Massaro Gianlorenzo, Pepe Francesco V, D'Angelo Milena
Dipartimento Interateneo di Fisica, Università degli Studi di Bari, 70125 Bari, Italy.
Istituto Nazionale di Fisica Nucleare, Sezione di Bari, 70125 Bari, Italy.
Sensors (Basel). 2022 Sep 3;22(17):6665. doi: 10.3390/s22176665.
Correlation plenoptic imaging (CPI) is a technique capable of acquiring the emerging from a scene of interest, namely, the combined information of intensity and propagation direction of light. This is achieved by evaluating correlations between the photon numbers measured by two high-resolution detectors. Volumetric information about the object of interest is decoded, through data analysis, from the measured four-dimensional correlation function. In this paper, we investigate the relevant aspects of the refocusing algorithm, a post-processing method that isolates the image of a selected transverse plane within the 3D scene, once applied to the correlation function. In particular, we aim at bridging the gap between existing literature, which only deals with refocusing algorithms in case of continuous coordinates, and the experimental reality, in which the correlation function is available as a discrete quantity defined on the sensors pixels.
相关全光成像（CPI）是一种能够获取从感兴趣场景中出射的光的技术，即光的强度和传播方向的组合信息。这是通过评估两个高分辨率探测器测量的光子数之间的相关性来实现的。通过数据分析，从测量的四维相关函数中解码出关于感兴趣物体的体积信息。在本文中，我们研究了重聚焦算法的相关方面，这是一种后处理方法，一旦应用于相关函数，就可以在3D场景中分离出选定横向平面的图像。特别是，我们旨在弥合现有文献（仅处理连续坐标情况下的重聚焦算法）与实验现实（其中相关函数作为定义在传感器像素上的离散量可用）之间的差距。
