Seeing Far in the Dark with Patterned Flash

TL;DR

This paper introduces a patterned flash technique for long-distance low-light imaging, which enhances signal detection at sparse points and enables depth perception, outperforming conventional flash methods.

Contribution

The paper presents a novel patterned flash system and a joint neural network-based reconstruction and depth estimation algorithm for improved long-distance imaging.

Findings

Significantly better performance at long distances in low-light conditions.

Effective depth perception using structured light from patterned flash.

Successful hardware prototype validation.

Abstract

Flash illumination is widely used in imaging under low-light environments. However, illumination intensity falls off with propagation distance quadratically, which poses significant challenges for flash imaging at a long distance. We propose a new flash technique, named ``patterned flash'', for flash imaging at a long distance. Patterned flash concentrates optical power into a dot array. Compared with the conventional uniform flash where the signal is overwhelmed by the noise everywhere, patterned flash provides stronger signals at sparsely distributed points across the field of view to ensure the signals at those points stand out from the sensor noise. This enables post-processing to resolve important objects and details. Additionally, the patterned flash projects texture onto the scene, which can be treated as a structured light system for depth perception. Given the novel system, we develop a joint image reconstruction and depth estimation algorithm with a convolutional neural network. We build a hardware prototype and test the proposed flash technique on various scenes. The experimental results demonstrate that our patterned flash has significantly better performance at long distances in low-light environments.