Mitigating illumination-, leaf-, and view-angle dependencies in hyperspectral imaging using polarimetry (Conference Presentation)

Danny Krafft; Grant Scarboro; Peter Balint-Kurti; Colleen Doherty; Michael Kudenov

doi:10.1117/12.2665181

13 June 2023 Mitigating illumination-, leaf-, and view-angle dependencies in hyperspectral imaging using polarimetry (Conference Presentation)

Danny Krafft, Grant Scarboro, Peter Balint-Kurti, Colleen Doherty, Michael Kudenov

Author Affiliations +

Proceedings Volume PC12539, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VIII; PC1253908 (2023) https://doi.org/10.1117/12.2665181
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

We developed a mast-mounted hyperspectral imaging polarimeter (HIP) that images a corn field across multiple diurnal cycles throughout a growing season. Using the polarization data, we present preliminary results demonstrating the potential to use polarization to de-couple light reflected from the surface versus light scattered from the tissues, thus enabling time of day, solar incidence angle, and viewing angle to be reduced as confounding factors for the spectral measurement. Polarization correction is achieved through training neural networks and by creating a scattering model of corn leaves by measuring the Bidirectional Reflectance Distribution Function (BRDF).

Conference Presentation

Citation Download Citation

Danny Krafft, Grant Scarboro, Peter Balint-Kurti, Colleen Doherty, and Michael Kudenov "Mitigating illumination-, leaf-, and view-angle dependencies in hyperspectral imaging using polarimetry (Conference Presentation)", Proc. SPIE PC12539, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping VIII, PC1253908 (13 June 2023); https://doi.org/10.1117/12.2665181

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