在间接成像中,成像操作员在间接成像中进行校对绘制
Optics express
|June 29, 2023
概括
间接成像相关图谱 (IIC) 通过重建对象的白度自相对应,使非视线 (NLOS) 成像成为可能. 这项研究模型IICIIC.
科学领域:
- 光学和光子学 在光学和光子学.
- 计算成像技术的成像
- 机器学习 机器学习
背景情况:
- 间接成像相关图谱 (IIC) 是一种用于非视线 (NLOS) 成像的连贯成像技术.
- 在大型对峙中,IIC可以恢复模糊物体的亚毫米分辨率图像.
- 在复杂的NLOS场景中预测IIC分辨率是具有挑战性的,因为对象位置和姿势的变化.
研究的目的:
- 在NLOS场景中为IIC成像操作员开发数学模型.
- 根据场景参数推导和实验验证空间分辨率的表达式.
- 提出一种自我监督的深度神经网络,用于从自相关数据中重建图像.
主要方法:
- 为间接成像相关图像 (IIC) 成像操作员开发数学模型.
- 导出空间分辨率表达式作为对象位置和姿势的函数.
- 衍生解决公式的实验验证.
- 自主监督深度神经网络的实施,用于从自相对应的图像重建.
主要成果:
- 一个经过验证的数学模型准确地预测了NLOS场景中的IIC成像操作员行为.
- 空间分辨率在数量上与物体位置和姿势参数有关.
- 通过使用深度学习框架,在1米的对峙处成功重建了具有~250μm特征的对象.
结论:
- 开发的数学模型增强了在NLOS成像中IIC性能的预测.
- 该研究提供了一种基于场景几何学的IIC分辨率优化的方法.
- 拟议的深度学习方法证明了NLOS成像中模糊对象的有效图像重建.
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