CN116312899B - Material surface BRDF parameter fitting method and system based on laser radar imaging - Google Patents
Material surface BRDF parameter fitting method and system based on laser radar imaging Download PDFInfo
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Abstract
The invention relates to the technical field of laser radar imaging material characteristic analysis, and provides a material surface BRDF parameter fitting method and system based on laser radar imaging. The method comprises the following steps: measuring BRDF measured values of the measured material at all angles by using a BRDF measuring system; initializing a data value interval of BRDF model parameters; randomly generating initial values of BRDF model parameters, adopting a BBO algorithm to fit the initial values of the BRDF model parameters to obtain fitted values, and selecting the first 50% of fitted values to input into a FireFly algorithm for secondary fitting; repeating the steps, and selecting the BRDF fitting value corresponding to the minimum objective function value as the optimal BRDF fitting value; and outputting the BRDF model parameter fitting value corresponding to the optimal BRDF fitting value as a fitting result. The invention solves the problems of low convergence speed, weak local searching capability and avoidance of sinking into local optimal solution of the BRDF parameter fitting method.
Description
Technical Field
The invention relates to the technical field of laser radar imaging material characteristic analysis, in particular to a material surface BRDF parameter fitting method and system based on laser radar imaging.
Background
The Bidirectional Reflectance Distribution Function (BRDF) is a physical quantity for representing the spatial reflectance characteristics of a target surface, and is widely applied to the fields of computer graphics, remote sensing, laser radar and the like. The parameter BRDF model well solves the problem that the surface parameters of the material need to be acquired in advance in the analysis theory, has good fitting effect on the composite material, and is widely researched and used. Fitting determination of BRDF model parameters is a difficult problem faced by all material property researches and is also a core problem of determination of the whole material reflection model. The BRDF model parameter fitting has the characteristics of large data volume, multiple unknown parameters and the like, so that an efficient and accurate fitting scheme is very important.
However, at present, the relevant research on the characteristics of the BRDF materials is carried out by the domestic partial scholars. Wu Zhensen the undetermined parameters in the parameter BRDF model are fitted by adopting a Genetic Algorithm (GA), and the GA algorithm has strong global searching capability, but has the disadvantages of low convergence speed, weak local searching capability and long running time. Wang Qianqian proposes a hybrid artificial bee colony algorithm, which improves the local searching capability of the algorithm and improves the algorithm efficiency, but the algorithm is easy to fall into a local optimal solution.
Disclosure of Invention
In view of the above, the invention provides a method and a system for fitting BRDF parameters on the surface of a material based on laser radar imaging, which are used for solving the technical problems of low convergence speed, weak local searching capability, long running time and easiness in sinking into a local optimal solution in the prior art.
In a first aspect, the invention provides a method for fitting BRDF parameters on a material surface based on laser radar imaging, which comprises the following steps:
s1, measuring BRDF measured values of a measured material at various angles by using a BRDF measuring system;
s2, initializing a data value interval of BRDF model parameters, wherein the BRDF model parameters comprise specular reflection coefficients of materialsDiffuse reflectance->Roughness->Refractive index +.>And->；
S3, generating initial values of the BRDF model parameters randomly according to the data value interval of the BRDF model parameters, and initializing a BBO-FireFly algorithm to obtain initialization parameters of the BBO-FireFly algorithm;
s4, based on the initialization parameters of the BBO-FireFly algorithm, fitting the initial values of the BRDF model parameters by adopting the BBO algorithm to obtain a plurality of BRDF model parameter fitting values, selecting the first 50% of the BRDF model parameter fitting values, inputting the BRDF model parameter fitting values into the FireFly algorithm for secondary fitting, and obtaining a plurality of BRDF model parameter optimization fitting values;
s5, substituting the BRDF model parameter optimization fitting values into the BRDF model to obtain a plurality of BRDF fitting values, and substituting the BRDF fitting values into the objective function to obtain a plurality of objective function values;
s6, repeating the steps S3-S5 for a preset number of times, finding out the minimum objective function value from all the obtained objective function values, taking the BRDF fitting value corresponding to the minimum objective function value as an optimal BRDF fitting value, and then obtaining a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value based on the BRDF model, and outputting the BRDF model parameter fitting value as a fitting result.
Further, the step S1 includes:
s11, initializing a BRDF measuring system, setting the range of values of an incident zenith angle and an observation zenith angle to be between-20 degrees and 90 degrees, and setting the range of values of an incident azimuth angle and an observation azimuth angle to be between 0 degrees and 360 degrees;
s12, setting an incident azimuth angle and an observation azimuth angle as constants by using the BRDF measuring system, and measuring with the interval of 5 DEG of each change of the observation zenith angle under the incident conditions that the incident zenith angle is 15 DEG, 30 DEG, 45 DEG and 60 DEG respectively to obtain BRDF measuring values of the measured material under each angle.
Further, the step S2 includes:
s21, establishing a BRDF model;
s22, substituting the initialized BRDF model parameter values into the BRDF model to obtain the data value intervals of the BRDF model parameters under each angle.
Further, the BRDF model formula is as follows:
，
wherein,,represents the fitting value of BRDF,/>Representing specular reflection coefficient, +.>Representing the coefficient of diffuse reflection,indicating material roughness, ++>And->Index of refraction>A shadow mask function representing a model; />Representing incident zenith angle>Representing the reflected zenith angle>Representing micro-primitivesThe angle between the normal N and the z-axis, +.>Representing the angle of incidence of the local coordinate system on the micro-facet.
Further, the step S3 includes:
s31, according to the data value interval of the BRDF model parameters, generating BRDF model parameter initial values with set groups at random;
s32, initializing a BBO-FireFly algorithm to obtain initialization parameters of the BBO-FireFly algorithm, wherein the initialization parameters comprise BBO algorithm parameters and FireFly algorithm parameters, and the BBO algorithm parameters comprise habitat number, population mobility, population migration rate, position mutation and mutation coefficients; the FireFly algorithm parameters comprise FireFly numbers, attractions among fireflies, position mutation and mutation coefficients.
Further, the step S5 includes:
s51, substituting the BRDF model parameter optimization fitting values into the BRDF model respectively to obtain a plurality of BRDF fitting values;
s52, substituting the BRDF fitting values into the objective function respectively to obtain a plurality of objective function values.
Further, the step S6 includes:
s61, repeating the steps S3-S5 to finish the circulation of preset circulation times, and obtaining a plurality of objective function values;
s62, comparing the magnitudes of the objective function values, selecting a BRDF fitting value corresponding to the minimum objective function value as an optimal BRDF fitting value, obtaining a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value based on a BRDF model, and outputting the BRDF model parameter fitting value as a fitting result.
Further, the formula of the objective function is as follows:
，
wherein,,fitting values for BRDF>For BRDF measurements, n is the number of measured data sets.
In a second aspect, the present invention provides a laser radar imaging-based material surface BRDF parameter fitting system, comprising:
the laser light source (1), the controller (2), the electric turntable (3), the detector (4) and the processor (5), wherein the electric turntable (3) is provided with two rotating arms,
the electric turntable (3) respectively controls the rotation of the laser light source (1) and the detector (4) by utilizing two rotating arms under the control of the controller (2) to measure BRDF values of the measured material at all angles;
the processor (5) is configured to perform the BRDF parameter fitting method of a material surface according to any one of claims 1-8.
Compared with the prior art, the invention has the beneficial effects that:
1. the model parameters obtained by adopting the BBO-FireFly algorithm are better matched with experimental data, so that the fitting speed and the fitting precision are both greatly improved, and the model parameters have better performance;
2. the method of the invention overcomes the problems of low convergence speed, weak local searching capability and long running time;
3. the method of the invention avoids the problem of sinking into a local optimal solution;
4. the method improves the efficiency and the measurement precision of the system.
Drawings
In order to more clearly illustrate the technical solutions of the present invention, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for fitting BRDF parameters on a material surface based on laser radar imaging provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of a method for fitting BRDF parameters on a material surface based on laser radar imaging provided by the embodiment of the invention;
fig. 3 is a schematic diagram of BRDF model parameters provided by an embodiment of the invention, where,for incident zenith angle>For reflecting zenith angle>Is the angle between the micro-surface element normal N and the z-axis, < ->Is the angle of incidence of the local coordinate system on the micro-bin;
FIG. 4 is a schematic diagram of the results of BRDF fitting values and measurement values for aluminum plates provided by the examples of the invention;
FIG. 5 is a schematic diagram of the results of the gold foil BRDF fitting values and measurement values provided by the embodiments of the invention;
fig. 6 is a block diagram of a material surface BRDF parameter fitting system based on laser radar imaging, wherein the system comprises a 1-laser light source, a 2-electric turntable controller, a 3-electric turntable, a 4-detector and a 5-processor.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as the particular system architecture, techniques, etc., in order to provide a thorough understanding of the embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
The invention relates to a material surface BRDF parameter fitting method based on laser radar imaging, which is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the BRDF model parameter fitting method includes:
s1, measuring BRDF measured values of a measured material at various angles by using a BRDF measuring system, wherein BBO is fully spliced into Biogeography-based optimization, which represents a biological geography optimization algorithm, BRDF is fully spliced into Bidirectional Reflectance Distribution FunctionBRDF abbreviations, which represent a bidirectional reflectance distribution function, and BRDF model parameters comprise specular reflectance coefficients of the materialDiffuse reflectance->Roughness of material>Refractive index parameter of material->And->；
The S1 comprises the following steps:
s11, initializing a BRDF measuring system, setting the range of values of an incident zenith angle and an observation zenith angle to be between-20 degrees and 90 degrees, and setting the range of values of an incident azimuth angle and an observation azimuth angle to be between 0 degrees and 360 degrees;
s12, setting an incident azimuth angle and an observation azimuth angle as constants by using the BRDF measuring system, and measuring with the interval of 5 DEG of each change of the observation zenith angle under the incident conditions that the incident zenith angle is 15 DEG, 30 DEG, 45 DEG and 60 DEG respectively to obtain BRDF measuring values of the measured material under each angle.
Initializing a BRDF measuring system, adopting a TBR200 electric rotating sliding table, performing oxidation treatment on a black anode, marking a two-phase stepping motor, sequentially placing samples of an aluminum plate and a gold foil on a horizontal platform, controlling the rotation angle of a light source arm, and changing the incident angle of a laser light source, wherein the incident angles are 15 degrees, 30 degrees, 45 degrees and 60 degrees respectively; the detector collecting the in-plane reflected beam automatically rotates around the motor 2, making measurements at 5 deg. intervals of each change, completing the measurement of the data.
S2, initializing a data value interval of BRDF model parameters, wherein the BRDF model parameters comprise specular reflection coefficients, diffuse reflection coefficients, roughness and refractive index coefficients of materials;
the step S2 comprises the following steps:
s21, establishing a BRDF model;
the BRDF model formula is as follows:
，
wherein,,represents the fitting value of BRDF,/>Representing specular reflection coefficient, +.>Representing the coefficient of diffuse reflection,indicating material roughness, ++>And->Index of refraction>A shadow mask function representing a model; />Representing incident zenith angle>Representing the reflected zenith angle>Representing the angle between the micro-surface element normal N and the z-axis,/->Representing the angle of incidence of the local coordinate system on the micro-facet. />And->Expressed as the following formula:
（1）
（2）
wherein,,indicating the azimuth angle of incidence +.>Indicating the azimuth angle of reflection, +.>Representing incident angle, ++>Indicating the scattering angle.
S22, substituting the initialized BRDF model parameter values into the BRDF model to obtain the data value intervals of the BRDF model parameters under each angle.
S3, generating initial values of the BRDF model parameters randomly according to the data value interval of the BRDF model parameters, and initializing a BBO-FireFly algorithm to obtain initialization parameters of the BBO-FireFly algorithm;
the step S3 comprises the following steps:
s31, according to the data value interval of the BRDF model parameters, generating BRDF model parameter initial values with set groups at random;
s32, initializing a BBO-FireFly algorithm to obtain initialization parameters of the BBO-FireFly algorithm, wherein the initialization parameters comprise BBO algorithm parameters and FireFly algorithm parameters, and the BBO algorithm parameters comprise habitat number, population mobility, population migration rate, position mutation and mutation coefficients; the FireFly algorithm parameters comprise FireFly numbers, attractions among fireflies, position mutation and mutation coefficients.
Initializing and generating a corresponding number of habitats according to the number of habitats set by the BBO-FireFly algorithm, randomly generating own positions of each habitat, initializing the initial position of a FireFly, and initializing parameters of the BBO-FireFly algorithm based on the initial position of the initial FireFly to obtain the initialization parameters of the BBO-FireFly algorithm.
S4, based on the initialization parameters of the BBO-FireFly algorithm, fitting the initial values of the BRDF model parameters by adopting the BBO algorithm to obtain a plurality of BRDF model parameter fitting values, selecting the first 50% of the BRDF model parameter fitting values, and inputting the BRDF model parameter fitting values into the FireFly algorithm to perform secondary fitting to obtain a plurality of BRDF model parameter fitting values;
the result of the BBO algorithm is a fitting value of the BRDF model parameter, and the result of the firefly algorithm is the fitting value of the BRDF model parameter after secondary fitting;
s5, substituting the BRDF model parameter optimization fitting values into the BRDF model to obtain a plurality of BRDF fitting values, and substituting the BRDF fitting values into the objective function to obtain a plurality of objective function values;
and after the result of the FireFly algorithm, namely the secondary fitting, the obtained fitting value of the BRDF model parameter represents the BBO-FireFly algorithm to complete the operation of a primary mixing algorithm, the fitting value of the current BRDF model parameter is obtained, the fitting value of the current BRDF model parameter is substituted into the BRDF model to obtain the BRDF fitting value, and the BRDF fitting value is substituted into the objective function, so that the corresponding objective function value is calculated.
The step S5 comprises the following steps:
s51, substituting the BRDF model parameter optimization fitting values into the BRDF model respectively to obtain a plurality of BRDF fitting values;
s52, substituting the BRDF fitting values into the objective function respectively to obtain a plurality of objective function values.
Fig. 4 is a schematic diagram of the results of BRDF fitting values and measured values for aluminum plates provided by the examples of the present invention.
Fig. 5 is a schematic diagram of the results of the BRDF fitting values and measured values of the gold foil provided by the embodiment of the invention.
S6, repeating the steps S3-S5 for a preset number of times, finding out the minimum objective function value from all the obtained objective function values, taking the BRDF fitting value corresponding to the minimum objective function value as an optimal BRDF fitting value, and then obtaining a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value based on the BRDF model, and outputting the BRDF model parameter fitting value as a fitting result.
The objective function formula is as follows:
，
wherein,,fitting values for BRDF>For BRDF measurements, n is the number of measured data sets.
The step S6 comprises the following steps:
s61, repeating the steps S3-S5 to finish the circulation of preset circulation times, and obtaining a plurality of objective function values;
s62, comparing the magnitudes of the objective function values, selecting a BRDF fitting value corresponding to the minimum objective function value as an optimal BRDF fitting value, obtaining a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value based on a BRDF model, and outputting the BRDF model parameter fitting value as a fitting result.
And comparing the magnitudes of the target function values, selecting the smallest target function value, wherein the BRDF fitting value corresponding to the smallest target function value is used as the optimal BRDF fitting value, substituting the BRDF fitting value into a BRDF model to obtain a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value, and outputting the BRDF model parameter fitting value as a fitting result.
The model parameters obtained by adopting the BBO-FireFly algorithm are better matched with experimental data, so that the fitting speed and the fitting precision are both greatly improved, and the model parameters have better performance; the problems of low convergence speed, weak local searching capability and long running time are overcome; the problem of sinking into a local optimal solution is avoided; the efficiency is improved, and meanwhile, the measurement accuracy of the system is improved.
Fig. 6 is a block diagram of a material surface BRDF parameter fitting system based on laser radar imaging according to an embodiment of the present invention.
Based on the same conception, the invention also provides a material surface BRDF parameter fitting system based on laser radar imaging, which comprises the following steps:
comprising the following steps: the laser light source (1), the controller (2), the electric turntable (3), the detector (4) and the processor (5), wherein the electric turntable (3) is provided with two rotating arms,
the electric turntable (3) respectively controls the rotation of the laser light source (1) and the detector (4) by utilizing two rotating arms under the control of the controller (2) to measure BRDF values of the measured material at all angles;
the processor (5) is configured to perform the BRDF parameter fitting method of a material surface according to any one of claims 1-8.
Any combination of the above optional solutions may be adopted to form an optional embodiment of the present application, which is not described herein in detail.
It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (6)
1. A material surface BRDF parameter fitting method based on laser radar imaging is characterized by comprising the following steps:
s1, measuring BRDF measured values of a measured material at various angles by using a BRDF measuring system;
s2, initializing a data value interval of BRDF model parameters, wherein the BRDF model parameters comprise specular reflection coefficients of materialsk b Coefficient of diffuse reflectionk d Roughness ofk r Refractive index coefficientaAndb；
s21, establishing a BRDF model;
the BRDF model formula is as follows:
；
；
；
wherein,,the fitted value of BRDF is represented,k b representing the coefficient of specular reflection,k d representing the coefficient of diffuse reflection,k r indicating the roughness of the material, and,aandbindex of refraction>A shadow mask function representing a model;θirepresents the angle of incidence zenith,θrrepresenting the reflected zenith angle>Representing the micro-bin normal NzThe included angle between the axes is defined by the angle,γrepresenting the angle of incidence of the local coordinate system on the micro-bin,/->Representing the azimuth angle of reflection;
s22, substituting the initialized BRDF model parameter values into the BRDF model to obtain the data value intervals of the BRDF model parameters under each angle;
s3, generating initial values of the BRDF model parameters randomly according to the data value interval of the BRDF model parameters, and initializing a BBO-FireFly algorithm to obtain initialization parameters of the BBO-FireFly algorithm;
s31, according to the data value interval of the BRDF model parameters, generating BRDF model parameter initial values with set groups at random;
s32, initializing a BBO-FireFly algorithm to obtain initialization parameters of the BBO-FireFly algorithm, wherein the initialization parameters comprise BBO algorithm parameters and FireFly algorithm parameters, and the BBO algorithm parameters comprise habitat number, population mobility, population migration rate, position mutation and mutation coefficients; the FireFly algorithm parameters comprise FireFly numbers, attractions among fireflies, position mutation and mutation coefficients;
initializing to generate habitats with corresponding numbers according to the number of habitats set by the BBO-FireFly mixing algorithm, randomly generating own positions of each habitat, initializing the initial position of a FireFly, and initializing parameters of the BBO-FireFly algorithm based on the initial position of the initial FireFly to obtain initialization parameters of the BBO-FireFly algorithm;
s4, based on the initialization parameters of the BBO-FireFly algorithm, fitting the initial values of the BRDF model parameters by adopting the BBO algorithm to obtain a plurality of BRDF model parameter fitting values, selecting the first 50% of the BRDF model parameter fitting values, inputting the BRDF model parameter fitting values into the FireFly algorithm for secondary fitting, and obtaining a plurality of BRDF model parameter optimization fitting values;
s5, substituting the BRDF model parameter optimization fitting values into the BRDF model to obtain a plurality of BRDF fitting values, and substituting the BRDF fitting values into the objective function to obtain a plurality of objective function values;
s6, repeating the steps S3-S5 for a preset number of times, finding out the minimum objective function value from all the obtained objective function values, taking the BRDF fitting value corresponding to the minimum objective function value as an optimal BRDF fitting value, and then obtaining a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value based on the BRDF model, and outputting the BRDF model parameter fitting value as a fitting result.
2. The method of claim 1, wherein S1 comprises:
s11, initializing a BRDF measuring system, setting the value ranges of an incident zenith angle and an observation zenith angle to be between-20 and 90 degrees, and setting the value ranges of an incident azimuth angle and an observation azimuth angle to be between 0 and 360 degrees;
s12, setting an incident azimuth angle and an observation azimuth angle as constants by using the BRDF measuring system, and measuring with the interval of 5 DEG of each change of the observation zenith angle under the incident conditions that the incident zenith angle is 15 DEG, 30 DEG, 45 DEG and 60 DEG respectively to obtain BRDF measuring values of the measured material under each angle.
3. The method of material surface BRDF parameter fitting according to claim 1, wherein S5 comprises:
s51, substituting the BRDF model parameter optimization fitting values into the BRDF model respectively to obtain a plurality of BRDF fitting values;
s52, substituting the BRDF fitting values into the objective function respectively to obtain a plurality of objective function values.
4. The method of material surface BRDF parameter fitting according to claim 1, wherein S6 includes:
s61, repeating the steps S3-S5 to finish the circulation of preset circulation times, and obtaining a plurality of objective function values;
s62, comparing the magnitudes of the objective function values, selecting a BRDF fitting value corresponding to the minimum objective function value as an optimal BRDF fitting value, obtaining a BRDF model parameter fitting value corresponding to the optimal BRDF fitting value based on a BRDF model, and outputting the BRDF model parameter fitting value as a fitting result.
5. The method of claim 4, wherein the objective function is formulated as follows:
；
wherein,,fitting values for BRDF>For BRDF measurements, n is the number of measured data sets.
6. A material surface BRDF parameter fitting system for implementing the material surface BRDF parameter fitting method of any one of claims 1-5, comprising: the laser light source (1), the controller (2), the electric turntable (3), the detector (4) and the processor (5), wherein the electric turntable (3) is provided with two rotating arms,
the electric turntable (3) respectively controls the rotation of the laser light source (1) and the detector (4) by utilizing two rotating arms under the control of the controller (2) to measure BRDF values of the measured material at all angles;
the processor (5) is configured to perform the BRDF parameter fitting method of a material surface according to any one of claims 1-5.
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