether the output of wave filter can cooperate decision threshold to detect chemical gas to exist in order to detect the influence that the pixel that contains chemical gas just must be removed background clutter.But need making up a rational statistical model, this make the output of wave filter to meet; Theory according to Manolakis; The background clutter that no chemical gas covers is at high spectrum image that long wave infrared region became; Through behind the matched filter, its output valve meets broad sense Pareto and distributes, and obtains a CFAR decision threshold through the mode of setting false-alarm probability.The detection of chemical gas is to accomplish with relevant with it decision threshold through designing a matched filter.Mahalanobis distance utilizes the similarity that the statistical property of data can two samples of fine measurement, and therefore on the problem of chemical gas identification, the pixel that detected chemical gas in the image is existed is judged to the minimum chemical gas of mahalanobis distance with it.Find P the minimum value in the mahalanobis distance, pairing gaseous species promptly is the chemical gas that this location of pixels is revealed or discharged.The design concept synoptic diagram of the inventive method is as shown in Figure 1, and above various piece is integrated, and is exactly the system of automatic chemical gas detection and Identification.
High light spectrum image-forming chemical gas of the present invention detects the recognition methods area of monitoring chemical gaseous emission or leakage at a distance, has avoided arriving on-site sampling, and has worked by computer operation, and detection speed is fast.
The present invention can be used for detection and the environmental monitoring field to the discharging of chemical plant dusty gas.
Description of drawings
The design concept synoptic diagram of Fig. 1 the inventive method; Fig. 2 is the process flow diagram that high light spectrum image-forming chemical gas of the present invention detects recognition methods.
Embodiment
Embodiment one: a kind of high light spectrum image-forming chemical gas of this embodiment detects recognition methods to carry out according to the following steps:
Step 1: in area to be detected during no chemical gas; Using the infrared pick-up device to adopt wavelength is at least three images that the different-wavebands shooting has K pixel in 8 μ m~13 μ m; Each wave band is taken an image, is obtained K pixel vectors x of background by the pixel of the correspondence of these images k, k=1 wherein, 2,3 ..., K; K is the number of pixels of entire image;
Step 2: use
Figure BDA0000065648150000041
Calculate the pixel vectors x of background kThe maximum likelihood estimated value of average
Figure BDA0000065648150000042
Use again
Figure BDA0000065648150000043
Calculate the pixel vectors x of background kThe maximum likelihood estimated matrix of variance
Figure BDA0000065648150000044
Wherein
Figure BDA0000065648150000045
Be pixel vectors x kTransposed vector;
Step 3: the target chemical gas for N kind needs detect according to the data in the chemical gas library of spectra, obtains chemical gas spectrum vector s in the gaseous spectrum storehouse i, i=1 wherein, 2,3 ..., N;
Step 4: in area to be detected; Using the infrared pick-up device to adopt wavelength is at least three images that the different-wavebands shooting has K pixel in 8 μ m~13 μ m; Each wave band is taken an image, is obtained K the pixel vectors z in area to be detected by the pixel of the correspondence of these images j, j=1 wherein, 2,3 ..., K;
Step 5: shilling i=1;
Step 6: utilize y i , j = s i T Σ ^ b - 1 ( z j - μ ^ b ) s i T Σ ^ b - 1 s i K the pixel vectors z that step 4 is obtained jThe output valve y of calculating filter I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kAnd pressing series arrangement from big to small, the maximum likelihood estimated value E [Y] of the average of [α K] individual output valve and the maximum likelihood estimated value Var [Y] of variance are designated as u with [α K] individual output valve simultaneously before calculating again iWherein
Figure BDA0000065648150000051
Be matrix
Figure BDA0000065648150000052
Inverse matrix; α=5%~10%;
Step 7: utilize E [ Y ] = σ 1 - ξ With Var [ Y ] = σ 2 ( 1 - ξ ) 2 ( 1 - 2 ξ ) Calculate parameter σ and ξ; Be used further to detect the thresholding of i kind chemical gas η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] ; P wherein FABe false-alarm probability, P FA=10 -3~10 -5
Step 8: the output valve y of each wave filter that step 6 is calculated I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kThe thresholding of the i kind chemical gas that calculates with step 7 η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] Together import decision device and compare, judge whether output valve, if not, then make i add 1, execution in step six greater than the wave filter of thresholding; If, execution in step nine;
Step 9: record is greater than the corresponding pixel vectors z of the output valve of thresholding iAnd corresponding i kind chemical gas;
Step 10: judge then whether i equals N, if not, make i add 1, execution in step six; If then execution in step 11;
Step 11: that writes down in the step 8 uses z greater than the corresponding pixel vectors of the output valve of thresholding cExpression, c=1,2 ..., C; The corresponding spectrum vector of chemical gas in the gaseous spectrum storehouse used s dExpression, d=1 wherein, 2,3 ..., D; Make c=1, d=1; Wherein C representes that D representes the maximal value of corresponding chemical gas kind greater than the maximal value of the number of the corresponding pixel vectors of the output valve of thresholding;
Step 12: calculate Δ c , d = ( z c - μ ^ b - a ^ d s d ) T Σ ^ b - 1 ( z c - μ ^ b - a ^ d s d ) Calculate horse formula distance, delta C, d, wherein, a ^ d = s d T Σ ^ b - 1 ( z c - μ ^ b ) s d T Σ ^ b - 1 s d ,
Figure BDA0000065648150000059
Be the maximum likelihood estimated value of the average of background,
Figure BDA00000656481500000510
The maximum likelihood estimated matrix of the variance of background
Figure BDA00000656481500000511
Inverse matrix,
Figure BDA00000656481500000512
The transposition of the spectrum vector of d kind chemical gas in the gaseous spectrum storehouse;
Step 13: judge whether d is 1, if make d add 1, execution in step 12; If not, execution in step 14 then;
Step 14: judge Δ C, d≤Δ C, d-1If,, record d gas; If not, execution in step 15;
Step 15: judge whether d equals D, if not, then make d add 1, return step 12; If, execution in step 16;
Step 10 six: c gas that monitors threat is judged into the chemical gas of last record and made c add 1;
Step 10 seven: judge whether c equals C, if not, make c add 1, execution in step 12; If then execution in step 18;
Step 10 eight: calculate the pairing volume coordinate of each pixel that detects chemical gas, accomplish the detection identification of chemical gas.
[α K] expression in the step 5 of this embodiment rounds calculating with α K.
In this embodiment,, utilize the high spectrum image of this wave band to carry out remote detection and Identification to the chemical gas of leakage or discharge in violation of regulations because atmosphere is transparent relatively in LONG WAVE INFRARED zone (8-13 μ m).Gas detection with based on chemical method is compared, and utilizes the high light spectrum image-forming technology that gas is detected and has more real-time and more secure to personal safety.In long wave infrared region, the imaging model of chemical gas can be constructed as x=as+v, and wherein x is a pixel vectors in the high spectrum image, and s is the spectrum vector of chemical gas, and v is the background vector, and a is the coefficient relevant with thickness with the concentration of this gas.Therefore,, design a matched filter and evade this interference, and whether the output of wave filter can cooperate decision threshold to detect chemical gas to exist in order to detect the influence that the pixel that contains chemical gas just must be removed background clutter.But need making up a rational statistical model, this make the output of wave filter to meet; Theory according to Manolakis; The background clutter that no chemical gas covers is at high spectrum image that long wave infrared region became; Through behind the matched filter, its output valve meets broad sense Pareto and distributes, and obtains a CFAR decision threshold through the mode of setting false-alarm probability.The detection of chemical gas is to accomplish with relevant with it decision threshold through designing a matched filter.Mahalanobis distance utilizes the similarity that the statistical property of data can two samples of fine measurement, and therefore on the problem of chemical gas identification, the pixel that detected chemical gas in the image is existed is judged to the minimum chemical gas of mahalanobis distance with it.Find P the minimum value in the mahalanobis distance, pairing gaseous species promptly is the chemical gas that this location of pixels is revealed or discharged.This embodiment integrates above various piece, is exactly the system of automatic chemical gas detection and Identification.The monitoring chemical gaseous emission at a distance of this embodiment or the area of leakage, aspects such as the detection of dusty gas discharging and environmental monitoring all have very high practicality in the chemical plant.
Embodiment two: what this embodiment and embodiment one were different is: calculating each method that detects the pairing volume coordinate of pixel of chemical gas in the step 10 eight is: according to the spatial resolution and the camera site of high spectrum sensor, calculate the pairing volume coordinate of each pixel that detects chemical gas: u = u 0 + θ · e v = v 0 + θ · f ′ , (u 0, v 0) be the volume coordinate of a known pixels on the image, be reference point with it, (u v) is the corresponding volume coordinate of pixel, and (e is the horizontal vertical number of pixels coordinate that the pixel that detects chemical gas deviates from benchmark pixel f), and θ is the spatial resolution of sensor.Other is identical with embodiment one.
Embodiment three: the method for a kind of high light spectrum image-forming chemical gas detection and Identification of this embodiment is carried out according to the following steps:
Step 1: in area to be detected during no chemical gas; Using the infrared pick-up device to adopt wavelength is 10 images that the different-wavebands shooting has 10000 pixels in 8 μ m~13 μ m; Each wave band is taken an image; Obtain 10 images altogether, obtain 10000 pixel vectors x of background by the pixel of the correspondence of these 10 images k, k=1 wherein, 2,3 ..., 10000;
Step 2: use
Figure BDA0000065648150000071
Calculate the maximum likelihood estimated value of the average of background
Figure BDA0000065648150000072
Use again
Figure BDA0000065648150000073
Calculate the maximum likelihood estimated matrix of the variance of background
Figure BDA0000065648150000074
Wherein
Figure BDA0000065648150000075
Be pixel vectors x kTransposed vector;
Step 3: the target chemical gas for 10 kinds of needs detect according to the data in the chemical gas library of spectra, obtains i kind chemical gas spectrum vector s in the gaseous spectrum storehouse i, i=1 wherein, 2,3 ..., 10;
Step 4: in area to be detected; Using the infrared pick-up device to adopt wavelength is the image that the 10 different-wavebands shooting in 8 μ m~13 μ m has 10000 pixels; Each wave band is taken an image; Obtain 10 images altogether, obtain 10000 pixel vectors z in area to be detected by the pixel of the correspondence of these 10 images j, j=1 wherein, 2,3 ..., 10000;
Step 5: shilling i=1;
Step 6: utilize y i , j = s i T Σ ^ b - 1 ( z j - μ ^ b ) s i T Σ ^ b - 1 s i 10000 pixel vectors z that step 4 is obtained jThe output valve y of calculating filter I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, 10000And, calculate maximum likelihood estimated value E [Y] and the maximum likelihood estimated value Var [Y] of variance of the average of preceding 500 output valves again by from big to small series arrangement, simultaneously the 500th output valve is designated as u iWherein
Figure BDA0000065648150000077
Be matrix
Figure BDA0000065648150000078
Inverse matrix;
Step 7: utilize E [ Y ] = σ 1 - ξ With Var [ Y ] = σ 2 ( 1 - ξ ) 2 ( 1 - 2 ξ ) Calculate parameter σ and ξ; Be used further to detect the thresholding of i kind chemical gas η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] ; P wherein FABe false-alarm probability, P FA=10 -4
Step 8: the output valve y of each wave filter that step 6 is calculated I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kThe thresholding of the i kind chemical gas that calculates with step 7 η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] Together import decision device and compare, judge whether output valve, if not, then make i add 1, execution in step six greater than the wave filter of thresholding; If, execution in step nine;
Step 9: record is greater than the corresponding pixel vectors z of the output valve of thresholding iAnd corresponding i kind chemical gas;
Step 10: judge then whether i equals N, if not, make i add 1, execution in step six; If then execution in step 11;
Step 11: that writes down in the step 8 uses z greater than the corresponding pixel vectors of the output valve of thresholding cExpression, c=1,2 ..., C; The corresponding spectrum vector of chemical gas in the gaseous spectrum storehouse used s dExpression, d=1 wherein, 2,3 ..., D; Make c=1, d=1; Wherein C representes that D representes the maximal value of corresponding chemical gas kind greater than the maximal value of the number of the corresponding pixel vectors of the output valve of thresholding;
Step 12: calculate Δ c . d = ( z c - μ ^ b - a ^ d s d ) T Σ ^ b - 1 ( z c - μ ^ b - a ^ d s d ) Calculate horse formula distance, delta C, d, wherein, a ^ d = s d T Σ ^ b - 1 ( z c - μ ^ b ) s d T Σ ^ b - 1 s d , Be the maximum likelihood estimated value of the average of background,
Figure BDA0000065648150000086
The maximum likelihood estimated matrix of the variance of background Inverse matrix, The transposition of the spectrum vector of d kind chemical gas in the gaseous spectrum storehouse;
Step 13: judge whether d is 1, if make d add 1, execution in step 12; If not, execution in step 14 then;
Step 14: judge Δ C, d≤Δ C, d-1If,, record d gas; If not, execution in step 15;
Step 15: judge whether d equals D, if not, then make d add 1, return step 12; If, execution in step 16;
Step 10 six: c gas that monitors threat is judged into the chemical gas of last record and made c add 1;
Step 10 seven: judge whether c equals C, if not, make c add 1, execution in step 12; If then execution in step 18;
Step 10 eight:, calculate the pairing volume coordinate of each pixel that detects chemical gas according to the spatial resolution and the camera site of high spectrum sensor: u = u 0 + θ · e v = v 0 + θ · f ′ , (u 0, v 0) be the volume coordinate of a known pixels on the image, be reference point with it, (u; V) be the corresponding volume coordinate of pixel, (e f) is the horizontal vertical number of pixels coordinate that the pixel that detects chemical gas deviates from benchmark pixel; θ is the spatial resolution of sensor, accomplishes the detection identification of chemical gas.
Wavelength in this embodiment in step 1 and the step 4 is that 10 different-wavebands in 8 μ m~13 μ m are got like this:
8.0μm~8.25μm 8.26μm~8.50μm 8.51μm~8.75μm 8.51μm~8.75μm 8.76μm~9.00μm
9.05μm~9.25μm 9.26μm~9.50μm 9.51μm~9.75μm 9.76μm~10.00μm 10.01μm~10.25μm
The dimension of pixel vectors is identical with the number of the wave band of being got in the high spectrum image, the pixel vectors x of background in the step 1 of this embodiment kDimension be 10 the dimension, the pixel vectors z in the step 4 jDimension also be 10 the dimension.
In this embodiment,, utilize the high spectrum image of this wave band to carry out remote detection and Identification to the chemical gas of leakage or discharge in violation of regulations because atmosphere is transparent relatively in LONG WAVE INFRARED zone (8-13 μ m).Gas detection with based on chemical method is compared, and utilizes the high light spectrum image-forming technology that gas is detected and has more real-time and more secure to personal safety.In long wave infrared region, the imaging model of chemical gas can be constructed as x=as+v, and wherein x is a pixel vectors in the high spectrum image, and s is the spectrum vector of chemical gas, and v is the background vector, and a is the coefficient relevant with thickness with the concentration of this gas.Therefore,, design a matched filter and evade this interference, and whether the output of wave filter can cooperate decision threshold to detect chemical gas to exist in order to detect the influence that the pixel that contains chemical gas just must be removed background clutter.But need making up a rational statistical model, this make the output of wave filter to meet; Theory according to Manolakis; The background clutter that no chemical gas covers is at high spectrum image that long wave infrared region became; Through behind the matched filter, its output valve meets broad sense Pareto and distributes, and obtains a CFAR decision threshold through the mode of setting false-alarm probability.The detection of chemical gas is to accomplish with relevant with it decision threshold through designing a matched filter.Mahalanobis distance utilizes the similarity that the statistical property of data can two samples of fine measurement, and therefore on the problem of chemical gas identification, the pixel that detected chemical gas in the image is existed is judged to the minimum chemical gas of mahalanobis distance with it.Find P the minimum value in the mahalanobis distance, pairing gaseous species promptly is the chemical gas that this location of pixels is revealed or discharged.This embodiment integrates above various piece, is exactly the system of automatic chemical gas detection and Identification.The monitoring chemical gaseous emission at a distance of this embodiment or the area of leakage, aspects such as the detection of dusty gas discharging and environmental monitoring all have very high practicality in the chemical plant.

Claims (2)

1. a high light spectrum image-forming chemical gas detects recognition methods, it is characterized in that the high light spectrum image-forming chemical gas detects recognition methods and carries out according to the following steps:
Step 1: in area to be detected during no chemical gas; Using the infrared pick-up device to adopt wavelength is at least three images that the different-wavebands shooting has K pixel in 8 μ m~13 μ m; Each wave band is taken an image, is obtained K pixel vectors x of background by the pixel of the correspondence of these images k, k=1 wherein, 2,3 ..., K; K representes the number of pixels of entire image;
Step 2: use
Figure FDA0000065648140000011
Calculate the pixel vectors x of background kThe maximum likelihood estimated value of average
Figure FDA0000065648140000012
Use again Calculate the pixel vectors x of background kThe maximum likelihood estimated matrix of variance
Figure FDA0000065648140000014
Wherein
Figure FDA0000065648140000015
Be pixel vectors x kTransposed vector;
Step 3: the target chemical gas for N kind needs detect according to the data in the chemical gas library of spectra, obtains chemical gas spectrum vector s in the gaseous spectrum storehouse i, i=1 wherein, 2,3 ..., N;
Step 4: in area to be detected; Using the infrared pick-up device to adopt wavelength is at least three images that the different-wavebands shooting has K pixel in 8 μ m~13 μ m; Each wave band is taken an image, is obtained K the pixel vectors z in area to be detected by the pixel of the correspondence of these images j, j=1 wherein, 2,3 ..., K;
Step 5: shilling i=1;
Step 6: utilize y i , j = s i T Σ ^ b - 1 ( z j - μ ^ b ) s i T Σ ^ b - 1 s i K the pixel vectors z that step 4 is obtained jThe output valve y of calculating filter I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kAnd pressing series arrangement from big to small, the maximum likelihood estimated value E [Y] of the average of [α K] individual output valve and the maximum likelihood estimated value Var [Y] of variance are designated as u with [α K] individual output valve simultaneously before calculating again iWherein
Figure FDA0000065648140000017
Be matrix
Figure FDA0000065648140000018
Inverse matrix; α=5%~10%;
Step 7: utilize E [ Y ] = σ 1 - ξ With Var [ Y ] = σ 2 ( 1 - ξ ) 2 ( 1 - 2 ξ ) Calculate parameter σ and ξ; Be used further to detect the thresholding of i kind chemical gas η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] ; P wherein FABe false-alarm probability, P FA=10 -3~10 -5Step 8: the output valve y of each wave filter that step 6 is calculated I, 1, y I, 2, y I, 3... Y I, j-1, y I, j, y I, j+1..., y I, kThe thresholding of the i kind chemical gas that calculates with step 7 η i = u i + σ ξ [ ( α P FA ) 2 - 1 ] Together import decision device and compare, judge whether output valve, if not, then make i add 1, execution in step six greater than the wave filter of thresholding; If, execution in step nine;
Step 9: record is greater than the corresponding pixel vectors z of the output valve of thresholding iAnd corresponding i kind chemical gas;
Step 10: judge then whether i equals N, if not, make i add 1, execution in step six; If then execution in step 11;
Step 11: that writes down in the step 8 uses z greater than the corresponding pixel vectors of the output valve of thresholding cExpression, c=1,2 ..., C; The corresponding spectrum vector of chemical gas in the gaseous spectrum storehouse used s dExpression, d=1 wherein, 2,3 ..., D; Make c=1, d=1; Wherein C representes that D representes the maximal value of corresponding chemical gas kind greater than the maximal value of the number of the corresponding pixel vectors of the output valve of thresholding;
Step 12: calculate Δ c , d = ( Z c - μ ^ b - a ^ d s d ) T Σ ^ b - 1 ( Z c - μ ^ b - a ^ d s d ) Calculate horse formula distance, delta C, d, wherein, a ^ d = s d T Σ ^ b - 1 ( z c - μ ^ b ) s d T Σ ^ b - 1 s d ,
Figure FDA0000065648140000024
Be the maximum likelihood estimated value of the average of background,
Figure FDA0000065648140000025
The maximum likelihood estimated matrix of the variance of background
Figure FDA0000065648140000026
Inverse matrix,
Figure FDA0000065648140000027
The transposition of the spectrum vector of d kind chemical gas in the gaseous spectrum storehouse;
Step 13: judge whether d is 1, if make d add 1, execution in step 12; If not, execution in step 14 then;
Step 14: judge Δ C, d≤Δ C, d-1If,, record d gas; If not, execution in step 15;
Step 15: judge whether d equals D, if not, then make d add 1, execution in step 12; If, execution in step 16;
Step 10 six: c gas that monitors threat is judged into the chemical gas of last record and made c add 1;
Step 10 seven: judge whether c equals C, if not, make c add 1, execution in step 12; If then execution in step 18;
Step 10 eight: calculate the pairing volume coordinate of each pixel that detects chemical gas, accomplish the detection identification of chemical gas.
2. a kind of high light spectrum image-forming chemical gas according to claim 1 detects recognition methods; It is characterized in that calculating in the step 10 eight each method that detects the pairing volume coordinate of pixel of chemical gas is: according to the spatial resolution and the camera site of high spectrum sensor, calculate the pairing volume coordinate of each pixel that detects chemical gas: u = u 0 + θ · e v = v 0 + θ · f ′ , (u 0, v 0) be the volume coordinate of a known pixels on the image, be reference point with it, (u v) is the corresponding volume coordinate of pixel, and (e is the horizontal vertical number of pixels coordinate that the pixel that detects chemical gas deviates from benchmark pixel f), and θ is the spatial resolution of sensor.
CN 201110146379 2011-06-01 2011-06-01 Chemical gas detection and identification method by hyperspectral imaging Active CN102331402B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN 201110146379 CN102331402B (en) 2011-06-01 2011-06-01 Chemical gas detection and identification method by hyperspectral imaging

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN 201110146379 CN102331402B (en) 2011-06-01 2011-06-01 Chemical gas detection and identification method by hyperspectral imaging

Publications (2)

Publication Number Publication Date
CN102331402A true CN102331402A (en) 2012-01-25
CN102331402B CN102331402B (en) 2013-05-01

Family

ID=45483253

Family Applications (1)

Application Number Title Priority Date Filing Date
CN 201110146379 Active CN102331402B (en) 2011-06-01 2011-06-01 Chemical gas detection and identification method by hyperspectral imaging

Country Status (1)

Country Link
CN (1) CN102331402B (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106018316A (en) * 2016-05-23 2016-10-12 湖北久之洋红外***股份有限公司 Gas detection method based on hyperspectral infrared image processing
CN107451590A (en) * 2017-07-19 2017-12-08 哈尔滨工程大学 Gas detection identification and concentration method for expressing based on EO-1 hyperion infrared image
CN110192098A (en) * 2016-11-14 2019-08-30 奥普加尔光电工业有限公司 System and method for quantifying gas leakage
CN110673628A (en) * 2019-09-20 2020-01-10 北京航空航天大学 Inspection method for oil-gas pipeline of composite wing unmanned aerial vehicle
CN111862541A (en) * 2020-06-28 2020-10-30 安徽旭帆信息科技有限公司 Poisonous and harmful gas monitoring system based on infrared imaging technology
CN111965116A (en) * 2020-07-21 2020-11-20 天津大学 Hyperspectrum-based airport gas detection system and method
CN111965115A (en) * 2020-07-21 2020-11-20 天津大学 Ship tail gas measurement system and method based on hyperspectrum

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101059425A (en) * 2007-05-29 2007-10-24 浙江大学 Method and device for identifying different variety green tea based on multiple spectrum image texture analysis
CN101144861A (en) * 2007-11-02 2008-03-19 北京航空航天大学 High spectrum sub-pixel target detection method and device
CN100507603C (en) * 2007-10-16 2009-07-01 哈尔滨工业大学 Hyperspectral image abnormal point detection method based on selective kernel principal component analysis
WO2010056254A1 (en) * 2008-11-17 2010-05-20 Raytheon Company Hyperspectral image dimension reduction system and method
CN101832926A (en) * 2010-03-19 2010-09-15 江南大学 Method for performing apple powder materialization non-destructive inspection by using hyper-spectral image technique

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101059425A (en) * 2007-05-29 2007-10-24 浙江大学 Method and device for identifying different variety green tea based on multiple spectrum image texture analysis
CN100507603C (en) * 2007-10-16 2009-07-01 哈尔滨工业大学 Hyperspectral image abnormal point detection method based on selective kernel principal component analysis
CN101144861A (en) * 2007-11-02 2008-03-19 北京航空航天大学 High spectrum sub-pixel target detection method and device
WO2010056254A1 (en) * 2008-11-17 2010-05-20 Raytheon Company Hyperspectral image dimension reduction system and method
CN101832926A (en) * 2010-03-19 2010-09-15 江南大学 Method for performing apple powder materialization non-destructive inspection by using hyper-spectral image technique

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
贺霖等: "高光谱图像目标检测研究进展", 《电子学报》, vol. 37, no. 9, 30 September 2009 (2009-09-30), pages 2016 - 2024 *

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106018316A (en) * 2016-05-23 2016-10-12 湖北久之洋红外***股份有限公司 Gas detection method based on hyperspectral infrared image processing
CN106018316B (en) * 2016-05-23 2018-11-09 湖北久之洋红外***股份有限公司 A kind of gas detection method based on EO-1 hyperion infrared image processing
CN110192098A (en) * 2016-11-14 2019-08-30 奥普加尔光电工业有限公司 System and method for quantifying gas leakage
CN107451590A (en) * 2017-07-19 2017-12-08 哈尔滨工程大学 Gas detection identification and concentration method for expressing based on EO-1 hyperion infrared image
CN107451590B (en) * 2017-07-19 2020-09-25 哈尔滨工程大学 Gas detection identification and concentration representation method based on hyperspectral infrared image
CN110673628A (en) * 2019-09-20 2020-01-10 北京航空航天大学 Inspection method for oil-gas pipeline of composite wing unmanned aerial vehicle
CN110673628B (en) * 2019-09-20 2020-09-29 北京航空航天大学 Inspection method for oil-gas pipeline of composite wing unmanned aerial vehicle
CN111862541A (en) * 2020-06-28 2020-10-30 安徽旭帆信息科技有限公司 Poisonous and harmful gas monitoring system based on infrared imaging technology
CN111965116A (en) * 2020-07-21 2020-11-20 天津大学 Hyperspectrum-based airport gas detection system and method
CN111965115A (en) * 2020-07-21 2020-11-20 天津大学 Ship tail gas measurement system and method based on hyperspectrum

Also Published As

Publication number Publication date
CN102331402B (en) 2013-05-01

Similar Documents

Publication Publication Date Title
CN102331402B (en) Chemical gas detection and identification method by hyperspectral imaging
CN100507603C (en) Hyperspectral image abnormal point detection method based on selective kernel principal component analysis
CN108414455B (en) Crop hail disaster remote sensing monitoring method for agricultural insurance claim settlement
CN111709329B (en) Unmanned aerial vehicle measurement and control signal high-speed recognition method based on deep learning
CN102903114A (en) Hyperspectral remotely-sensed data dimensionality reduction method based on improved hierarchical clustering
CN103426167A (en) Hyperspectral real-time detection method based on recursive analysis
CN116499938B (en) Intelligent monitoring method for aerosol suspended matters in professional workplace
CN111444774A (en) Forest resource monitoring method based on unmanned aerial vehicle aerial survey technology
CN106096505A (en) The SAR target identification method of expression is worked in coordination with based on Analysis On Multi-scale Features
CN113008806A (en) Agricultural product production area heavy metal spatial distribution determination method
CN115457001A (en) Photovoltaic panel foreign matter detection method, system, device and medium based on VGG network
CN103870807A (en) High spectrum mixed nuclear RX anomaly detection method
CN117649123A (en) Wisdom garden management system
CN115830516B (en) Computer neural network image processing method for battery deflagration detection
Yang et al. Research on farmland crop classification based on UAV multispectral remote sensing images
CN116704241A (en) Full-channel 3D convolutional neural network hyperspectral remote sensing image classification method
CN106018316A (en) Gas detection method based on hyperspectral infrared image processing
CN115826477A (en) Water area monitoring system and method based on data visualization
CN114629047A (en) Method, device and equipment for detecting slippage of damper
CN115482489A (en) Improved YOLOv 3-based power distribution room pedestrian detection and trajectory tracking method and system
Koltunov et al. GOES early fire detection (GOES-EFD) system prototype
Roy Hybrid algorithm for hyperspectral target detection
CN117094995B (en) Reaction kettle gas leakage detection method, device, medium and equipment
Pollard Development and Evaluation of Machine Learning Models for Fugitive Methane Detection and Intensity Prediction
CN117975372B (en) Construction site safety detection system and method based on YOLOv and transducer encoder

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20200327

Address after: 150001 No. 118 West straight street, Nangang District, Heilongjiang, Harbin

Patentee after: Harbin University of technology high tech Development Corporation

Address before: 150001 Harbin, Nangang, West District, large straight street, No. 92

Patentee before: HARBIN INSTITUTE OF TECHNOLOGY