CN113218874A - Method and system for obtaining surface target object reflectivity based on remote sensing image - Google Patents
Method and system for obtaining surface target object reflectivity based on remote sensing image Download PDFInfo
- Publication number
- CN113218874A CN113218874A CN202110478899.8A CN202110478899A CN113218874A CN 113218874 A CN113218874 A CN 113218874A CN 202110478899 A CN202110478899 A CN 202110478899A CN 113218874 A CN113218874 A CN 113218874A
- Authority
- CN
- China
- Prior art keywords
- information
- atmospheric
- reflectivity
- earth
- pixel
- 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.)
- Pending
Links
- 238000002310 reflectometry Methods 0.000 title claims abstract description 111
- 238000000034 method Methods 0.000 title claims abstract description 42
- 239000000443 aerosol Substances 0.000 claims abstract description 50
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 44
- 238000012937 correction Methods 0.000 claims abstract description 36
- 238000012545 processing Methods 0.000 claims description 24
- 238000002834 transmittance Methods 0.000 claims description 22
- 230000003595 spectral effect Effects 0.000 claims description 20
- 230000005855 radiation Effects 0.000 claims description 10
- 230000008569 process Effects 0.000 claims description 8
- 238000005316 response function Methods 0.000 claims description 6
- 238000004088 simulation Methods 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 5
- 238000003384 imaging method Methods 0.000 claims description 5
- 230000001360 synchronised effect Effects 0.000 claims description 5
- 230000005540 biological transmission Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000009792 diffusion process Methods 0.000 claims description 3
- 230000001174 ascending effect Effects 0.000 claims 1
- 230000000694 effects Effects 0.000 description 9
- 230000008859 change Effects 0.000 description 5
- 230000003287 optical effect Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000003702 image correction Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 238000012892 rational function Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
- 238000011144 upstream manufacturing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/55—Specular reflectivity
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1793—Remote sensing
Landscapes
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Computer Networks & Wireless Communication (AREA)
- Image Processing (AREA)
Abstract
The method comprises the steps that first atmospheric parameter information and an earth-surface load image are synchronously acquired through a first instrument and an earth-surface observation load camera which are carried on the same satellite; acquiring aerosol information and water vapor information synchronously corresponding to each pixel in the ground load image through longitude and latitude information in the first atmospheric parameter information; determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; acquiring apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera; and under the condition that the earth load image does not contain cloud information, acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the earth surface comprehensive reflectivity and the background reflectivity. The method and the device ensure the authenticity of the reflectivity of the obtained earth surface target object, namely ensure the authenticity of the earth surface load image reflecting the real reflectivity of the earth surface.
Description
The present patent application claims priority of chinese patent application No. CN2021103921944, entitled "method and system for obtaining reflectivity of ground surface target object based on remote sensing image", filed on 13/04/2021, which is incorporated herein by reference in its entirety.
Technical Field
The application belongs to the technical field of remote sensing, and particularly relates to a method and a system for obtaining the reflectivity of a surface target object based on a remote sensing image.
Background
The optical radiation signal received by the satellite load is the coupling information of the earth surface information and the atmosphere information, wherein the earth surface information is required to be observed, and the atmosphere information is the interference item thereof. Because, on the one hand, atmospheric blurring effects caused by atmospheric scattering and absorption have a significant influence on the quality of the satellite image (i.e. the image corresponding to the optical radiation signal); on the other hand, the satellite image is distorted when the real reflectivity of the earth surface is reflected. Therefore, how to obtain real earth surface information from the satellite images and obtain real surface feature reflectivity is the focus of research.
Disclosure of Invention
The application aims to provide a method and a system for obtaining the reflectivity of an earth surface target object based on a remote sensing image so as to solve the problems in the prior art.
An embodiment of the application provides a method for obtaining surface target object reflectivity based on remote sensing images, which comprises the following steps: synchronously acquiring first atmospheric parameter information and a ground load image through a first instrument and a ground load observation camera which are carried on the same satellite; the first atmospheric parameter information comprises longitude and latitude information, aerosol information and water vapor information; aerosol information and water vapor information synchronously corresponding to all pixels in the ground load image are obtained through the longitude and latitude information; determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle; acquiring apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera; under the condition that the earth load image does not contain cloud information, acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity.
The method as described above, wherein optionally, the obtaining aerosol information and water vapor information synchronously corresponding to each pixel in the geo-referenced load image through the latitude and longitude information includes: according to the time information, matching a first atmospheric parameter with the same imaging time aiming at the ground load image, and obtaining first image information after the first atmospheric parameter is matched; analyzing the first image pixel by pixel to obtain longitude and latitude information corresponding to each pixel of the ground load image; and acquiring aerosol information and water vapor information matched with each pixel in the synchronous first atmospheric parameter information based on the longitude and latitude information.
The method as described above, wherein optionally, the obtaining aerosol information and water vapor information matched with each pixel in the synchronized first atmospheric parameter information based on the longitude and latitude information includes: and matching one or the combination of aerosol information and water vapor information in the first atmospheric parameter information to each pixel of the geo-referenced load image through an interpolation method based on the longitude and latitude information.
The method as described above, wherein optionally, the obtaining the apparent radiance corresponding to each pixel element according to the radiometric calibration parameter of the earth observation load camera includes: acquiring radiometric calibration parameters of the earth observation load camera; establishing a first relation among the radiometric calibration parameters, the gray value of each pixel and the apparent radiance; and acquiring the apparent radiance corresponding to each pixel based on the first relation.
The method as above, wherein, optionally, the second atmospheric parameter comprises an upstream atmospheric transmittance T (θ)v) And the downstream atmospheric transmittance T (theta)s) Atmospheric range radiation LpathAtmospheric hemisphere albedo S; acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter, and specifically comprising the following steps:
obtaining the surface comprehensive reflectivity by the following formula:
wherein: l is the apparent radiance; fsIs the wave band average out-of-atmosphere solar irradiance, relative to the corresponding wave band of the ground load image, thetasIs the zenith angle of the sun, thetavAnd observing the zenith angle.
The method as described above, wherein optionally, the determining the background reflectivity around the surface target image element comprises:
calculating atmospheric point diffusion function weight reflecting mutual influence between adjacent pixels and a target pixel according to the resolution of the earth observation load camera; and determining the background reflectivity around each pixel in the earth surface target object based on the atmospheric point spread function weight and the earth surface comprehensive reflectivity of each pixel.
The method as described above, wherein optionally, the second atmospheric parameter includes atmospheric diffuse transmittance, atmospheric direct transmittance; the obtaining the reflectivity of the surface target object based on the second atmospheric parameter, the surface comprehensive reflectivity and the background reflectivity comprises: determining a ratio of the atmospheric diffuse transmittance and the direct atmospheric transmittance as a first correction coefficient; and correcting the comprehensive earth surface reflectivity of each pixel element of the earth load image by using a set relation so as to acquire the reflectivity of the earth surface target object, wherein the set relation is as follows:
ρt=[ρ1+q(ρ1-ρM)]·[1-(ρM-0.15)·S]
where ρ is1For the total reflectivity of the earth's surface, ptIn order to obtain the reflectivity of the ground surface target object after correction, S is the albedo of the atmospheric hemisphere, q is a first correction coefficient, rhoMIs the background reflectivity around the target pixel.
The method as described above, wherein optionally, the preset atmospheric correction look-up table includes: the sub lookup tables respectively correspond to the spectral bands of the earth observation load camera; the construction process of the sub lookup table is as follows:
determining a spectral band, a spectral response function and an aerosol transmission model corresponding to the pre-constructed sub lookup table; setting parameter items, wherein the parameter items comprise aerosol information, water vapor information, a solar zenith angle, an observation zenith angle and a relative azimuth angle; calculating a result of the second atmospheric parameter as a function of one or a combination of the parameter terms based on the spectral band, the spectral response function, the aerosol transport model simulation; and constructing the sub lookup table according to a simulation calculation result, the aerosol information, the water vapor information, the solar zenith angle, the observation zenith angle and the relative azimuth angle.
The method as described above, wherein optionally, in case the geo-payload image contains cloud information, then obtaining the apparent reflectivity based on the apparent radiance.
Another embodiment of the present application provides a system for obtaining surface target reflectivity based on remote sensing images, including:
the system comprises a first instrument and an earth observation load camera which are carried on the same satellite, wherein the first instrument and the earth observation load camera synchronously acquire first atmospheric parameter information and an earth load image; the first atmospheric parameter information comprises longitude and latitude information, aerosol information and water vapor information;
the first processing device is used for receiving information of the first instrument and the earth observation load camera and obtaining aerosol information and water vapor information synchronously corresponding to each pixel in the earth load image through the longitude and latitude information;
the second processing device is used for determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle;
the third processing device is used for acquiring the apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera;
the fourth processing device is used for acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter under the condition that the earth load image does not contain cloud information; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity.
Compared with the prior art, in the implementation process, the data reliability is ensured by taking the first atmospheric parameter information and the earth load image which are synchronously acquired by the first instrument and the earth observation load camera which are carried on the same satellite as the data for acquiring the reflectivity of the earth surface target object based on the remote sensing image, and meanwhile, in the data processing process, the second atmospheric parameter corresponding to each pixel is determined according to the preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle; acquiring apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera; under the condition that the earth load image does not contain cloud information, acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity, improving the image definition and the image quality of a processing result, and ensuring the authenticity and the accuracy of the reflectivity of the obtained earth surface target object, namely ensuring the authenticity and the accuracy of the earth surface load image reflecting the real reflectivity of the earth surface.
Drawings
Fig. 1 is a schematic flow chart of a method for obtaining the reflectivity of a surface target object based on a remote sensing image according to the present application;
FIG. 2 is a schematic diagram showing comparison results before and after processing of remote sensing images for town areas;
FIG. 3 is a graphical representation of the comparison of the remote sensing images before and after processing for rural areas;
fig. 4 is a comparison diagram of the spectral reflectance of the ground surface target (vegetation) and the spectral emissivity curve of the standard ground object before and after the remote sensing image processing.
Detailed Description
The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
As shown in fig. 1, an embodiment of the present application provides a method for obtaining a reflectivity of an earth surface target based on a remote sensing image, which includes:
s1, synchronously acquiring first atmospheric parameter information and a ground load image by a first instrument and a ground load observation camera on the same satellite; the first atmospheric parameter information comprises longitude and latitude information, aerosol information and water vapor information.
Specifically, the composition of the earth's atmosphere is different in each region and changes at any time, and particularly, the temporal and spatial changes of water vapor and aerosol are large and are main uncertain factors in the atmosphere. In order to realize higher ground load image correction accuracy level, the method and the device are based on the premise that the first atmospheric parameter information and the ground load image are synchronously acquired by a first instrument and a ground observation load camera on the same satellite.
The ground observation load camera is used, a wide multispectral camera, a hyperspectral camera and an infrared camera are exemplified, the wide multispectral camera can be used in the application, the resolution of the wide multispectral camera is 16m, the width is 800km, the full view field is 62.6 degrees, and a wide and large view field ground load image is obtained through the wide and large view field ground observation load camera. Because the field of view is relatively large, the observation zenith angle and the observation azimuth angle of the camera change along with the pixel, and the sun zenith angle and the sun azimuth angle also change along with the change of the geographic position in the whole width, and the difference of the observation zenith angle, the observation azimuth angle, the sun zenith angle and the sun azimuth angle can cause the length of an atmospheric transmission path to be different, so that the atmospheric parameters such as the optical thickness of aerosol, the water vapor content and the like are changed, namely, the longitude and latitude information, the aerosol information and the water vapor information change along with the pixel, so that a first instrument is required to synchronously acquire the information. The adopted first instrument is an atmosphere correction instrument and is used for synchronously acquiring high-precision atmospheric parameters, and the atmospheric parameters exemplarily comprise longitude and latitude information, aerosol information, water vapor information and the like.
S2, acquiring aerosol information and water vapor information synchronously corresponding to each pixel in the ground load image through the longitude and latitude information;
specifically, according to time information, first atmospheric parameters with the same imaging time are matched for a ground load image, and first image information after the first atmospheric parameters are matched is obtained; then analyzing the first image pixel by pixel to obtain longitude and latitude information corresponding to each pixel of the ground load image; and acquiring aerosol information and water vapor information matched with each pixel in the synchronous first atmospheric parameter information based on the longitude and latitude information.
In the specific implementation, the wide multispectral image product data and the product data of the atmosphere corrector are stored in different scenes, and the widths of the scenes are the same. And matching the atmospheric correction instrument data with the same imaging time according to the imaging date and time of the wide multispectral image data to be corrected to realize scene-division matching.
And reading rpb files corresponding to the wide multispectral image, and analyzing and obtaining longitude and latitude information and longitude and latitude information of each pixel of the multispectral image based on a rational function model.
The aerosol and water vapor parameters obtained by the atmosphere correction instrument are stored in an H5 file, the aerosol information, the water vapor information and the longitude and latitude information are in one-to-one correspondence, and the atmospheric parameters obtained by the atmosphere correction instrument are matched to the wide multispectral image pixel by pixel according to the longitude and latitude information of each pixel of the wide multispectral image and the longitude and latitude information of the data of the atmosphere correction instrument.
S3, determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle;
s4, acquiring apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera;
s5, acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter under the condition that the earth load image does not contain cloud information; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity.
According to the method, through the processes, the first atmospheric parameter information and the ground load image which are synchronously acquired by the first instrument carried on the same satellite and the ground observation load camera are used as data for acquiring the reflectivity of the earth surface target object based on the remote sensing image, so that the accuracy of the data is ensured, and meanwhile, in the data processing process, the second atmospheric parameter corresponding to each pixel is determined according to the preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle; acquiring apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera; under the condition that the earth load image does not contain cloud information, acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive earth surface reflectivity and the background reflectivity, improving the image definition and the image quality of a processing result, and ensuring the real reflectivity of the obtained earth surface target object, namely ensuring that the ground load image reflects the authenticity of the real earth surface reflectivity.
Considering that the atmospheric characteristics do not change greatly in a certain space, the spatial resolution of the current general atmospheric correction instrument is km level, and the spatial resolution of the earth load wide multispectral image is m level, so that part or all information of the atmospheric correction instrument is matched to the wide multispectral image pixel by pixel through an interpolation method. And matching one or the combination of aerosol information and water vapor information in the first atmospheric parameter information to each pixel of the ground load image through an interpolation method based on the longitude and latitude information.
Further, in step S4, obtaining the apparent radiance corresponding to each pixel according to the radiometric parameter of the earth observation load camera includes:
acquiring radiometric calibration parameters of the earth observation load camera; establishing a first relation among the radiometric calibration parameters, the gray value of each pixel and the apparent radiance; and acquiring the apparent radiance corresponding to each pixel based on the first relation.
Specifically, a ground observation load camera, such as the multispectral camera of the present application, has a radiometric calibration parameter, and corresponds to an image pixel gray value for each pixel of a ground observation remote sensing image, and establishes a first relationship among the radiometric calibration parameter, the gray value of each pixel, and an apparent radiance as follows:
L=A·DN+C
in the above formula, DN is the gray value of each pixel of each spectral band of the earth-observation remote sensing image, a is the slope of the radiometric calibration coefficient of the earth-observation load camera, C is the intercept of the radiometric calibration coefficient, and L is the apparent radiance of the multispectral image obtained by conversion.
Further, the second atmospheric parameters exemplarily include an upward atmospheric transmittance, a downward atmospheric transmittance, an atmospheric direct transmittance, an atmospheric diffuse transmittance, a hemispherical albedo, a range radiation, an earth surface irradiance and the like, the second atmospheric parameters corresponding to each pixel are determined according to a preset atmospheric correction lookup table, and the preset atmospheric correction lookup table is used for determining the second atmospheric parameters corresponding to each pixel according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, a solar zenith angle, an observation zenith angle and a relative azimuth angle; in a specific implementation, the preset atmospheric calibration lookup table includes: and the sub lookup tables respectively correspond to the spectral bands of the earth observation load camera.
And the construction process of the sub lookup table is as follows:
determining a spectral band, a spectral response function and an aerosol transmission model corresponding to the pre-constructed sub lookup table; setting parameter items, wherein the parameter items comprise aerosol information, water vapor information, a solar zenith angle, an observation zenith angle and a relative azimuth angle; calculating a result of the second atmospheric parameter as a function of one or a combination of the parameter terms based on the spectral band, the spectral response function, the aerosol transport model simulation; and constructing the sub lookup table according to a simulation calculation result, the aerosol information, the water vapor information, the solar zenith angle, the observation zenith angle and the relative azimuth angle.
The construction of the sub-lookup table can be expanded as desired by those skilled in the art under the above framework and is not described in further detail herein.
Step S5, obtaining the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter, specifically including: obtaining the surface comprehensive reflectivity by the following formula:
wherein: l is the apparent radiance; l ispathFor atmospheric radiation, FsIs the wave band average out-of-atmosphere solar irradiance, relative to the corresponding wave band of the ground load image, thetasIs the zenith angle of the sun, thetavObserve the zenith angle, T (theta)v) For upward atmospheric transmittance, T (theta)s) The downward atmospheric transmittance and S the atmospheric hemisphere albedo.
The step S5 of determining the background reflectivity around the surface target object image element includes:
calculating atmospheric point diffusion function weight reflecting mutual influence between adjacent pixels and a target pixel according to the resolution of the earth observation load camera; and determining the background reflectivity around each pixel in the earth surface target object based on the atmospheric point spread function weight and the earth surface comprehensive reflectivity of each pixel.
Specifically, the mutual influence between the adjacent pixels and the target pixels is caused by an adjacent Effect (adjacent Effect), and as can be understood, the adjacent Effect refers to a phenomenon that photons reflected by an unobserved target in remote sensing reach a sensor through atmospheric scattering, and is also called atmospheric Cross radiation (Cross radiation). This causes the apparent radiation amount observed to the ground by the remote sensor on the high-altitude platform to contain contributions from the earth surface of the environment surrounding the field of view, causing image blurring and reducing the actual resolution and quantification accuracy of the remote sensing image. The three main factors that influence the proximity effect are: the resolution of the earth observation load camera, atmospheric parameters, and satellite observation geometry. Therefore, the influence of the adjacent pixels can be regarded as the convolution of the radiation field of the target surface and the atmospheric point spread function, the weight function of the atmospheric point spread function can be calculated according to the spatial resolution of the multispectral camera, and further the comprehensive surface reflectivity of each pixel is determined:
in the above formula, ρMFor the background reflectivity around the target pixel, N is the proximity effect window size, which represents the proximity effect influence range, and for the multispectral camera used in this application, N is 5, for example. P (x, y) can be regarded as a weight function, which describesAt a distance of from the target pixelThe contribution rate of the point to the target pixel. Considering that the influence of the neighboring pixels on the target pixel exponentially decreases with the increase of the distance, the weight function is calculated using the following formula.
Further, the second atmospheric parameter comprises atmospheric diffuse transmittance and atmospheric direct transmittance; step S5, the obtaining the reflectivity of the surface target object based on the second atmospheric parameter, the surface integrated reflectivity and the background reflectivity includes:
determining a ratio of the atmospheric diffuse transmittance and the direct atmospheric transmittance as a first correction coefficient; and correcting the comprehensive earth surface reflectivity of each pixel element of the earth load image by using a set relation so as to acquire the reflectivity of the earth surface target object, wherein the set relation is as follows:
ρt=[ρ1+q(ρ1-ρM)]·[1-(ρM-0.15)·S]
where ρ istFor the corrected reflectivity, p, of the earth surface target1For the total reflectivity of the earth's surface, pMThe background reflectivity around the target pixel is shown, S is the atmospheric hemisphere albedo, and q is a first correction coefficient.
The ground load image information which is from step S1 and is subjected to preliminary processing in steps S2 to S4, namely the apparent radiance corresponding to each pixel is further processed in step S5, so that the contrast and the definition of the remote sensing image can be effectively improved, the color is more vivid and real, the details of the image can be better presented, the effect of the reflectivity of the obtained ground surface target object can be ensured, and the comparison result of the remote sensing image in the town area before and after processing is shown in figure 2, wherein the left image is the remote sensing image in the untreated town area, and the right side is the remote sensing image in the treated town area; the comparison result before and after processing for the remote sensing image of the rural area is shown in fig. 3, the left image is the remote sensing image of the unprocessed rural area, and the right image is the remote sensing image of the processed rural area. The comparison of the spectral reflectance of the surface target (vegetation) and the spectral reflectance of the standard surface target after the remote sensing image is processed is shown in fig. 4.
The further method also comprises the following steps: in the case where the ground load image contains cloud information, then the apparent reflectance is obtained based on the apparent radiance.
It is understood that in the case where the ground load image contains cloud information, the surface target reflectivity cannot be obtained, and at this time, the apparent reflectivity is obtained based on the apparent radiance as a processing result of the ground load image. Whether the ground load image contains cloud information can be judged according to the apparent radiance corresponding to each pixel after the apparent radiance corresponding to each pixel is obtained. The determination process can be developed as required by those skilled in the art, and is not described in detail herein.
The embodiment of the application further provides a system for obtaining the reflectivity of an earth surface target object based on the remote sensing image, which comprises:
the system comprises a first instrument and an earth observation load camera which are carried on the same satellite, wherein the first instrument and the earth observation load camera synchronously acquire first atmospheric parameter information and an earth load image; the first atmospheric parameter information comprises longitude and latitude information, aerosol information and water vapor information;
the first processing device is used for receiving information of the first instrument and the earth observation load camera and obtaining aerosol information and water vapor information synchronously corresponding to each pixel in the earth load image through the longitude and latitude information;
the second processing device is used for determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle;
the third processing device is used for acquiring the apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera;
the fourth processing device is used for acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter under the condition that the earth load image does not contain cloud information; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity.
The system can effectively improve the contrast and definition of the remote sensing image obtained by processing, the color is more bright and real, and the details of the image are better presented so as to ensure the effect of the reflectivity of the acquired earth surface target object.
The construction, features and functions of the present application are described in detail in the embodiments illustrated in the drawings, which are only preferred embodiments of the present application, but the present application is not limited by the drawings, and all equivalent embodiments that can be modified or changed according to the idea of the present application are within the scope of the present application without departing from the spirit of the present application.
Claims (10)
1. A method for obtaining the reflectivity of a surface target object based on a remote sensing image is characterized by comprising the following steps:
synchronously acquiring first atmospheric parameter information and a ground load image through a first instrument and a ground load observation camera which are carried on the same satellite; the first atmospheric parameter information comprises longitude and latitude information, aerosol information and water vapor information;
aerosol information and water vapor information synchronously corresponding to all pixels in the ground load image are obtained through the longitude and latitude information;
determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle;
acquiring apparent radiance corresponding to each pixel according to the radiance scaling parameters of the earth observation load;
under the condition that the earth load image does not contain cloud information, acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity.
2. The method of claim 1, wherein the obtaining aerosol information and water vapor information synchronously corresponding to each pixel in the geo-referenced load image through the latitude and longitude information comprises:
according to the time information, matching a first atmospheric parameter with the same imaging time aiming at the ground load image, and obtaining first image information after the first atmospheric parameter is matched;
analyzing the first image pixel by pixel to obtain longitude and latitude information corresponding to each pixel of the ground load image;
and acquiring aerosol information and water vapor information matched with each pixel in the synchronous first atmospheric parameter information based on the longitude and latitude information.
3. The method of claim 2, wherein the obtaining aerosol information and water vapor information matched with each pixel in the synchronous first atmospheric parameter information based on the longitude and latitude information comprises:
and matching one or the combination of aerosol information and water vapor information in the first atmospheric parameter information to each pixel of the geo-referenced load image through an interpolation method based on the longitude and latitude information.
4. The method of claim 1, wherein obtaining the apparent radiance corresponding to each pixel according to the radiometric parameters of the earth observation load camera comprises:
acquiring radiometric calibration parameters of the earth observation load camera;
establishing a first relation among the radiometric calibration parameters, the gray value of each pixel and the apparent radiance;
and acquiring the apparent radiance corresponding to each pixel based on the first relation.
5. The method of any of claims 1-4, wherein the second atmospheric parameter comprises an ascending atmospheric transmittance T (θ)v) And the downstream atmospheric transmittance T (theta)s) Atmospheric range radiation LpathAtmospheric hemisphere albedo S;
acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter, and specifically comprising the following steps:
obtaining the surface comprehensive reflectivity by the following formula:
wherein: l is the apparent radiance; fsIs the wave band average out-of-atmosphere solar irradiance, relative to the corresponding wave band of the ground load image, thetasIs the zenith angle of the sun, thetavAnd observing the zenith angle.
6. The method of claim 5, wherein said determining a background reflectivity around said surface target object pixels comprises:
calculating atmospheric point diffusion function weight reflecting mutual influence between adjacent pixels and a target pixel according to the resolution of the earth observation load camera;
and determining the background reflectivity around each pixel in the earth surface target object based on the atmospheric point spread function weight and the earth surface comprehensive reflectivity of each pixel.
7. The method of claim 6, wherein the second atmospheric parameter comprises atmospheric diffuse transmittance, direct atmospheric transmittance;
the obtaining the reflectivity of the surface target object based on the second atmospheric parameter, the surface comprehensive reflectivity and the background reflectivity comprises:
determining a ratio of the atmospheric diffuse transmittance and the direct atmospheric transmittance as a first correction coefficient;
and correcting the comprehensive earth surface reflectivity of each pixel element of the earth load image by using a set relation so as to acquire the reflectivity of the earth surface target object, wherein the set relation is as follows:
ρt=[ρ1+q(ρ1-ρM)]·[1-(ρM-0.15)·S]
where ρ is1For the total reflectivity of the earth's surface, ptIn order to obtain the reflectivity of the ground surface target object after correction, S is the albedo of the atmospheric hemisphere, q is a first correction coefficient, rhoMIs the background reflectivity around the target pixel.
8. The method of claim 1, wherein the preset atmospheric correction look-up table comprises:
the sub lookup tables respectively correspond to the spectral bands of the earth observation load camera;
the construction process of the sub lookup table is as follows:
determining a spectral band, a spectral response function and an aerosol transmission model corresponding to the pre-constructed sub lookup table;
setting parameter items, wherein the parameter items comprise aerosol information, water vapor information, a solar zenith angle, an observation zenith angle and a relative azimuth angle;
calculating a result of the second atmospheric parameter as a function of one or a combination of the parameter terms based on the spectral band, the spectral response function, the aerosol transport model simulation;
and constructing the sub lookup table according to a simulation calculation result, the aerosol information, the water vapor information, the solar zenith angle, the observation zenith angle and the relative azimuth angle.
9. The method according to any one of claims 6-8, further comprising: in the case where the ground load image contains cloud information, then the apparent reflectance is obtained based on the apparent radiance.
10. A system for obtaining the reflectivity of a surface target object based on remote sensing images is characterized by comprising:
the system comprises a first instrument and an earth observation load camera which are carried on the same satellite, wherein the first instrument and the earth observation load camera synchronously acquire first atmospheric parameter information and an earth load image; the first atmospheric parameter information comprises longitude and latitude information, aerosol information and water vapor information;
the first processing device is used for receiving information of the first instrument and the earth observation load camera and obtaining aerosol information and water vapor information synchronously corresponding to each pixel in the earth load image through the longitude and latitude information;
the second processing device is used for determining a second atmospheric parameter corresponding to each pixel according to a preset atmospheric correction lookup table; wherein: the preset atmospheric correction lookup table is used for determining second atmospheric parameters corresponding to the pixels according to the dependence of the second atmospheric parameters on aerosol information, water vapor information, solar zenith angle, observation zenith angle and relative azimuth angle;
the third processing device is used for acquiring the apparent radiance corresponding to each pixel according to the radiometric calibration parameter of the earth observation load camera;
the fourth processing device is used for acquiring the comprehensive reflectivity of the earth surface according to the apparent radiance and the second atmospheric parameter under the condition that the earth load image does not contain cloud information; determining the background reflectivity around the surface target object pixel; and acquiring the reflectivity of the earth surface target object based on the second atmospheric parameter, the comprehensive reflectivity of the earth surface and the background reflectivity.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202110392194 | 2021-04-13 | ||
CN2021103921944 | 2021-04-13 |
Publications (1)
Publication Number | Publication Date |
---|---|
CN113218874A true CN113218874A (en) | 2021-08-06 |
Family
ID=77090244
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202110478899.8A Pending CN113218874A (en) | 2021-04-13 | 2021-04-30 | Method and system for obtaining surface target object reflectivity based on remote sensing image |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN113218874A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116309185A (en) * | 2023-05-12 | 2023-06-23 | 海南辐探遥感科技有限公司 | Water color satellite image land proximity effect correction algorithm based on lookup table |
CN117315411A (en) * | 2023-10-18 | 2023-12-29 | 自然资源部国土卫星遥感应用中心 | Simulation method for hyperspectral satellite image radiometric calibration data |
Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111415309A (en) * | 2020-03-19 | 2020-07-14 | 中国矿业大学(北京) | High-resolution remote sensing image atmospheric correction method based on minimum reflectivity method |
WO2021038621A1 (en) * | 2019-08-23 | 2021-03-04 | 三菱電機株式会社 | Image processing device and image processing method |
-
2021
- 2021-04-30 CN CN202110478899.8A patent/CN113218874A/en active Pending
Patent Citations (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2021038621A1 (en) * | 2019-08-23 | 2021-03-04 | 三菱電機株式会社 | Image processing device and image processing method |
CN111415309A (en) * | 2020-03-19 | 2020-07-14 | 中国矿业大学(北京) | High-resolution remote sensing image atmospheric correction method based on minimum reflectivity method |
Non-Patent Citations (16)
Title |
---|
傅俏燕等: "CBERS影像的业务化大气订正", 《国土资源遥感》, no. 1, pages 48 - 50 * |
冯学智等: "《遥感数字图像处理与应用》", 31 October 2011, 商务印书馆, pages: 76 - 77 * |
刘其悦等: "基于6S模型的HJ-1/CCD影像逐像元大气校正", 《黑龙江科技信息》 * |
刘其悦等: "基于6S模型的HJ-1/CCD影像逐像元大气校正", 《黑龙江科技信息》, no. 31, 5 November 2010 (2010-11-05), pages 11 * |
吴黎: "《MODIS遥感信息处理方法及应用》", 30 June 2017, 哈尔滨工程大学出版社, pages: 56 * |
周守东 等: "陆地晴空水汽柱含量的MODIS反演方法研究", 《海南师范大学学报(自然科学版)》 * |
周守东 等: "陆地晴空水汽柱含量的MODIS反演方法研究", 《海南师范大学学报(自然科学版)》, vol. 30, no. 1, 31 March 2017 (2017-03-31), pages 47 - 54 * |
明艳芳等: "《高光谱特征参数协同的矿物类型遥感识别方法》", 中国矿业大学出版社, pages: 49 * |
曹红业等: "基于辐射传输模型的高分二号影像大气校正方法研究", 《红外技术》, vol. 42, no. 6, pages 534 - 540 * |
李孟凡等: "便携式多通道辐射参考光源的设计与测试", 《光学学报》, vol. 40, no. 20, pages 1 - 7 * |
李正强等: "光学遥感卫星大气校正研究综述", 《南京信息工程大学学报(自然科学版)》, vol. 10, no. 1, pages 6 - 15 * |
汤兴等: "高分一号卫星多光谱遥感图像邻近效应校正研究", 《光学学报》, no. 02, 29 February 2016 (2016-02-29), pages 1 - 4 * |
王艳: "基于多元数据的洪灾区域快速提取方法研究", 《中国知网》, pages 18 * |
舒敏: "高分辨率遥感影像薄云去除算法研究", 《中国知网》, pages 30 - 31 * |
赵少帅等: "面向气溶胶反演的高分四号影像云检测", 《遥感信息》, vol. 34, no. 5, pages 81 - 87 * |
边福强等: "高光谱遥感大气辐射校正技术的研究", 《大气与环境光学学报》, vol. 13, no. 1, pages 65 - 73 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116309185A (en) * | 2023-05-12 | 2023-06-23 | 海南辐探遥感科技有限公司 | Water color satellite image land proximity effect correction algorithm based on lookup table |
CN117315411A (en) * | 2023-10-18 | 2023-12-29 | 自然资源部国土卫星遥感应用中心 | Simulation method for hyperspectral satellite image radiometric calibration data |
CN117315411B (en) * | 2023-10-18 | 2024-04-09 | 自然资源部国土卫星遥感应用中心 | Simulation method for hyperspectral satellite image radiometric calibration data |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN111795936B (en) | Multispectral remote sensing image atmospheric correction system and method based on lookup table and storage medium | |
US8073279B2 (en) | Automated atmospheric characterization of remotely sensed multi-spectral imagery | |
Teillet | Image correction for radiometric effects in remote sensing | |
CN111368817B (en) | Method and system for quantitatively evaluating thermal effect based on earth surface type | |
JP2008527766A (en) | Method and apparatus for improving digital images | |
CN108256186B (en) | Pixel-by-pixel atmospheric correction method for online calculation lookup table | |
KR101702187B1 (en) | Device and method for calibration of high resolution electro optical satellite | |
CN109325973B (en) | Urban river network area water body atmosphere correction method | |
CN110907364B (en) | Optical remote sensing image atmospheric correction method and device based on ephemeris parameters | |
Bruce et al. | Pre-processing methodology for application to Landsat TM/ETM+ imagery of the wet tropics | |
CN113218874A (en) | Method and system for obtaining surface target object reflectivity based on remote sensing image | |
CN113970376B (en) | Satellite infrared load calibration method based on marine region re-analysis data | |
CN116519557B (en) | Aerosol optical thickness inversion method | |
JP6964834B2 (en) | Image processing device and image processing method | |
CN111415309A (en) | High-resolution remote sensing image atmospheric correction method based on minimum reflectivity method | |
CN109919250B (en) | Soil moisture-considered evapotranspiration space-time characteristic fusion method and device | |
Maciel et al. | Evaluation of ACOLITE atmospheric correction methods for Landsat-8 and Sentinel-2 in the Río de la Plata turbid coastal waters | |
CN114581349A (en) | Visible light image and infrared image fusion method based on radiation characteristic inversion | |
CN110689505B (en) | Scene-based satellite-borne remote sensing instrument self-adaptive correction method and system | |
CN115507959A (en) | Infrared radiation characteristic analysis method for target detection | |
CN109945969B (en) | Method and device for determining earth radiation balance based on meteorological satellite observation | |
Li et al. | An improved on-orbit relative radiometric calibration method for agile high-resolution optical remote-sensing satellites with sensor geometric distortion | |
Schläpfer et al. | Correction of shadowing in imaging spectroscopy data by quantification of the proportion of diffuse illumination | |
CN111595781B (en) | Surface fitting ground hyperspectral image reflectivity correction method | |
CN110702228B (en) | Edge radiation correction method for aviation hyperspectral image |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination |