Biological Vision Inspired Adaptive Plasmonic Polarizer for Object-Level Infrared Meta-Imaging

Abstract

Polarization-resolved imaging systems detect structural contrast beyond intensity, yet conventional systems often suffer from fixed analyzers. To date, achieving spectral modulation via polarization scanning remains challenging in the longwave infrared region. Inspired by mantis shrimp vision, we present a plasmonic polarizer enabling continuous polarization-angle (0–180°) encoding for infrared meta-imaging. The meta-polarizer consists of patterned graphene with alternating ferroelectric domains, achieving transmission extinction modulations of 5.59 and 8.91 dB at 9.5 and 12.3 μm. Simulations attribute polarization selectivity to graphene plasmon resonances tunable by meta-polarizer geometry and the ferroelectric-domain-induced carrier concentration. We also develop an object-level fusion framework selecting optimal polarization states per target based on contrast, edge, entropy, and degree of polarization. On a 36-orientation data set of 42,660 images, the fused meta-polarizer image exceeds 97% detection precision, versus 83% for conventional thermal imaging. Our work highlights spectral-spatial encoding with physics-guided preprocessing, advancing thermal perception for autonomous sensing.