Single-photon cameras (SPCs) have emerged as a promising technology for high-resolution 3D imaging. A single-photon 3D camera determines the round-trip time of a laser pulse by capturing the arrival of individual photons at each camera pixel. Constructing photon-timestamp histograms is a fundamental operation for a single-photon 3D camera. However, in-pixel histogram processing is computationally expensive and requires large amount of memory per pixel. Digitizing and transferring photon timestamps to an off-sensor histogramming module is bandwidth and power hungry. Here we present an online approach for distance estimation without explicitly storing photon counts. The two key ingredients of our approach are (a) processing photon streams using race logic, which maintains photon data in the time-delay domain, and (b) constructing count-free equi-depth histograms. Equi-depth histograms are a succinct representation for ``peaky'' distributions, such as those obtained by an SPC pixel from a laser pulse reflected by a surface. Our approach uses a binner element that converges on the median (or, more generally, to another quantile) of a distribution. We cascade multiple binners to form an equi-depth histogrammer that produces multi-bin histograms. Our evaluation shows that this method can provide an order of magnitude reduction in bandwidth and power consumption while maintaining similar distance reconstruction accuracy as conventional processing methods.

翻译：单光子相机（SPC）已成为高分辨率三维成像领域的一项有前景技术。单光子3D相机通过捕捉每个像素处单个光子的到达时刻，来确定激光脉冲的往返时间。构建光子时间戳直方图是单光子3D相机的基本操作。然而，像素内直方图处理计算成本高昂，且每个像素需要大量内存。将光子时间戳数字化并传输到片外的直方图模块，则存在带宽和功耗瓶颈。本文提出了一种无需显式存储光子计数的在线距离估计方法。该方法有两个关键要素：（a）利用竞态逻辑处理光子流，将光子数据维持在时延域中；（b）构建免计数的等深直方图。等深直方图是对“尖峰”型分布（例如SPC像素接收经表面反射的激光脉冲所获得的分布）的一种简洁表示。我们的方法采用一种能收敛到分布中位数（或更一般地，其他分位数）的分箱器件。通过级联多个分箱器件，我们构成了一个等深直方图生成器，可产生多箱直方图。评估表明，该方法在保持与传统处理方法相近的距离重建精度的同时，可将带宽和功耗降低一个数量级。