CN105160631A - Method for calculating radiation correction coefficient - Google Patents

Method for calculating radiation correction coefficient Download PDF

Info

Publication number
CN105160631A
CN105160631A CN201510381649.7A CN201510381649A CN105160631A CN 105160631 A CN105160631 A CN 105160631A CN 201510381649 A CN201510381649 A CN 201510381649A CN 105160631 A CN105160631 A CN 105160631A
Authority
CN
China
Prior art keywords
value
pixel
wave band
correction coefficient
ref
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
CN201510381649.7A
Other languages
Chinese (zh)
Other versions
CN105160631B (en
Inventor
马丕明
陈星夕
马艳华
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.)
Shandong University
Original Assignee
Shandong University
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 Shandong University filed Critical Shandong University
Priority to CN201510381649.7A priority Critical patent/CN105160631B/en
Publication of CN105160631A publication Critical patent/CN105160631A/en
Application granted granted Critical
Publication of CN105160631B publication Critical patent/CN105160631B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Image Processing (AREA)
  • Photometry And Measurement Of Optical Pulse Characteristics (AREA)

Abstract

The invention discloses a method for calculating a radiation correction coefficient, and belongs to the technical field of infrared image processing. The method comprises the steps: firstly finding a pixel, matched with a ground object scaling point, from an original image, and recording the position of the pixel; secondly carrying out the radiation correction of the original image through employing a lab radiation correction coefficient, and then carrying out the atmospheric correction of the image after radiation correction; thirdly enabling the ground object scaling point and the radiation brightness of the matched pixel of the processed image to form a data pair, and then carrying out the linear fitting of the data pairs of different ground objects, thereby obtaining the slope and intercept of a band; and finally carrying out the calculation of the slope and intercept of a corresponding point value in the lab radiation correction coefficient, thereby obtaining the new slope and intercept, i.e., the new radiation correction coefficient. The method can iron out the defect of an absolute lab radiation correction coefficient. When an image processed through the radiation correction coefficient is compared with an image processed through the absolute radiation correction coefficient, the image processed through the radiation correction coefficient is closer to the actual spectrum curve of the ground object. Meanwhile, the method can save the time in calculating the radiation correction coefficient.

Description

A kind of method asking radiant correction coefficient
Technical field
The present invention relates to a kind of method asking radiant correction coefficient in infrared technique, belong to infrared image processing technical field.
Background technology
The atural object radiation information that thermal infrared sensor obtains, except the interference being subject to atmospheric effect, also also exists a series of systematic error, as the change and detector error etc. of recording noise, reference temperature.In order to obtain accurate radiation information from sensing data, sensor by radiant correction, namely must set up quantitative relationship between output valve and the radiance value of incidence.Therefore, before acquisition of image data, need to demarcate the input value of sensor and integrating sphere spectral radiance value in laboratory, obtain linear relationship coefficient between the two, be absolute radiation correction coefficient.
When dealing with remote sensing images, carry out needing to provide radiant correction coefficient accurately in radiant correction process to original image, the data obtained so just can closer to the spectral charactersitics of targets.Paper " the radiation delivery characteristic of space optical remote sensor and bearing calibration " (the optical precision engineering that Ren Jianwei, Wan Zhi, Li Xiansheng, Ren Jianyue deliver, 2007,15 (2): 1188) what provide radiant correction coefficient in asks method: be the function that entrance pupil spoke illuminometer is shown as gradation of image by the target Equivalent that Taylor series represent under certain observation condition:
L＝A' 0+A′ 1*DN+A' 2*DN 2+A′ 3*DN 3+...+A' n*DN n
Wherein A' 0, A ' 1, A' 2... A' nbe radiant correction coefficient, once this calibration coefficient is determined, just can be finally inversed by the radiance L at camera entrance pupil place according to the digital output DN value of this funtcional relationship and camera, finally restore the radiance image of target.This radiant correction coefficient ask method more loaded down with trivial details, and not and actual spectral charactersitics of targets curve combine, therefore its accuracy is poor.
Summary of the invention
In order to overcome defect and the deficiency of prior art existence, the present invention proposes a kind of method asking radiant correction coefficient, the method, based on Absolute Radiometric Calibration Coefficients, in conjunction with actual atural object radiance value, tries to achieve the method for the radiant correction coefficient after improvement.
Technical scheme of the present invention is as follows:
A kind of method asking radiant correction coefficient, carry out data by computing machine to integrating sphere calibration data to read in, analyze and computing, based on Absolute Radiometric Calibration Coefficients, in conjunction with actual atural object radiance value, try to achieve the radiant correction coefficient after improvement, the method step is as follows:
(1) by computing machine, integrating sphere calibration data are read in DN value and the integrating sphere radiance value of pixel by wave band, each pixel DN value of integrating sphere calibration data is designated as DN 0(i, j), integrating sphere radiance value is designated as L 0j (), wherein i is pixel number, and j is wave band number, DN 0represent detector pixel Digital output numerical value, L 0for integrating sphere spoke brightness value, because infrared imaging system is linear, so adopt the linear absolute radiometric calibration formula in laboratory to obtain the Digital output numerical value of the pixel of detector:
DN 0(i,j)＝k 0(i,j)*L 0(j)，
Wherein k 0(i, j) be designated as wave band be j, pixel is the radiant correction coefficient of i;
(2) read raw image data and radiant correction coefficient data by computing machine, obtain the pixel DN value DN of each wave band of raw image data 1(i, j), by DN 1(i, j) substitutes into radiant correction formula, tries to achieve the radiance value of each pixel of original image after radiant correction, is designated as L 1(i, j), radiant correction formula is:
(3) the various radiation energy that remote sensing utilizes all will interact with earth atmosphere-or scattering, or absorb, and make energy attenuation, and spectral distribution is changed, the attenuation of air to different wave length only selectively, thus the image of air to different-waveband is different, therefore the process of these atmospheric effects will be eliminated to the image of radiant correction, selecting experience linear approach obtains Reflectivity for Growing Season, with ASD spectrometer respectively geodetic thing be DN value and the earth surface reflection Ref of water body and cement dyke, here water body shows for dark target, cement dyke shows for bright target, the DN value measured and reflectivity Ref store by wave band, the DN value of dark target and reflectivity Ref are DN l(j) and Ref lj (), the DN value of bright target and reflectivity Ref are DN h(j) and Ref h(j), the DN value of each wave band is made to be converted to reflectivity by linear regression technique, DN value and the reflectivity of dark target and bright target is read in by computing machine, respectively the DN value of dark target and bright target and reflectivity Ref being substituted into DN value is converted in the linear representation of reflectivity Ref, calculate Product-factor A (j) of each wave band and add deduction item B (j), by Product-factor A (j) with add deduction item B (j) and store by wave band, here, DN value is converted to the linear representation of reflectivity Ref and is:
Ref (i aSD, j)=A (j) * DN (i aSD, j)+B (j), wherein DN (i aSD, j) represent that the ASD spectrometers digitize of a jth wave band, i-th atural object pixel exports numerical value, Ref (i aSD, j) represent a corresponding jth wave band, i-th atural object pixel reflectance value, A (j) is Product-factor, relevant with atmospheric transmittance and instrument gain, and B (j) adds deduction item, relevant with dark current and atmospheric path radiation;
(4) the DN value DN of raw image data is read in by computing machine 1in (i, j) and step (3) atmospheric correction Product-factor A (j) with add deduction item B (j), by wave band by DN 1(i, j), A (j) and B (j) substitute into DN value and are converted in the linear representation of reflectivity Ref, obtain the reflectivity Ref (i, j) of each pixel of raw image data;
(5) the radiance value L of view data after radiant correction in step (2) is read in by computing machine 1the reflectivity Ref (i, j) of each pixel of raw image data in (i, j) and step (4), by wave band by L 1(i, j) and the mutually multiplied L of Ref (i, j) 2(i, j), L 2(i, j) is for carrying out the radiance value of pixel after atmospheric correction to view data after radiant correction in step (2);
(6) radiance value of ground atural object scaling point is by ASD spectrophotometer, if its radiance value measured is here n represents different atural object;
(7) open the atural object scaling point positional information file of ASD record, open the image after step (5) process simultaneously, image is found out the pixel consistent with geographical location information, and records the radiance value of this pixel
(8) identical wave band j, the radiance value of ground culture point with the radiance value of the pixel in correspondence image form a pair discrete point, the radiance value of Different Ground culture point with the radiance value of the pixel in correspondence image form one group of discrete point pair, read all discrete points data by computing machine, by wave band j to often organizing discrete point pair carry out least-squares algorithm linear fitting, obtain full wave linear fit slope k 1(j) and linear fit intercept d 1j (), by linear fit slope k 1(j) and linear fit intercept d 1j () is pressed wave band number and is stored, wherein, linear fit expression formula is: L 3 ( n ) ( j ) = k 1 ( j ) * L 2 ( n ) ( i , j ) + d 1 ( j ) ;
(9) the pixel i that step (7) image finds is recorded in, all pixels number are by integrating sphere calibration data the DN value DN (i of i, j) txt file is saved to by wave band, then the DN (i, j) of all pixels of each wave band found is averaged and obtain will with integrating sphere radiance value L 0j () is carried out two point Linear matchings and is tried to achieve k 2(j), k 2j () is here the radiant correction coefficient after the average of all pixel DN values and integrating sphere radiance value linear fit, wherein linear fit expression formula is: L ( j ) = k 2 ( j ) * D N ( j ) ‾ ;
(10) k is read by wave band 2(j), k 1(j) and d 1(j), note K (j)=k 1(j) * k 2(j), D (j)=d 1(j), obtain K (j) and the D (j) of each wave band, K (j) and D (j) is deposited by wave band, the K (j) tried to achieve and D (j) is new radiant correction coefficient, j band image DN value DN (j) can be converted to radiance value L (j) of j band image by conversion formula L (j)=K (j) * DN (j)+D (j).
Described DN value refers to Digital output numerical value.
The invention has the beneficial effects as follows that the radiant correction coefficient obtained carries out radiant correction to original image, the image after radiant correction is close to the actual spectrum curve of atural object.
Embodiment
Below in conjunction with embodiment, the invention will be further described, but be not limited thereto.
Embodiment:
The embodiment of the present invention is as follows, a kind of method asking radiant correction coefficient, carry out data by computing machine to integrating sphere calibration data to read in, analyze and computing, based on Absolute Radiometric Calibration Coefficients, in conjunction with actual atural object radiance value, try to achieve the radiant correction coefficient after improvement, the method step is as follows:
(1) by computing machine, integrating sphere calibration data are read in DN value and the integrating sphere radiance value of pixel by wave band, each pixel DN value of integrating sphere calibration data is designated as DN 0(i, j), integrating sphere radiance value is designated as L 0j (), wherein i is pixel number, and j is wave band number, DN 0represent detector pixel Digital output numerical value, L 0for integrating sphere spoke brightness value, because infrared imaging system is linear, so adopt the linear absolute radiometric calibration formula in laboratory to obtain the Digital output numerical value of the pixel of detector:
DN 0(i,j)＝k 0(i,j)*L 0(j)，
Wherein k 0(i, j) be designated as wave band be j, pixel is the radiant correction coefficient of i;
(2) read raw image data and radiant correction coefficient data by computing machine, obtain the pixel DN value DN of each wave band of raw image data 1(i, j), by DN 1(i, j) substitutes into radiant correction formula, tries to achieve the radiance value of each pixel of original image after radiant correction, is designated as L 1(i, j), radiant correction formula is:
(3) the various radiation energy that remote sensing utilizes all will interact with earth atmosphere-or scattering, or absorb, and make energy attenuation, and spectral distribution is changed, the attenuation of air to different wave length only selectively, thus the image of air to different-waveband is different, therefore the process of these atmospheric effects will be eliminated to the image of radiant correction, selecting experience linear approach obtains Reflectivity for Growing Season, with ASD spectrometer respectively geodetic thing be DN value and the earth surface reflection Ref of water body and cement dyke, here water body shows for dark target, cement dyke shows for bright target, the DN value measured and reflectivity Ref store by wave band, the DN value of dark target and reflectivity Ref are DN l(j) and Ref lj (), the DN value of bright target and reflectivity Ref are DN h(j) and Ref h(j), the DN value of each wave band is made to be converted to reflectivity by linear regression technique, DN value and the reflectivity of dark target and bright target is read in by computing machine, respectively the DN value of dark target and bright target and reflectivity Ref being substituted into DN value is converted in the linear representation of reflectivity Ref, calculate Product-factor A (j) of each wave band and add deduction item B (j), by Product-factor A (j) with add deduction item B (j) and store by wave band, here, DN value is converted to the linear representation of reflectivity Ref and is:
Ref (i aSD, j)=A (j) * DN (i aSD, j)+B (j), wherein DN (i aSD, j) represent that the ASD spectrometers digitize of a jth wave band, i-th atural object pixel exports numerical value, Ref (i aSD, j) represent a corresponding jth wave band, i-th atural object pixel reflectance value, A (j) is Product-factor, relevant with atmospheric transmittance and instrument gain, and B (j) adds deduction item, relevant with dark current and atmospheric path radiation;
(4) the DN value DN of raw image data is read in by computing machine 1in (i, j) and step (3) atmospheric correction Product-factor A (j) with add deduction item B (j), by wave band by DN 1(i, j), A (j) and B (j) substitute into DN value and are converted in the linear representation of reflectivity Ref, obtain the reflectivity Ref (i, j) of each pixel of raw image data;
(5) the radiance value L of view data after radiant correction in step (2) is read in by computing machine 1the reflectivity Ref (i, j) of each pixel of raw image data in (i, j) and step (4), by wave band by L 1(i, j) and the mutually multiplied L of Ref (i, j) 2(i, j), L 2(i, j) is for carrying out the radiance value of pixel after atmospheric correction to view data after radiant correction in step (2);
(6) radiance value of ground atural object scaling point is by ASD spectrophotometer, if its radiance value measured is here n represents different atural object;
(7) open the atural object scaling point positional information file of ASD record, open the image after step (5) process simultaneously, image is found out the pixel consistent with geographical location information, and records the radiance value of this pixel
(8) identical wave band j, the radiance value of ground culture point with the radiance value of the pixel in correspondence image form a pair discrete point, the radiance value of Different Ground culture point with the radiance value of the pixel in correspondence image form one group of discrete point pair, read all discrete points data by computing machine, by wave band j to often organizing discrete point pair carry out least-squares algorithm linear fitting, obtain full wave linear fit slope k 1(j) and linear fit intercept d 1j (), by linear fit slope k 1(j) and linear fit intercept d 1j () is pressed wave band number and is stored, wherein, linear fit expression formula is: L 3 ( n ) ( j ) = k 1 ( j ) * L 2 ( n ) ( i , j ) + d 1 ( j ) ;
(9) the pixel i that step (7) image finds is recorded in, all pixels number are by integrating sphere calibration data the DN value DN (i of i, j) txt file is saved to by wave band, then the DN (i, j) of all pixels of each wave band found is averaged and obtain will with integrating sphere radiance value L 0j () is carried out two point Linear matchings and is tried to achieve k 2(j), k 2j () is here the radiant correction coefficient after the average of all pixel DN values and integrating sphere radiance value linear fit, wherein linear fit expression formula is: L ( j ) = k 2 ( j ) * D N ( j ) ‾ ;
(10) k is read by wave band 2(j), k 1(j) and d 1(j), note K (j)=k 1(j) * k 2(j), D (j)=d 1(j), obtain K (j) and the D (j) of each wave band, K (j) and D (j) is deposited by wave band, the K (j) tried to achieve and D (j) is new radiant correction coefficient, j band image DN value DN (j) can be converted to radiance value L (j) of j band image by conversion formula L (j)=K (j) * DN (j)+D (j).

Claims (1)

1. ask the method for radiant correction coefficient for one kind, carry out data by computing machine to integrating sphere calibration data to read in, analyze and computing, based on Absolute Radiometric Calibration Coefficients, in conjunction with actual atural object radiance value, try to achieve the radiant correction coefficient after improvement, the method step is as follows:
(1) by computing machine, integrating sphere calibration data are read in DN value and the integrating sphere radiance value of pixel by wave band, each pixel DN value of integrating sphere calibration data is designated as DN 0(i, j), integrating sphere radiance value is designated as L 0j (), wherein i is pixel number, and j is wave band number, DN 0represent detector pixel Digital output numerical value, L 0for integrating sphere spoke brightness value, because infrared imaging system is linear, so adopt the linear absolute radiometric calibration formula in laboratory to obtain the Digital output numerical value of the pixel of detector:
DN 0(i,j)＝k 0(i,j)*L 0(j)，
Wherein k 0(i, j) be designated as wave band be j, pixel is the radiant correction coefficient of i;
(2) read raw image data and radiant correction coefficient data by computing machine, obtain the pixel DN value DN of each wave band of raw image data 1(i, j), by DN 1(i, j) substitutes into radiant correction formula, tries to achieve the radiance value of each pixel of original image after radiant correction, is designated as L 1(i, j), radiant correction formula is:
(3) the various radiation energy that remote sensing utilizes all will interact with earth atmosphere-or scattering, or absorb, and make energy attenuation, and spectral distribution is changed, the attenuation of air to different wave length only selectively, thus the image of air to different-waveband is different, therefore the process of these atmospheric effects will be eliminated to the image of radiant correction, selecting experience linear approach obtains Reflectivity for Growing Season, with ASD spectrometer respectively geodetic thing be DN value and the earth surface reflection Ref of water body and cement dyke, here water body shows for dark target, cement dyke shows for bright target, the DN value measured and reflectivity Ref store by wave band, the DN value of dark target and reflectivity Ref are DN l(j) and Ref lj (), the DN value of bright target and reflectivity Ref are DN h(j) and Ref h(j), the DN value of each wave band is made to be converted to reflectivity by linear regression technique, DN value and the reflectivity of dark target and bright target is read in by computing machine, respectively the DN value of dark target and bright target and reflectivity Ref being substituted into DN value is converted in the linear representation of reflectivity Ref, calculate Product-factor A (j) of each wave band and add deduction item B (j), by Product-factor A (j) with add deduction item B (j) and store by wave band, here, DN value is converted to the linear representation of reflectivity Ref and is:
Ref (i aSD, j)=A (j) * DN (i aSD, j)+B (j), wherein DN (i aSD, j) represent that the ASD spectrometers digitize of a jth wave band, i-th atural object pixel exports numerical value, Ref (i aSD, j) represent a corresponding jth wave band, i-th atural object pixel reflectance value, A (j) is Product-factor, relevant with atmospheric transmittance and instrument gain, and B (j) adds deduction item, relevant with dark current and atmospheric path radiation;
(4) the DN value DN of raw image data is read in by computing machine 1in (i, j) and step (3) atmospheric correction Product-factor A (j) with add deduction item B (j), by wave band by DN 1(i, j), A (j) and B (j) substitute into DN value and are converted in the linear representation of reflectivity Ref, obtain the reflectivity Ref (i, j) of each pixel of raw image data;
(5) the radiance value L of view data after radiant correction in step (2) is read in by computing machine 1the reflectivity Ref (i, j) of each pixel of raw image data in (i, j) and step (4), by wave band by L 1(i, j) and the mutually multiplied L of Ref (i, j) 2(i, j), L 2(i, j) is for carrying out the radiance value of pixel after atmospheric correction to view data after radiant correction in step (2);
(6) radiance value of ground atural object scaling point is by ASD spectrophotometer, if its radiance value measured is here n represents different atural object;
(7) open the atural object scaling point positional information file of ASD record, open the image after step (5) process simultaneously, image is found out the pixel consistent with geographical location information, and records the radiance value of this pixel
(8) identical wave band j, the radiance value of ground culture point with the radiance value of the pixel in correspondence image form a pair discrete point, the radiance value of Different Ground culture point with the radiance value of the pixel in correspondence image form one group of discrete point pair, read all discrete points data by computing machine, by wave band j to often organizing discrete point pair carry out least-squares algorithm linear fitting, obtain full wave linear fit slope k 1(j) and linear fit intercept d 1j (), by linear fit slope k 1(j) and linear fit intercept d 1j () is pressed wave band number and is stored, wherein, linear fit expression formula is: L 3 ( n ) ( j ) = k 1 ( j ) * L 2 ( n ) ( i , j ) + d 1 ( j ) ;
(9) the pixel i that step (7) image finds is recorded in, all pixels number are by integrating sphere calibration data the DN value DN (i of i, j) txt file is saved to by wave band, then the DN (i, j) of all pixels of each wave band found is averaged and obtain will with integrating sphere radiance value L 0j () is carried out two point Linear matchings and is tried to achieve k 2(j), k 2j () is here the radiant correction coefficient after the average of all pixel DN values and integrating sphere radiance value linear fit, wherein linear fit expression formula is: L ( j ) = k 2 ( j ) * D N ( j ) ‾ ;
(10) k is read by wave band 2(j), k 1(j) and d 1(j), note K (j)=k 1(j) * k 2(j), D (j)=d 1(j), obtain K (j) and the D (j) of each wave band, K (j) and D (j) is deposited by wave band, the K (j) tried to achieve and D (j) is new radiant correction coefficient, j band image DN value DN (j) can be converted to radiance value L (j) of j band image by conversion formula L (j)=K (j) * DN (j)+D (j).
CN201510381649.7A 2015-07-02 2015-07-02 A kind of method for seeking radiant correction coefficient Active CN105160631B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510381649.7A CN105160631B (en) 2015-07-02 2015-07-02 A kind of method for seeking radiant correction coefficient

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510381649.7A CN105160631B (en) 2015-07-02 2015-07-02 A kind of method for seeking radiant correction coefficient

Publications (2)

Publication Number Publication Date
CN105160631A true CN105160631A (en) 2015-12-16
CN105160631B CN105160631B (en) 2018-06-29

Family

ID=54801474

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510381649.7A Active CN105160631B (en) 2015-07-02 2015-07-02 A kind of method for seeking radiant correction coefficient

Country Status (1)

Country Link
CN (1) CN105160631B (en)

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106485683A (en) * 2016-10-20 2017-03-08 中国科学院上海技术物理研究所启东光电遥感中心 A kind of image adaptive non-uniform correction method based on scene
CN106600646A (en) * 2016-11-25 2017-04-26 北京空间机电研究所 Method for correcting uniformity of on-orbit image of infrared pendular scanning camera
CN107656289A (en) * 2017-08-23 2018-02-02 中国科学院光电研究院 Spaceborne optics load absolute radiation calibration method and system based on ground spoke brightness
CN107860478A (en) * 2017-11-17 2018-03-30 北京长峰科威光电技术有限公司 A kind of restorative procedure of infrared imaging system cold emission blackspot
CN108090883A (en) * 2018-01-04 2018-05-29 中煤航测遥感集团有限公司 High spectrum image preprocess method, device and electronic equipment
CN108174127A (en) * 2018-01-30 2018-06-15 中国科学院长春光学精密机械与物理研究所 Relative radiometric correction methods of the face battle array CMOS under global shutter working method
CN109035150A (en) * 2018-04-24 2018-12-18 湖南省有色地质勘查研究院 A kind of remote sensing image data defogging method based on middle-low alloy steels
CN114965306A (en) * 2022-05-27 2022-08-30 淮阴师范学院 Calibration method of optical sensor for measuring reflectivity
CN115615938A (en) * 2022-12-14 2023-01-17 天津中科谱光信息技术有限公司 Water quality analysis method and device based on reflection spectrum and electronic equipment

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101442608A (en) * 2008-12-31 2009-05-27 中国资源卫星应用中心 Method for improving relative radiation correction of CCD camera
US20100208870A1 (en) * 2009-02-19 2010-08-19 Yu Zou Scattered radiation correction method and scattered radiation correction apparatus
CN102324098A (en) * 2011-08-23 2012-01-18 中国资源卫星应用中心 Relative radiation calibration method in combination with laboratory calibration and even landscape statistics
CN104580944A (en) * 2013-10-10 2015-04-29 中国科学院光电研究院 Method for carrying out relative radiometric calibration on CCD (Charge-Coupled Device) image

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101442608A (en) * 2008-12-31 2009-05-27 中国资源卫星应用中心 Method for improving relative radiation correction of CCD camera
US20100208870A1 (en) * 2009-02-19 2010-08-19 Yu Zou Scattered radiation correction method and scattered radiation correction apparatus
CN102324098A (en) * 2011-08-23 2012-01-18 中国资源卫星应用中心 Relative radiation calibration method in combination with laboratory calibration and even landscape statistics
CN104580944A (en) * 2013-10-10 2015-04-29 中国科学院光电研究院 Method for carrying out relative radiometric calibration on CCD (Charge-Coupled Device) image

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
HERRERO-HUERTA M ET AL.: "Vicarious radiometric calibration of a multispectral sensor from an aerial trike applied to precision agriculture", 《COMPUTERS & ELECTRONICS IN AGRICULTURE》 *
吕桂龙: "机载推帚式高光谱图像预处理技术研究与实现", 《中国优秀硕士学位论文全文数据库 信息科技辑》 *
曾湧 等: "基于实验室定标和均匀景统计的相对辐射定标方法", 《航天返回与遥感》 *
马庆军: "高光谱成像仪的高精度实验室辐射定标及校正方法", 《硅谷》 *

Cited By (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106485683A (en) * 2016-10-20 2017-03-08 中国科学院上海技术物理研究所启东光电遥感中心 A kind of image adaptive non-uniform correction method based on scene
CN106600646B (en) * 2016-11-25 2019-05-24 北京空间机电研究所 A kind of in-orbit image conformity bearing calibration of infrared sweeping camera
CN106600646A (en) * 2016-11-25 2017-04-26 北京空间机电研究所 Method for correcting uniformity of on-orbit image of infrared pendular scanning camera
CN107656289A (en) * 2017-08-23 2018-02-02 中国科学院光电研究院 Spaceborne optics load absolute radiation calibration method and system based on ground spoke brightness
CN107860478B (en) * 2017-11-17 2019-11-22 北京长峰科威光电技术有限公司 A kind of restorative procedure of infrared imaging system cold emission blackspot
CN107860478A (en) * 2017-11-17 2018-03-30 北京长峰科威光电技术有限公司 A kind of restorative procedure of infrared imaging system cold emission blackspot
CN108090883A (en) * 2018-01-04 2018-05-29 中煤航测遥感集团有限公司 High spectrum image preprocess method, device and electronic equipment
CN108090883B (en) * 2018-01-04 2020-05-05 中煤航测遥感集团有限公司 Hyperspectral image preprocessing method and device and electronic equipment
CN108174127A (en) * 2018-01-30 2018-06-15 中国科学院长春光学精密机械与物理研究所 Relative radiometric correction methods of the face battle array CMOS under global shutter working method
CN109035150A (en) * 2018-04-24 2018-12-18 湖南省有色地质勘查研究院 A kind of remote sensing image data defogging method based on middle-low alloy steels
CN109035150B (en) * 2018-04-24 2019-05-10 湖南省有色地质勘查研究院 A kind of remote sensing image data defogging method based on middle-low alloy steels
CN114965306A (en) * 2022-05-27 2022-08-30 淮阴师范学院 Calibration method of optical sensor for measuring reflectivity
CN114965306B (en) * 2022-05-27 2024-02-20 淮阴师范学院 Calibration method of optical sensor for measuring reflectivity
CN115615938A (en) * 2022-12-14 2023-01-17 天津中科谱光信息技术有限公司 Water quality analysis method and device based on reflection spectrum and electronic equipment
CN115615938B (en) * 2022-12-14 2023-03-28 天津中科谱光信息技术有限公司 Water quality analysis method and device based on reflection spectrum and electronic equipment

Also Published As

Publication number Publication date
CN105160631B (en) 2018-06-29

Similar Documents

Publication Publication Date Title
CN105160631A (en) Method for calculating radiation correction coefficient
CN108662991B (en) Land block scale winter wheat leaf area index estimation method based on remote sensing satellite data
US10527542B2 (en) Method of calculating TAVI based on a band ratio model and solar altitude angle
CN106780079B (en) Winter wheat different growth period leaf area index inversion method based on remote sensing data
Tan et al. A comparison of radiometric correction techniques in the evaluation of the relationship between LST and NDVI in Landsat imagery
CN112050948B (en) Non-barrier infrared temperature measurement method based on detector temperature drift model
CN110987821B (en) Hyperspectral rapid atmospheric correction parameterization method
CN102901516A (en) Multispectral image radiation correction method based on absolute radiometric calibration
CN109269641B (en) Multi-sensor cooperative radiometric calibration method for space-painting first satellite
CN102540166A (en) Cross radiation calibration method based on optimization algorithm of hyper-spectral sensor
CN111323129A (en) Earth surface temperature inversion method based on broadband thermal infrared image
Kusnierek et al. Challenges in using an analog uncooled microbolometer thermal camera to measure crop temperature
Wen et al. Parametrized BRDF for atmospheric and topographic correction and albedo estimation in Jiangxi rugged terrain, China
CN114564767A (en) Under-cloud surface temperature estimation method based on sun-cloud-satellite observation geometry
CN114219994A (en) Ocean optical satellite radiometric calibration method based on air-sea cooperative observation
CN111044153B (en) Nonlinear calibration method and device for infrared spectrum of spectrum correlation system
Liu et al. Vicarious calibration of the formosat-2 remote sensing instrument
CN105737980A (en) Radiometric calibration method and device
CN111044152B (en) Self-adaptive correction method and system for spectrum bias external field of spectrum correlation system
CN113029977B (en) Automatic cross radiometric calibration method for wide-field-angle multispectral sensor
CN115222619A (en) Wall surface emissivity solving method based on thermal infrared image correction brightness of thermal imager
CN110702228B (en) Edge radiation correction method for aviation hyperspectral image
Wang et al. Mapping soil organic matter content in field using HJ-1 satellite image
Aleksanin et al. The Influence of Observation Conditions on the Accuracy of NDVI Vegetation Index Calculation from Earth Remote Sensing Data
Zahir Application of Geo-informatics Technology to Access the Surface Temperature Using LANDSAT 8 OLI/TIRS Satellite Data: A Case Study in Ampara District in Sri Lanka

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant