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Updated: Mar 10, 2026
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Infrared Degenerate Four-wave Mixing with Upconversion Detection for Quantitative Gas Sensing
Published on: March 22, 2019
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Upconversion optical entropy encoding for infrared complex-amplitude imaging
Sheng-Ke Zhu1, Tuqiang Pan2,3, Chao-Xian Tang1
1Institute of Electromagnetics and Acoustics, Key Laboratory of Electromagnetic Wave Science and Detection Technology, Xiamen University, Xiamen, China.
Light, Science & Applications
|March 9, 2026
Summary
Researchers developed a new infrared imaging system using upconversion optical entropy encoding. This breakthrough enables real-time complex-amplitude imaging, capturing both phase and amplitude information at video rates.
Area of Science:
- Photonics and Imaging Science
- Optoelectronics
- Deep Learning Applications
Background:
- Upconversion detection using silicon photodetectors has advanced infrared imaging.
- Current systems struggle with real-time, complex-amplitude imaging (phase and amplitude).
- This limits the full potential of infrared scene analysis.
Purpose of the Study:
- To develop a video-rate infrared complex-amplitude imaging system.
- To overcome limitations in real-time phase and amplitude information capture.
- To enhance infrared imaging capabilities for diverse applications.
Main Methods:
- Proposed upconversion optical entropy encoding by integrating coherent and incoherent approaches.
- Leveraged light scattering in disordered photonic structures and lanthanide upconversion photoluminescence.
- Utilized a deep learning network for reconstruction of infrared light-field information from visible snapshots.
Main Results:
- Demonstrated a video-rate (25 fps) infrared complex-amplitude imaging system.
- Achieved high-fidelity 8-bit grayscale modulation.
- Reached a power detection limit of 0.2 nW μm⁻², significantly improving photosensitivity.
Conclusions:
- The developed system enables real-time, high-fidelity infrared complex-amplitude imaging.
- Potential applications include natural scene imaging and autonomous driving sign classification.
- The approach is versatile and can be integrated with other cross-band imaging methods.
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