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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Detalhes bibliográficos

Principais autores:	Chenning Tao, Zhiyong Zhou, Huanzheng Zhu, Lianwei Huang, Haoyi Zhao, Yusheng Zhang, Daru Chen, Min Qiu, Qiang Li
Formato:	Artigo
Idioma:	Inglês
Publicado em:	SpringerOpen 2026-07-01
coleção:	PhotoniX
Assuntos:	Computational imaging Spectral imaging Spectral encoding Inverse design Euclidean distance optimization
Acesso em linha:	https://doi.org/10.1186/s43074-026-00272-0
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