# Upconversion optical entropy encoding for infrared complex-amplitude imaging

## TL;DR

A new infrared imaging method uses upconversion and entropy encoding to capture detailed images at video speed with high sensitivity.

## Contribution

Introduces upconversion optical entropy encoding for real-time, high-fidelity infrared complex-amplitude imaging.

## Key findings

- Achieved video-rate infrared imaging at 25 fps with 8-bit grayscale modulation.
- Demonstrated a power detection limit three orders of magnitude lower than conventional methods.
- Applied the system to natural scene imaging and speed-limit sign classification for autonomous driving.

## Abstract

Upconversion detection of infrared radiation by cost-effective silicon photodetectors in visible bands has spurred a revolution in infrared imaging technology, unlocking a wide range of applications in biological imaging, optical spectroscopy, and optical data storage. Despite significant progress in upconversion detection, real-time, concurrent, complex-amplitude imaging of both phase and amplitude information, indispensable for disclosing the full signature of infrared scenes, remains a daunting challenge, impeding their widespread applications. By integrating the unique advantages of both coherent and incoherent approaches, we propose the concept of upconversion optical entropy encoding and demonstrate a video-rate infrared complex-amplitude imaging system. This is achieved by leveraging the synergistic interaction between light scattering in disordered photonic structures and lanthanide upconversion photoluminescence. By tailoring the information entropy of upconversion speckles, infrared light-field information can be captured in a single visible snapshot and explicitly reconstructed, assisted by a deep learning network, enabling infrared complex-amplitude imaging at a video rate of 25 frames per second (fps) and with high-fidelity 8-bit grayscale modulation. The high photosensitivity of the developed infrared imaging system enables a power detection limit of 0.2 nW μm−2, three orders of magnitude lower than that of conventional parametric upconversion imaging. As a proof of concept, we demonstrate its applications in capturing video frames of natural scene images and classifying images of speed-limit signs for autonomous driving. This approach can be readily integrated with other cross-band imaging methods, paving the way for various infrared application scenarios that require video-rate, high-photosensitivity, and high-fidelity protocols.

We demonstrate upconversion optical entropy encoding for infrared complex-amplitude imaging by leveraging the synergistic interaction between light scattering in disordered photonic structures and lanthanide upconversion photoluminescence.