Mr. Bo Jia Profile

Bo Jia

at Beihang Univ

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Proceedings Article | 12 December 2018 Paper

Roughness estimation of inhomogeneous paint based on polarization imaging detection

Ying Zhang, Jiabin Xuan, Huijie Zhao, Bo Jia, Liyi Luo, Yi Zhang

Proceedings Volume 10849, 1084910 (2018) https://doi.org/10.1117/12.2505479

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Polarimetric imagery is a powerful tool in remote sensing because the polarization information of the targets contains surface features, shape, material composition, and surface roughness, which improves applications such as target detection, shape extraction and anomaly detection. For the importance of the quantitative polarmetric remote sensing, the quantitative estimation of the physical characteristics of the target has attracted considerable scientific interests and become the trend of polarimetric imagery. However, because of the spatial scale effect, specifically, in the large detection distance, the quantitative estimation accuracy of the target can be affected by the inhomogeneous target. In this paper, a novel method based on polarization imaging detection to estimate the roughness of inhomogeneous paint surface in outdoor is proposed. A shadowing method was used to eliminate the effect of skylight and improve the estimation accuracy in outdoor experiment. In addition, the correction method based on local variance of roughness distribution was performed to improve the estimation accuracy of inhomogeneous paint. The results showed that the estimation error of roughness for homogeneous paint in two distances were both below 8%. Especially for the target with smaller roughness, after the correction, the estimation accuracy of inhomogeneous paint were below 6% in two detection distances, which confirms the effectiveness of estimation approach and verifies the practicality of the correction method to improve the estimation accuracy of inhomogeneous target in polarimetric imaging remote sensing detection. The approach presented in this paper has important significance for the development of the quantitative remote sensing, especially for targets with inhomogeneous surface.

Proceedings Article | 12 December 2018 Paper

Surface properties estimation of sandy land based on multi-angle polarized image information

Bo Jia, Ying Zhang, Huijie Zhao, Jiabin Xuan, Liyi Luo, Na Li

Proceedings Volume 10844, 108440N (2018) https://doi.org/10.1117/12.2505204

KEYWORDS: Surface roughness, Polarization, Statistical analysis, Particles, Reflection, Error analysis, Surface properties, Remote sensing, Reflectivity, Bidirectional reflectance transmission function

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In this paper a method to estimate surface roughness of sand land from multi-angle and multi-waveband polarized detections is presented. Firstly, the polarized bidirectional reflectance distribution function (pBRDF) of the sand land’s surface based on the microfacet theory was established. Then three sand samples with particle sizes of 0.5 mm, 0.7 mm and 1 mm were obtained by a series of sieves. And the polarization information was acquired by full-polarized multispectral imaging system based on Liquid Crystal Variable Retarder (LCVR). We used the nonlinear least squares method to estimate the surface roughness of from the measured data. Lastly, the analysis results show that the accuracy of sand roughness estimation is improved as the number of the angles (i.e., source incident angles and detection angles) and wavebands increase until the estimation accuracy saturates. It is indicated that the method based on polarization imaging detection to estimate sandy land surface roughness is effective.

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