Target recognition method based on polarization parameters

Guo, Lei; Cao, Ercong; Gu, Guohua; Hu, Xiaobo; Qian, Wei; Wan, Minjie; Zhao, Ran

doi:10.1117/12.2247059

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Polarization of light provides valuable information about scenes that cannot be obtained directly from intensity or spectral images and polarization images seek to obtain the vector nature of the optical field from the scene [1]. Polarization imaging is widely used in those fields, such as industrial inspection [2], environmental monitoring [3], biomedical diagnosis [4,5], marine detection [6][7][8], remote sensing [9][10][11], military reconnaissance [12][13][14], etc.…”

Section: Introductionmentioning

confidence: 99%

An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy

Zhang

Sun

et al. 2018

Anal. Chem.

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Improving both the stability and accuracy of laser-induced breakdown spectroscopy (LIBS) is an issue in quantitative analysis. For certain environments outside of the laboratory, consistently and exactly maintaining the distance from the optical system to the sample surface is difficult, and fluctuations of this distance severely affect the stability of the spectrum. In this work, the principal components of the plasma images are extracted and used to correct the spectral line intensities as an auxiliary method to reduce spectral fluctuation. The presented image auxiliary method is combined with univariate analysis and multivariate analysis, and the element concentrations of Cu, Mn, V, and Cr in steel samples are analyzed. For univariate analysis, all the determination coefficients ( R) of the four elements exceed 0.99, whereas the average relative standard deviations (RSDs) of the intensities decrease from 30.45, 23.14, 27.03, and 22.04%, to 2.13, 3.38, 2.49, and 3.58%, respectively. For the multivariate analysis, the R values for Cu, Mn, V, and Cr also all exceed 0.99, and the average RSDs of the predicted concentrations of the validation samples decrease to 2.87, 3.82, 2.86, and 6.51%, respectively.

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Section: Introductionmentioning

confidence: 99%

An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy

Zhang

Sun

et al. 2018

Anal. Chem.

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Polarized-pixel performance model for DoFP polarimeter

Feng

Shi

Liu

et al. 2018

J. Opt.

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A division of a focal plane (DoFP) polarimeter is manufactured by placing a micropolarizer array directly onto the focal plane array (FPA) of a detector. Each element of the DoFP polarimeter is a polarized pixel. This paper proposes a performance model for a polarized pixel. The proposed model characterizes the optical and electronic performance of a polarized pixel by three parameters. They are respectively major polarization responsivity, minor polarization responsivity and polarization orientation. Each parameter corresponds to an intuitive physical feature of a polarized pixel. This paper further extends this model to calibrate polarization images from a DoFP (division of focal plane) polarimeter. This calibration work is evaluated quantitatively by a developed DoFP polarimeter under varying illumination intensity and angle of linear polarization. The experiment proves that our model reduces nonuniformity to 6.79% of uncalibrated DoLP (degree of linear polarization) images, and significantly improves the visual effect of DoLP images.

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Target recognition method based on polarization parameters

Cited by 2 publications

References 3 publications

An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy

An Image Auxiliary Method for Quantitative Analysis of Laser-Induced Breakdown Spectroscopy

Polarized-pixel performance model for DoFP polarimeter

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