High frequency near-infrared up-conversion single-photon imaging based on the quantum compressed sensing

Area of Science:

• Optics and Photonics
• Quantum Imaging
• Signal Processing

Background:

• Traditional photon counting for infrared up-conversion imaging suffers from long integration times and background noise sensitivity.
• These limitations hinder the practical application of infrared imaging in fields like remote sensing and night vision.

Purpose of the Study:

• To develop a novel passive up-conversion single-photon imaging method.
• To overcome the limitations of existing photon counting technologies in infrared imaging.
• To improve the signal-to-noise ratio and robustness of near-infrared imaging.

Main Methods:

• Utilized quantum compressed sensing to capture high-frequency scintillation information from near-infrared targets.
• Employed frequency domain characteristic imaging to process infrared target data.
• Developed a passive up-conversion single-photon imaging approach.

Main Results:

• Achieved significant improvement in imaging signal-to-noise ratio despite strong background noise.
• Successfully measured targets with GHz-order flicker frequencies.
• Demonstrated a signal-to-background ratio of up to 1:100 in experimental imaging.

Conclusions:

• The proposed method greatly enhances the robustness of near-infrared up-conversion single-photon imaging.
• This advancement is expected to promote the practical application of this imaging technology.
• The technique offers a promising solution for overcoming background noise challenges in sensitive imaging.