Aircraft skin defect localization using imaging polarimetry

Luo, David A.; Barraza, E. Tomas; Kudenov, Michael W.

doi:10.1117/1.oe.57.8.084101

Cited by 3 publications

References 33 publications

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Study on scattering light field distribution of optical element in-surface defects based on Mueller matrix

et al. 2021

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For precise optical elements, the size of in-surface defects is at the nanometer scale. When incident light illuminates in-surface defects on optical elements, strong diffraction and scattering effects are produced, and this greatly reduces the beam quality in optical systems. In this study, a three-dimensional model of the in-surface defects of K9 optical components was established. On this basis, a theoretical model of electromagnetic scattering between the defect and the incident and scattering fields was constructed. The 4 × 4-order scattering Mueller matrix light field distributions of incident light modulated by different-sized defects were obtained by numerical simulations, and the influencing factors were analyzed. These simulations provide a theoretical basis and a reference for the manufacture of precision optical elements and a scale calibration for surface quality detection methods.

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Study on scattering light field distribution of optical element in-surface defects based on Mueller matrix

et al. 2021

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Fast compressed channeled spectropolarimeter for full Stokes vector measurement

Zhou

et al. 2019

Modeling Aspects in Optical Metrology VII

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Mitigating Illumination-, Leaf-, and View-Angle Dependencies in Hyperspectral Imaging Using Polarimetry

Krafft,

Scarboro,

Hsieh

et al. 2024

Plant Phenomics

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Automation of plant phenotyping using data from high-dimensional imaging sensors is on the forefront of agricultural research for its potential to improve seasonal yield by monitoring crop health and accelerating breeding programs. A common challenge when capturing images in the field relates to the spectral reflection of sunlight (glare) from crop leaves that, at certain solar incidences and sensor viewing angles, presents unwanted signals. The research presented here involves the convergence of 2 parallel projects to develop a facile algorithm that can use polarization data to decouple light reflected from the surface of the leaves and light scattered from the leaf’s tissue. The first project is a mast-mounted hyperspectral imaging polarimeter (HIP) that can image a maize field across multiple diurnal cycles throughout a growing season. The second project is a multistatic fiber-based Mueller matrix bidirectional reflectance distribution function (mmBRDF) instrument which measures the polarized light-scattering behavior of individual maize leaves. The mmBRDF data was fitted to an existing model, which outputs parameters that were used to run simulations. The simulated data were then used to train a shallow neural network which works by comparing unpolarized 2-band vegetation index (VI) with linearly polarized data from the low-reflectivity bands of the VI. Using GNDVI and red-edge reflection ratio we saw an improvement of an order of magnitude or more in the mean error ( ϵ ) and a reduction spanning 1.5 to 2.7 in their standard deviation ( ϵ σ ) after applying the correction network on the HIP sensor data.

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Aircraft skin defect localization using imaging polarimetry

Cited by 3 publications

References 33 publications

Study on scattering light field distribution of optical element in-surface defects based on Mueller matrix

Study on scattering light field distribution of optical element in-surface defects based on Mueller matrix

Fast compressed channeled spectropolarimeter for full Stokes vector measurement

Mitigating Illumination-, Leaf-, and View-Angle Dependencies in Hyperspectral Imaging Using Polarimetry

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