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Hybrid deep learning for hyperspectral cube reconstruction in computed tomography imaging spectrometry via angular spectrum propagation
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DOI：10.1016/j.optlaseng.2026.109827.png)
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Abstract
En 中文
• Introduces SGD-RODE for high-fidelity CTIS hyperspectral cube reconstruction. • Uses spectral weighting and graph-based ODEs for spatial-spectral consistency. • Applies SPP to correct distortions from diffractive optics and misalignment. • Employs MobileNetV4 for efficient spectral-spatial feature extraction. • Integrates GCAA to optimize loss, speed convergence, and improve stability.
Keywords:
SGD-RODE
spectral weighting
graph-based ODEs
SPP
MobileNetV4
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3.7
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