Analysis of Optimal Spectral Bands for Thermal Infrared Hyperspectral Image Reconstruction Driven by Physical Simulation Model

doi:10.16182/j.issn1004731x.joss.25-FZ0720

Abstract

Abstract:

To achieve accurate reconstruction of thermal infrared hyperspectral images under limited spectral bands, this paper proposed a reconstruction method based on physical modeling and simulation. Semi-global decomposition algorithm was adopted to invert the thermophysical properties of the scenario based on the physical model of thermal radiation, simulating and generating full-band hyperspectral data. An optimal spectral band selection strategy driven by a physical model was proposed, which integrated the sensitivity of temperature inversion and the separability of material spectra. Experiments were conducted on both simulated and measured datasets to evaluate the performance of material identification, temperature inversion, and spectral reconstruction under different numbers of spectral bands and selection strategies.Simulation results show that the proposed strategy improves the inversion accuracy of thermophysical properties when the number of spectral bands is small. In terms of spectral reconstruction, the strategy effectively suppresses local error peaks and improves the overall stability and reliability of reconstruction by ensuring the simulation accuracy of critical wavenumber regions.

Key words: thermal infrared, hyperspectral, spectral reconstruction, semi-global decomposition, temperature and emissivity separation, spectral band optimization

CLC Number:

TP751.1

Yang Yonghao, He Xiaoyu. Analysis of Optimal Spectral Bands for Thermal Infrared Hyperspectral Image Reconstruction Driven by Physical Simulation Model[J]. Journal of System Simulation, 2025, 37(12): 3189-3201.

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参数	仿真场景4	实测场景11
数据尺寸	1 080×1 920×54	260×1 500×49
波数范围/cm^-1	720:10:1 250	760:10:1 240
材料种类数	4	6