Geometry-driven spectral encoding by maximizing distinguishability in encoding space

Abstract Computational spectral imaging overcomes the trade-off between spectral resolution and light throughput, but its performance still remains fundamentally limited by the geometric separability of spectral signatures in the encoding space. Current encoder designs predominantly focus on minimiz...

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Autors principals:	Chenning Tao, Zhiyong Zhou, Huanzheng Zhu, Lianwei Huang, Haoyi Zhao, Yusheng Zhang, Daru Chen, Min Qiu, Qiang Li
Format:	Artigo
Idioma:	Inglês
Publicat:	SpringerOpen 2026-07-01
Col·lecció:	PhotoniX
Matèries:	Computational imaging Spectral imaging Spectral encoding Inverse design Euclidean distance optimization
Accés en línia:	https://doi.org/10.1186/s43074-026-00272-0
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