Spline based emissivity retrieval for LWIR hyperspectral imagery

O. McElhinney; M. L. Pieper; D. Manolakis; C. Loughlin; V. Ingle; Randall Bostick; A. Weisner

doi:10.1117/12.2618553

31 May 2022 Spline based emissivity retrieval for LWIR hyperspectral imagery

O. McElhinney, M. L. Pieper, D. Manolakis, C. Loughlin, V. Ingle, Randall Bostick, A. Weisner

Proceedings Volume 12094, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII; 120940N (2022) https://doi.org/10.1117/12.2618553
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

Effective material identification with hyperspectral thermal infrared imaging requires an accurate estimate of the material emissivity within a pixel. When atmospheric effects are accurately known, the measured at-sensor radiance can be converted to ground radiance. Emissivity retrieval from the ground radiance is an undetermined problem due to the additional unknown temperature of the material. Hyperspectral temperature emissivity separation (TES) retrieval algorithms assume the emissivity spectra for solids are smooth and that the determined emissivity will be smoothest when the correct temperature is found. Smoothness-based TES algorithms typically quantify roughness by what a smoothing technique removes when applied to an emissivity estimate with temperature. We propose measuring the roughness of an emissivity estimate directly using splines. Splines can be used to fit a continuously differentiable function to the emissivity estimates at all temperatures exactly. Roughness can then be calculated as the integral of the second derivative squared of the spline. Where smoothing-based TES algorithms typically have difficulty on rough emissivity signatures due to the over-smoothing of true emissivity features, splines show resistance to rough signatures since they preserve the emissivity features. In this paper TES using splines will be described along with a comparative performance evaluation to the standard smoothingbased algorithm. Ground radiance test spectra are simulated with smooth and rough emissivity signatures. An improvement is shown using TES with splines for rough emissivity signatures.

Conference Presentation

Citation Download Citation

O. McElhinney, M. L. Pieper, D. Manolakis, C. Loughlin, V. Ingle, Randall Bostick, and A. Weisner "Spline based emissivity retrieval for LWIR hyperspectral imagery", Proc. SPIE 12094, Algorithms, Technologies, and Applications for Multispectral and Hyperspectral Imaging XXVIII, 120940N (31 May 2022); https://doi.org/10.1117/12.2618553

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