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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Bibliografiska uppgifter

Huvudupphov:	Chenning Tao, Zhiyong Zhou, Huanzheng Zhu, Lianwei Huang, Haoyi Zhao, Yusheng Zhang, Daru Chen, Min Qiu, Qiang Li
Materialtyp:	Artigo
Språk:	Inglês
Utgiven:	SpringerOpen 2026-07-01
Serie:	PhotoniX
Ämnen:	Computational imaging Spectral imaging Spectral encoding Inverse design Euclidean distance optimization
Länkar:	https://doi.org/10.1186/s43074-026-00272-0
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