一个可见,近红外和中红外的计算光谱仪,由单旋旋片编码器启用
Junren Wen1,2,3, Weiming Shi2,3, Cheng Gao1,2,3
1Shanghai Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Shanghai, China.
Communications engineering
|February 28, 2025
概括
这项研究引入了一种使用单旋膜编码器 (SSFE) 和深度学习的新型计算光谱仪. 它可以在可见到中红外范围内实现高分辨率的光谱分析,用于化学化合物分类.
科学领域:
- 光谱学和光谱仪学
- 计算成像技术的成像
- 材料科学 材料科学 材料科学
背景情况:
- 传统的基于过器的光谱编码使制造和设备的一致性变得复杂.
- 计算光谱仪提供低成本,现场和快速的光谱分析能力.
- 现有的方法在实现高分辨率和在广的频谱范围内保持一致性方面面临挑战.
研究的目的:
- 开发一种新的计算光谱仪,用于可见到中红外光谱分析.
- 通过使用新的编码方法和重建算法来提高光谱分辨率和精度.
- 为了证明该设备在经济高效的化学化合物分类方面的潜力.
主要方法:
- 集成单旋片编码器 (SSFE) 与基于深度学习的重建算法.
- 使用粒子群优化 (PSO) 为低相关性和高复杂性优化光谱反应.
- 对光谱重建准确度和化学化合物分类精度的实验验证.
主要成果:
- 实现了0.5nm (可见光),2nm (近红外) 和10nm (中红外) 的单峰分辨率.
- 对于各自的范围,已证明3nm,6nm和20nm的双峰分辨率.
- 在可见范围的光谱重建中获得了1.05 × 10−3的平均平均平方误差 (MSE).
- 在对220种化学化合物进行分类时,获得了81.38%的精度.
结论:
- 拟议的基于SSFE的计算光谱仪可以在广泛的波长范围内提供高分辨率的光谱分析.
- SSFE和深度学习的结合为光谱重建提供了强大而准确的方法.
- 这项技术为紧,经济高效和多功能光谱应用提供了一个有前途的解决方案.
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