Spatiotemporal Flux Probing for Single-Photon Videography

2026-09-18

AI Summary

研究解决了极端光子稀缺条件下动态场景高速视频恢复问题，通过开发时空通量探测理论和算法直接从光子流估计强度的傅里叶系数。

Abstract

We address the problem of recovering high-speed videos from dynamic scenes under extreme photon sparsity. Existing methods rely on aggregating photon detections in local spatiotemporal windows to improve signal-to-noise ratio; however, this local grouping discards global structure and fails in low-light regimes where photon detections are sparse in space and time. In this work, we show that the information needed to recover both motion and illumination is encoded in correlations over the full space-time pattern of photon arrivals. Building on this insight, we develop a spatiotemporal flux probing theory and an algorithm that estimates the Fourier coefficients of the underlying intensity directly from the photon stream. We demonstrate that our approach (1) recovers fast motion and temporal illumination dynamics with substantially fewer photons than prior methods, (2) enables velocity-selective videography that automatically refocuses video onto specific detected motions, and (3) generalizes across sensing modalities including single-photon, event, and spike cameras.

Problem

• Spatiotemporal Flux Probing
• Single-Photon Videography
• Photon Sparsity

Innovation

• spatiotemporal flux probing
• Fourier coefficients estimation
• low-light videography
• velocity-selective videography