Seeing through fire with one pixel

Zilin Deng

doi:10.1016/j.optlaseng.2024.108540

2024-12-01

PRE

Guoan Zheng (Guoan Zheng)

常

常慧宾 (Huibin Chang)

Jingang Zhong

DOI：10.1016/j.optlaseng.2024.108540

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摘要

En 中文

Seeing through fire is a critical capability in various applications, such as fire rescue, industrial combustion monitoring, and scientific research. However, the intense electromagnetic radiation emitted by flames can saturate and blind conventional imaging systems, making it challenging to visualize objects or scenes obscured by fire. In this paper, we present a novel method for real-time, full-color through-flame imaging using structured illumination and single-pixel detection. By projecting a series of carefully designed light patterns onto the scene and measuring the backscattered light with a single-pixel detector, we can computationally reconstruct the obscured scene while effectively suppressing the flame's contribution to the image. The single-pixel detector's high dynamic range and sensitivity enable it to capture the weak backscattered signal without being overwhelmed by the flame's intense radiation. We demonstrate the method's effectiveness in several experiments, showcasing its ability to image static and dynamic scenes through both steady and turbulent flames at a frame rate of 15 Hz. Furthermore, we show that the proposed method can be extended to full-color imaging by using three single-pixel detectors with different color filters. The results highlight the potential of this approach for enhancing visibility in fire-related scenarios and other challenging imaging conditions. We believe that the integration of this technology into augmented reality systems could provide firefighters and other users with valuable real-time visual information, improving situational awareness and decision-making in critical situations. We also believe the method can be used for seeing through any self-luminous objects.

Keyword:

Single-pixel imaging

Through-flame imaging

Real-time imaging

Full-color imaging

Computational imaging