"Our method simplifies and reduces the cost of using light to capture sound while also enabling applications in scenarios where traditional microphones are ineffective, such as conversing through a glass window," said team leader Xu-Ri Yao. "As long as there is a way for light to pass through, sound transmission isn't necessary."
Published in Optics Express, the study marks the first use of single-pixel imaging for acoustic detection. Unlike conventional high-end systems, which depend on expensive lasers or high-speed cameras, this approach relies on basic optical components, making it significantly more accessible. The researchers demonstrated successful sound recovery from objects like leaves and paper sheets, revealing the broad adaptability of their method.
"The new technology could potentially change the way we record and monitor sound, bringing new opportunities to many fields, such as environmental monitoring, security and industrial diagnostics," Yao noted. "For example, it could make it possible to talk to someone stuck in a closed-off space like a room or a vehicle."
The core of the innovation lies in single-pixel imaging, where a lone detector, rather than a multi-pixel sensor, gathers light modulated by a spatial light modulator. The modulated patterns encode scene information, and a computer reconstructs the vibration data. This setup allowed Yao's team to detect sound-induced motion through changes in light intensity, even under ambient lighting conditions.
By integrating Fourier-based localization techniques, the team achieved precise and efficient measurement of subtle vibrations. "Combining single-pixel imaging with Fourier-based localization methods allowed us to achieve high-quality sound detection using simpler equipment and at a lower cost," said Yao. "Our system enables sound detection using everyday items like paper cards and leaves, under natural lighting conditions, and doesn't require the vibrating surface to reflect light in a certain way."
The system also benefits from generating minimal data-just 4 MB/s-making it suitable for long-term recording and real-time internet transmission. In tests, the visual microphone reconstructed both Mandarin and English numerals and even music from Beethoven's Fur Elise, with the paper card yielding clearer sound than the leaf. Low-frequency audio was captured accurately, while higher frequencies required filtering to improve clarity.
"Currently, this technology still only exists in the laboratory and can be used in special scenarios where traditional microphones fail to work," said Yao. The team plans to extend its applications to biological sensing, such as monitoring heart rate and pulse, while also enhancing sensitivity, range, and portability.
Research Report:A visual microphone based on computational imaging
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