Effective Linear-Array Computational Hyperspectral Imaging With Multilayer Thin Films

• Published in: IEEE photonics technology letters Vol. 37; no. 18; pp. 1041 - 1044
• Main Authors: Yao, Mingjia, Qian, Chengwei, Yuan, Jiantao, Zhu, Chengyi, Zhang, Hongfei, Weng, Jiawei, Pan, Shuwen, He, Xin, Yin, Rui
• Format: Journal Article
• Language: English
• Published: New York IEEE 15.09.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biomedical engineering; Broadband; Channels; Color imagery; computational imaging; Correlation; Filters; Fluctuations; Hyperspectral imaging; Image reconstruction; Imaging; Linear-array; Medical imaging; multilayer thin films; Multilayers; Nonhomogeneous media; Optical sensors; Remote sensing; Spectrum analysis; Thin films; Training; Transformers
• ISSN: 1041-1135; 1941-0174
• DOI: 10.1109/LPT.2025.3576272

Spectral imaging technology has extensive applications in remote sensing, medical diagnosis, biomedical engineering, archaeology and art conservation, and food testing. Conventional cameras use 4 channels (RGGB) to reconstruct color images. Our system employs 4 broadband-encoding random filters as encoders and utilizes a multi-level spectral transformer (MST) as the software decoder. This enables the reconstruction of hyperspectral images across 61 channels ranging from 410 nm to 890 nm, at a resolution of <inline-formula> <tex-math notation="LaTeX">1280\times 1080 </tex-math></inline-formula>. Experimental results demonstrate that our framework can accurately reconstruct hyperspectral images in both indoor and outdoor settings. This technology has the potential to replace existing color-imaging sensors and shows promising prospects in the fields of imaging and spectral analysis.