通过深度学习在扩散器后面的光谱成像中估计中心波长
Applied optics
|September 14, 2023
概括
这项研究引入了一种深度学习方法,用于从斑点图像中估计中心波长. 这使得使用单色相机通过散射介质进行多光谱成像.
科学领域:
- 光学和光子学 在光学和光子学.
- 计算机视觉 计算机视觉
- 机器学习 机器学习
背景情况:
- 通过散射介质进行多谱成像对于传感应用至关重要.
- 斑点图像包含编码的空间和光谱信息,使物体结构和光谱估计成为可能.
- 当前的方法在通过散射介质重建图像和估计光谱特性方面面临挑战.
研究的目的:
- 开发一种基于深度学习的策略,用于估计来自斑点图像的照明光的中心波长.
- 使用单个单色相机,通过散射介质实现多光谱成像.
- 在单一拍摄中重建图像并估计光谱信息.
主要方法:
- 利用深度学习来分析用单色相机拍摄的斑点图像.
- 在不同中央波长的窄带光采集的斑点图像上训练模型.
- 制定扩展光谱区域用于图像重建和波长估计的战略.
主要成果:
- 精确估计的中心波长在1纳米的步骤对物体的100纳米的光谱变化.
- 一次成功的图像重建和中央波长估计.
- 演示深度学习能够从斑点模式解码光谱信息的能力.
结论:
- 拟议的深度学习方法有效地估计了来自斑点图像的中心波长,克服了分散媒体的挑战.
- 这种技术可通过使用单色相机的散射介质进行一次性多光谱成像.
- 这种方法具有很大的潜力,可以在各个领域推进传感技术.
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