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Proceedings Article | 1 November 2024 Presentation + Paper

Multiresolution components fused evaluation for hyperspectral atmospheric radiative transfer model using feature selective validation

Shaoping Shuai, Jun Ma, Jia Liu, Xiaoyu He, Xiaojian Xu

Proceedings Volume 13199, 131990C (2024) https://doi.org/10.1117/12.3031448

KEYWORDS: Fused deposition modeling, Atmospheric modeling, Data modeling, Histograms, Radiative transfer, Wavelets, Spectral resolution, Reflection, Computer simulations, Atmospheric particles

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Hyperspectral atmospheric radiative transfer model (HARTM) is an essential component for image calibration and explanation in remote sensing applications. A HARTM describes the interaction between electromagnetic radiation and the earth’s atmosphere, which affects the quality and radiative accuracy of the acquired data. The performance evaluation of the HARTM is crucial to ensure the reliability of the retrieved information from calibrated images. By comparing the simulated results with measured or other validated reference data, the accuracy of HARTM can be assessed. Currently used similarity metrics, such as the Euclidean distance (ED) and the spectral angle metric (SAM), are relatively one-sided and single-valued overall assessment in evaluating hyperspectral model. The IEEE standard 1597.1 proposed feature selective validation (FSV) method as the key mathematical tool which has been widely applied in electromagnetic model verification, validation and accreditation (VV&A). However, to the best of our knowledge, the applications of FSV method in evaluating hyperspectral similarity has not yet been proposed up to this point. This paper concentrates on developing a technique for HARTM evaluation by means of FSV. Specifically, a multi-resolution components fused evaluation is proposed to obtain a more flexible comparison between the model and the measured data. As an example, the proposed approach is applied to validate the BeiHang University-Atmospheric Transfer Model (BHU-ATM) using the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) data. Results of multi-resolution components fused evaluation show good consistency with the results of directly evaluating the original data.

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