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排放幽灵成像:通过数据增强进行重建

K J Coakley¹, H H Chen-Mayer², B Ravel²

¹National Institute of Standards and Technology, 325 Broadway, Boulder, CO 80305 USA.

Physical review. A

|April 15, 2024

概括

幽灵成像通过调节发生束来使用单像素探测器重建物体. 这项研究介绍了一种数据增强方法,用于改进QR因子化和无效化,增强2D对象重建.

科学领域:

光学和光子学在光学和光子学.
计算机成像成像技术
在X射线成像中使用X射线成像.

背景情况:

幽灵成像使用单像素探测器重建没有空间分辨率的物体.
发生光束的空间调制与不同的面具方向是幽灵成像的关键.
传统方法面临的挑战是测量矩阵因子化,当方向小于像素时.

研究的目的:

改进幽灵成像重建,特别是当面具定向的数量 (N) 小于像素的数量 (P) 时.
开发一种使用幽灵成像技术进行二维物体重建的强大方法.
为了提高精度和减少幽灵成像重建中的噪音.

主要方法:

开发了一种数据增强方法,以实现对N < P的测量矩阵的QR分解.
采用截断的单数值分解来确定噪声抑制的摩尔-罗斯伪反向.
应用了自适应权重光滑方法来进一步消除重建图像的阴影.
利用在布鲁克黑文国家实验室获得的X射线光数据进行实验验证.

主要成果:

提出的方法即使在N < P时也能成功执行QR分解.
截断的SVD和自适应重量平滑的组合显著减少重建中的噪音.
与Gram-Schmidt正交法化方法相比,模拟显示出更高的性能.
对实验性X射线光数据的成功应用证明了其实际效用.

结论:

新的数据增强和否定策略增强了幽灵成像重建的准确性和稳定性.
该方法在面具定向有限的场景中特别有效.
这项工作为幽灵成像应用提供了重大进展,包括X射线光成像.

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