Abstract
Single-photon cameras are becoming increasingly popular in time-of-flight 3D imaging because they can time-tag individual photons with extreme resolution. However, their performance is susceptible to hardware limitations, such as system bandwidth, maximum laser power, sensor data rates, and in-sensor memory and compute resources. Compressive histograms were recently introduced as a solution to the challenge of data rates through an online in-sensor compression of photon timestamp data. Although compressive histograms work within limited in-sensor memory and computational resources, they underperform when subjected to real-world illumination hardware constraints. To address this, we present a constrained optimization approach for designing practical coding functions for compressive single-photon 3D imaging. Using gradient descent, we jointly optimize an illumination and coding matrix (i.e., the coding functions) that adheres to hardware constraints. We show through extensive simulations that our coding functions consistently outperform traditional coding designs under both bandwidth and peak power constraints. This advantage is particularly pronounced in systems constrained by peak power. Finally, we show that our approach adapts to arbitrary parameterized impulse responses by evaluating it on a real-world system with a non-ideal impulse response function.
Abstract (translated)
单光子相机因能够以极高分辨率标记个别光子，在飞行时间3D成像领域越来越受欢迎。然而，它们的性能易受硬件限制的影响，如系统带宽、最大激光功率、传感器数据传输速率以及片上存储和计算资源等。最近引入了压缩直方图作为一种解决数据率挑战的方法，通过在线片上压缩光子时间戳数据来实现。尽管压缩直方图能够在有限的片上内存和计算资源下工作，但在面对实际照明硬件限制时表现不佳。为了解决这个问题，我们提出了一种约束优化方法，用于设计适用于压缩单光子3D成像的实际编码函数。通过梯度下降法，我们可以同时优化照明与编码矩阵（即编码功能），使其符合硬件限制条件。通过广泛的模拟实验，我们展示了我们的编码方案在带宽和峰值功率受限的情况下均优于传统编码设计方案的性能表现，特别是在受到峰值功率约束的系统中优势更为显著。最后，我们在一个具有非理想脉冲响应函数的实际系统上评估了这种方法，证明它可以适应任意参数化的脉冲响应。
URL
https://arxiv.org/abs/2510.12123
