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Tunable Optimally‐Coded Snapshot Hyperspectral Imaging for Scene Adaptation (Laser Photonics Rev. 19(10)/2025)
Author(s) -
Zhang Chong,
Liu Wenjing,
Li Juntao,
Li Siqi,
Wang Lizhi,
Huang Hua,
Zheng Yuanjin,
Wang Yongtian,
Suo Jinli,
Song Weitao
Publication year - 2025
Publication title -
laser and photonics reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.778
H-Index - 116
eISSN - 1863-8899
pISSN - 1863-8880
DOI - 10.1002/lpor.202570044
Tunable Optimally Coded Snapshot Hyperspectral Imaging The cover feature highlights the principles and capabilities of the tunable optimally coded snapshot hyperspectral imaging (TOSHI) system. By leveraging the refreshability of the LCoS‐SLM, TOSHI dynamically optimizes optical encoding and software decoding based on scene data, enhancing spectral and spatial reconstruction accuracy. This image demonstrates its effectiveness in adaptive hyperspectral imaging across various lighting conditions and complex scenes. Integrating hardware encoding with deep learning‐based reconstruction, TOSHI advances computational hyperspectral imaging for scientific and industrial applications. For more details, see article 2401921 by Weitao Song and co‐workers.

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