Laser Technology, Volume. 47, Issue 3, 407(2023)

Parameter fitting method of BRDF model based on generalized inverse matrix

ZHAO Jiale1, ZHOU Bing1, WANG Guanglong2、*, YING Jiaju1, WANG Qianghui1, and DENG Lei1
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    In order to improve the efficiency of parameter fitting of binary reflectance distribution function (BRDF)model and understand the spectral direction characteristics of ground object more specifically, a method of parameter fitting of BRDF model based on generalized inverse matrix was proposed. Firstly, the directional characteristics of spectral reflection of ground objects were analyzed, and then the spectral reflectance of targets in different directions was measured by imaging spectrometer. The experimental conditions and a priori measurement data were substituted into BRDF model, the generalized inverse matrix equation was established, and the model parameters of measurement targets were fitted. Using the BRDF model parameters of fitting the push any particular direction under the condition of spectral reflectance and compared with experimental data. Spectral angle mapping method was used to measure its similarity and the results showed that the grass and camouflage raincoat fitting spectrum curve and the measured spectral curve similarity is very high, up to the 0.1307 and 0.0896, confirmed the validity of the parameter fitting method, the ability to verify the generalization of the BRDF model fitting. This method is simple in principle, fast and effective, and provides reference for other types of BRDF model parameter fitting and subsequent research on spectral characteristics of ground objects.

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    ZHAO Jiale, ZHOU Bing, WANG Guanglong, YING Jiaju, WANG Qianghui, DENG Lei. Parameter fitting method of BRDF model based on generalized inverse matrix[J]. Laser Technology, 2023, 47(3): 407

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    Paper Information

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    Received: Mar. 24, 2022

    Accepted: --

    Published Online: Dec. 5, 2023

    The Author Email: WANG Guanglong (zhbgxgc@163.com)

    DOI:10.7510/jgjs.issn.1001-3806.2023.03.019

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