A Multi‐Resonant Tunable Fabry‐Pérot Cavity for High Throughput Spectral Imaging

Abstract Spectral imaging technology has gained widespread application across diverse fields due to its ability to capture spatial and spectral information simultaneously. However, conventional spectral scanning methods using single‐peak tunable filters face the challenges of low optical throughput. Inspired by Fellgett's advantage in Fourier‐transform infrared spectroscopy, this paper proposes a tunable filter with multiple resonances to improve optical throughput. It is composed of a simple Fabry‐Pérot cavity filled with liquid crystal. An artificial neural network is employed to match with the filter for spectrum reconstruction. Experimental results show a spectral resolution of 10 nm and a switching time of ≈23 ms between adjacent states. As a demonstration, biological specimens are spectrally imaged under different light conditions with good fidelity. The results suggest that the filter possesses over six times higher optical throughput than a commercial liquid crystal tunable filter (LCTF), leading to better spectrum accuracy for spectral imaging under low‐light conditions. The compact and cost‐effective design of this tunable filter enables seamless integration into imaging systems, presenting promising prospects for practical applications such as portable health management and food inspection in low‐light conditions.