CN109684712B - BRDF (bidirectional reflectance distribution function) model creating method and device, electronic equipment and storage medium - Google Patents
BRDF (bidirectional reflectance distribution function) model creating method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a method and a device for creating a BRDF (bidirectional reflectance distribution function) model, electronic equipment and a storage medium, belonging to the technical field of satellite remote sensing, wherein the method comprises the following steps: acquiring each measured data of a current data test scene; establishing a BRDF initial model based on correspondence of the radiance of each object surface reflected along with a corresponding incident angle to the equivalent specular reflectance of a micro surface element at a corresponding inclination angle according to each measured data; and correcting the created BRDF initial model to obtain a corrected BRDF model. The scheme of the invention can realize that: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
Description
Technical Field
The embodiment of the invention relates to the technical field of satellite remote sensing, in particular to a method and a device for creating a BRDF (bidirectional reflectance distribution function) model, electronic equipment and a storage medium.
Background
The BRDF (Bidirectional reflection Distribution Function) is used to define the ratio of the intensity of reflected radiation (radiance) in a given direction to the intensity of radiation (irradiance) in the incident direction. The model describing how the incident light rays in different directions are distributed in each emergent direction after being reflected by a specific surface is the BRDF model corresponding to the surface. Since BRDF is difficult to measure on a satellite, BRF (Bi-directional reflectivity Factor) is generally used instead of BRDF. It is defined as: the ratio of the brightness of the reflected radiation in a certain direction to the brightness of the reflected radiation in that direction of an ideal diffuse reflector under the same irradiance conditions.
The BRDF model plays an important role in the remote sensing of the solar reflection band satellite. The method is a key parameter of remote sensor radiometric calibration, and is essential in links such as on-satellite reference plate calibration, site substitution calibration, DCC calibration, lunar calibration and the like. The method is a key parameter for inverting the remote sensing product of the terrestrial surface albedo, and the derived remote sensing products such as the incident total short wave energy, the soil humidity, the vegetation coverage, the desertification, the snowfall distribution and the like are closely related to the production and life of human beings.
The BRDF models that exist so far can be classified into three types, namely a physical model (Pinty and Verstraete, 1991), an empirical model (Walthal, 1985) and a semi-empirical model (Hapke, 1981, 1986, rahman,1993, roujean,1992, ross-li, 1995) according to principles; they can also be classified by structure into linear nucleus drive (Walthal, roujean, ross-li) and nonlinear nucleus drive (Hapke, rahman, pinty and Verstraete). The linear kernel driving model is commonly used for developing remote sensing products due to the advantage of the computing speed, and a Ross-li BRDF model is selected for the MODIS MCD43 product. For 20 years, the BRDF model is newly reported. The main research only focuses on the aspects of correcting the nuclear structure of the existing model, improving the inversion accuracy (Jiao z.t., 2016) of the existing model at a hot spot, or establishing a customized BRDF model (Bhatt r., 2017) with higher accuracy than a universal model aiming at a specific ground object type. Existing widely used BRDF models, such as Hapke, roujean, ross-li, and their modified versions, do not solve the problem of low model accuracy under large observation geometries (solar zenith angles and/or satellite zenith angles greater than 80 degrees) (Sgrahler, a.h., 1999). The problem directly restricts the precision level of the remote sensing quantification application of the solar reflection band.
How to provide a new method for creating the BRDF model, and the BRDF model obtained by creation has higher test precision on a test target object, which is a technical problem to be solved.
Disclosure of Invention
The embodiment of the invention aims to provide a method and a device for creating a BRDF (bidirectional reflectance distribution function) model, electronic equipment and a storage medium, which are used for solving the problem that the existing BRDF model has low test precision on a test target object.
In order to achieve the above object, an embodiment of the present invention provides the following:
in a first aspect of embodiments of the present invention, there is provided a method of creating a BRDF model, the method comprising: acquiring each measured data of a current data test scene; establishing a BRDF initial model based on the equivalent specular reflectance ratio corresponding the radiance reflected by the surface of each object along with the corresponding incident angle to the micro surface element at the corresponding inclination angle according to each measured data; and correcting the created BRDF initial model to obtain a corrected BRDF model.
In another embodiment of the present invention, the modified BRDF model can also be applied to at least one of the following test target objects: various surface feature type target objects, lunar surface target objects and deep convection cloud target objects.
In yet another embodiment of the present invention, the modified BRDF model is a linear kernel-driven model.
In a further embodiment of the present invention, the driving kernels in the linear kernel driving model are respectively a cosine function of an angle between a normal of the tiny surface element and a normal of the horizontal surface element and an angle between the observation geometry and the normal of the tiny surface element, wherein a calculation formula corresponding to the linear kernel driving model is as follows:
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) Wherein BRF is a bidirectional reflectance factor, M z Is the angle of the normal of the micro surface element relative to the normal of the horizontal ground surface; m is a group of i Is the angle of the incident direction with respect to the normal of the tiny surface element, a 1-4 Are multiple linear regression coefficients.
In a second aspect of an embodiment of the present invention, there is provided an apparatus for creating a BRDF model, the apparatus comprising: the acquisition module acquires each measured data of the current data test scene; the establishing module is used for establishing a BRDF initial model based on the fact that the radiance reflected by the surface of each object along with the corresponding incident angle corresponds to the equivalent specular reflectance of the micro surface element at the corresponding inclination angle according to each measured data acquired by the acquiring module; and the correcting module is used for correcting the BRDF initial model created by the created model to obtain a corrected BRDF model.
In another embodiment of the present invention, the modified BRDF model modified by the modification module can be further applied to at least one of the following test target objects: various surface feature type target objects, lunar surface target objects and deep convection cloud target objects.
In another embodiment of the present invention, the modified BRDF model modified by the modification module is a linear kernel-driven model.
In another embodiment of the present invention, the driving kernels in the linear kernel driving model are respectively a cosine function of an angle between a normal of a micro surface element and a normal of a horizontal surface element and an angle between an observation geometry and the normal of the micro surface element, wherein a calculation formula corresponding to the linear kernel driving model is as follows:
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) Wherein, BRF is a bidirectional reflectivity factor, mz is an included angle of the normal line of the tiny surface element relative to the normal line of the horizontal ground surface; mi is the angle of incidence direction with respect to the normal of the tiny surface element, a 1-4 Are multiple linear regression coefficients.
In a third aspect of embodiments of the present invention, an electronic device is provided, which includes a memory and a processor, the processor and the memory completing communication with each other through a bus; the memory stores program instructions executable by the processor, which when called by the processor are capable of performing the method as described above.
In a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided, characterized in that a computer program is stored thereon, which computer program, when being executed by a processor, realizes the steps of the method as described above.
The embodiment of the invention has the following advantages: the BRDF model creating method, the BRDF model creating device, the electronic equipment and the storage medium provided by the embodiment of the invention can realize the following steps: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It should be apparent that the drawings in the following description are merely exemplary, and that other embodiments can be derived from the drawings provided by those of ordinary skill in the art without inventive effort.
Fig. 1 is a schematic flow chart of a method for creating a BRDF model according to embodiment 1 of the present invention;
FIG. 2 is a schematic diagram of a prior art precision test of the Ross-li BRDF model;
fig. 3 is a schematic diagram of a michike BRDF model for detecting accuracy of the michike BRDF model using measured data of the dunghuang gobi field in embodiment 1 of the present invention under a small observation geometry;
FIG. 4 is another schematic diagram of the Mike BRDF model tested by Dunhuang Gobi field measured data in the embodiment 1 of the present invention;
FIG. 5 is a schematic diagram of the accuracy of the Mike BRDF model for testing different ground feature types by using the MODIS MCD43 product in example 1 of the present invention;
fig. 6 is a schematic structural diagram of a device for creating a BRDF model according to embodiment 2 of the present invention.
In the figure: 601-an obtaining module; 602-a creation module; 603-correction module.
Detailed Description
The present invention is described in terms of particular embodiments, other advantages and features of the invention will become apparent to those skilled in the art from the following disclosure, and it is to be understood that the described embodiments are merely exemplary of the invention and that it is not intended to limit the invention to the particular embodiments disclosed. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
According to embodiment 1 of the present invention, a method for creating a BRDF model is provided, and as shown in fig. 1, a flow diagram of the method for creating a BRDF model provided in embodiment 1 of the present invention is provided. The method at least comprises the following steps:
s101, acquiring each measured data of a current data test scene;
s102, establishing a BRDF initial model based on correspondence of radiance reflected by the surface of each object along with a corresponding incident angle to equivalent specular reflectance of a micro surface element at a corresponding inclination angle according to each measured data;
s103, correcting the created BRDF initial model to obtain a corrected BRDF model; thus, by the scheme provided by embodiment 1 of the present invention, it is possible to: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
In an alternative example, the modified BRDF model can also be applied to at least one of the following test target objects: various surface feature type target objects, lunar surface target objects and deep convection cloud target objects.
In an alternative example, the modified BRDF model is a linear kernel-driven model.
In an alternative example, the driving kernels in the linear kernel driving model are respectively the angle between the normal of the infinitesimal element and the normal of the horizontal surface and the cosine function of the angle between the observation geometry and the normal of the infinitesimal element, wherein the linear kernel driving model has the following corresponding calculation formula:
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) Wherein BRF is a bidirectional reflectance factor, M z Is the angle of the normal of the micro surface element relative to the normal of the horizontal ground surface; mi is the angle of incidence direction with respect to the normal of the tiny surface element, a 1-4 Are multiple linear regression coefficients.
In practical applications, BRFs in other observation geometries are calculated by the following two steps. The method comprises the following specific steps:
step 1: regression model coefficients using existing data
Collecting BRF data of target surfaces with different observation geometries as much as possible, and calculating an included angle M between the normal line of the tiny surface element and the normal line of the target surface according to the existing data observation geometries z Angle M of incidence direction with respect to normal of micro surface element i Then fitting the multiple linear regression coefficient a by using a least square formula (1～4) ；
Step 2: calculating BRF under other observation geometries;
calculating M corresponding to other observation geometries z And M i According to the following formula
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) And step 1
Coefficient a obtained by regression (1～4) And calculating BRF under other observation geometries.
FIG. 2 is a schematic diagram of the precision test of the Ross-li BRDF model in the prior art; fig. 3 is a schematic diagram of the method for detecting the accuracy of the michike BRDF model using the measured data of the dunghuang gobi field in embodiment 1 of the present invention, and the michike BRDF model under the small observation geometry. Comparing fig. 2 and fig. 3, it can be known that the precision of the michike BRDF model is tested by using the measured data of the dunhuang gobi field, and the precision of the michike BRDF model under the small observation geometry is equivalent to that of the international advanced Ross-li BRDF model.
It should be noted that the modified BRDF model in embodiment 1 of the present invention is a completely new BRDF model that is suitable for various surface feature types, has a model accuracy equivalent to that of the mainstream BRDF model in a small observation geometry, and is improved greatly in a large observation geometry.
Fig. 4 is another schematic diagram of the method for verifying the accuracy of the michike BRDF model using the measured data of the dunghuang gobi field in embodiment 1 of the present invention.
As shown in fig. 4, it can be seen that: the precision of the Mike BRDF model is checked by using measured data of Dunhuang Gobi field, the BRF output calculated by Ross-li BRDF under large observation geometry is an abnormal value larger than 2, and when the solar zenith angle is close to 90 degrees, a value close to infinity can be output due to the algorithm defect of the model. And the BRF calculated by the Micoke BRDF model is always in a reasonable interval of 0.4-0.5.
Fig. 5 is a schematic diagram of the accuracy of the michoke BRDF model under different ground feature types tested by the MODIS MCD43 product in example 1 of the present invention. As shown in FIG. 5, the abscissa is the BRF calculated by the Micoke BRDF model, and the ordinate is the BRF calculated by the Ross-Li BRDF model. As can be seen from the data in fig. 5: the correlation coefficient between the BRF calculated by the Micoke BRDF model under the small observation geometry and the BRF corresponding to the product is as high as 0.999.
In summary, the method for creating the BRDF model provided in embodiment 1 of the present invention has the following beneficial effects: the method for creating the BRDF model is provided, and the BRDF model created by the method has higher test precision on the test target object.
Example 2
According to embodiment 2 of the present invention, a device for creating a BRDF is further provided, as shown in fig. 6, which is a schematic structural diagram of the device for creating a BRDF provided in embodiment 2 of the present invention.
The device for creating the BRDF provided by embodiment 2 of the present invention includes an obtaining module 601, a creating module 602, and a modifying module 603.
Specifically, the obtaining module 601 obtains each measured data of the current data test scenario;
a creating module 602, configured to create a BRDF initial model based on correspondence of radiance reflected by the surface of each object along with a corresponding incident angle to an equivalent specular reflectance of a micro surface element at a corresponding inclination angle, with reference to each measured data acquired by the acquiring module 601;
the correcting module 603 corrects the BRDF initial model created by the created model to obtain a corrected BRDF model; thus, with the apparatus for creating a BRDF provided in embodiment 2 of the present invention, it is possible to: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
In an optional example, the modified BRDF model modified by the modification module 603 can be further applied to at least one of the following test target objects: various surface feature type target objects, lunar surface target objects and deep convection cloud target objects.
In an alternative example, the modified BRDF model modified by the modification module 603 is a linear kernel-driven model.
In an alternative example, the driving kernels in the linear kernel driving model are respectively the angle between the normal of the tiny surface element and the normal of the horizontal surface element and the cosine function of the angle between the observation geometry and the normal of the tiny surface element, wherein the linear kernel driving model has the following corresponding calculation formula:
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) Wherein BRF is a bidirectional reflectance factor, M z Is the angle of the normal of the micro surface element relative to the normal of the horizontal ground surface; mi is the angle of incidence direction with respect to the normal of the tiny surface element, a 1-4 Are multiple linear regression coefficients.
For parts of the scheme provided in embodiment 2 of the present invention that are the same as or similar to parts of the scheme provided in embodiment 1 of the present invention, please refer to the description of corresponding parts in embodiment 1 of the present invention, and further details are not described herein.
In summary, the apparatus for creating a BRDF provided in embodiment 2 of the present invention has the following beneficial effects: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
Example 3
According to embodiment 3 of the present invention, there is also provided an electronic apparatus including: the processor and the memory are communicated with each other through a bus; the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform a method comprising: acquiring each measured data of a current data test scene; establishing a BRDF initial model based on correspondence of the radiance of each object surface reflected along with a corresponding incident angle to the equivalent specular reflectance of a micro surface element at a corresponding inclination angle according to each measured data; and correcting the created BRDF initial model to obtain a corrected BRDF model.
For parts of the scheme provided in embodiment 3 of the present invention that are the same as or similar to parts of the scheme provided in embodiment 1 of the present invention, please refer to the description of corresponding parts in embodiment 1 of the present invention, and further details are not described herein.
In summary, the electronic device provided in embodiment 3 of the present invention has the following beneficial effects: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
Example 4
According to embodiment 4 of the present invention, there is also provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the method of: acquiring each measured data of a current data test scene; establishing a BRDF initial model based on correspondence of the radiance of each object surface reflected along with a corresponding incident angle to the equivalent specular reflectance of a micro surface element at a corresponding inclination angle according to each measured data; and correcting the created BRDF initial model to obtain a corrected BRDF model.
For parts of the same or similar contents in the scheme provided in embodiment 4 of the present invention and the scheme provided in embodiment 1 of the present invention, please refer to the description of the corresponding parts in embodiment 1 of the present invention, and details are not repeated herein.
In summary, the computer-readable storage medium provided in embodiment 4 of the present invention has the following beneficial effects: the method for creating the BRDF model is novel, and the created BRDF model has higher test precision on the test target object.
Although the invention has been described in detail with respect to the general description and the specific embodiments, it will be apparent to those skilled in the art that modifications and improvements may be made based on the invention. Accordingly, such modifications and improvements are intended to be within the scope of the invention as claimed.
Claims (4)
1. A method for creating a BRDF model is characterized by comprising the following steps:
acquiring each measured data of a current data test scene;
establishing a BRDF initial model based on correspondence of the radiance of each object surface reflected along with a corresponding incident angle to the equivalent specular reflectance of a micro surface element at a corresponding inclination angle according to each measured data;
correcting the created BRDF initial model to obtain a corrected BRDF model;
the modified BRDF model can also be applied to at least one of the following test target objects: various surface feature type target objects, lunar surface target objects and deep convection cloud target objects;
the modified BRDF model is a linear kernel driving model;
the driving kernels in the linear kernel driving model are respectively an included angle of a normal line of the tiny surface element relative to a normal line of a horizontal ground surface and a cosine function of an included angle of the observation geometry and the normal line of the tiny surface element, wherein a calculation formula corresponding to the linear kernel driving model is as follows:
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) Wherein BRF is a bidirectional reflectance factor, M z Is the angle of the normal of the micro surface element relative to the normal of the horizontal ground surface; mi is the angle of incidence direction with respect to the normal of the tiny surface element, a 1- a 4 Are multiple linear regression coefficients.
2. An apparatus for creating a BRDF, comprising:
the acquisition module acquires each measured data of the current data test scene;
the establishing module is used for establishing a BRDF initial model based on the fact that the radiance reflected by the surface of each object along with the corresponding incident angle corresponds to the equivalent specular reflectance of the micro surface element at the corresponding inclination angle according to each measured data acquired by the acquiring module;
the correction module is used for correcting the BRDF initial model created by the creation module to obtain a corrected BRDF model;
the modified BRDF model modified by the modification module can be applied to at least one of the following test target objects: various surface feature type target objects, lunar surface target objects and deep convection cloud target objects on the surface;
the modified BRDF model obtained by the modification of the modification module is a linear kernel driving model;
the driving kernels in the linear kernel driving model are respectively an included angle of a normal line of the tiny surface element relative to a normal line of a horizontal ground surface and a cosine function of an included angle of the observation geometry and the normal line of the tiny surface element, wherein a calculation formula corresponding to the linear kernel driving model is as follows:
BRF＝a 1 +a 2 *cos(M i )*(1+cos(M z ))+a 3 *cos 2 (M z )+a 4 *cos 2 (M i ) Wherein BRF is a bidirectional reflectance factor, M z Is the angle of the normal of the micro surface element relative to the normal of the horizontal ground surface; mi is the angle of incidence direction with respect to the normal of the tiny surface element, a 1- a 4 Are multiple linear regression coefficients.
3. An electronic device, comprising:
the processor and the memory are communicated with each other through a bus; the memory stores program instructions executable by the processor, the processor invoking the program instructions to perform the method of claim 1.
4. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method as claimed in claim 1.
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