Spectral Reflectance Imaging with Dual-Illumination and RGB Camera via Regularized End-to-End Learning Article Swipe
Hao Sha
,
Jeroen Cerpentier
,
Shining Ma
,
Ping Zhao
,
Yue Liu
,
Yongtian Wang
,
Youri Meuret
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1364/oe.574609
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1364/oe.574609
Spectral reflectance imaging reveals illumination-independent material properties, supporting accurate analysis in areas like medicine and cultural preservation. However, traditional hyperspectral systems are costly, and single-RGB methods often struggle with spectral ambiguity and limited accuracy. To address this trade-off between accuracy and efficiency, we propose a dual-illumination-based spectral reflectance imaging method using RGB inputs. Our method introduces a regularization-guided end-to-end framework that jointly optimizes illumination selection and reflectance reconstruction. Specifically, we incorporate regularization terms derived from multi-illumination gain priors to guide discriminative illumination learning, and design a physically-aware illumination modeling network to alleviate optimization imbalance between branches. For reconstruction, we build a lightweight yet high-performance architecture that integrates adaptive illumination augmentation, hierarchical multi-path processing, and channel-wise recalibration. Complementary spectral and spatial loss functions further improve reconstruction quality. Experiments show that our method significantly outperforms state-of-the-art methods on multiple datasets and enables high-quality reflectance reconstruction even with low-cost hardware. We deploy a physical prototype system and demonstrate its reliability under hardware-induced spectral deviations, as well as its practicality and deployment potential through the downstream application.
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All OpenAlex metadata
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https://openalex.org/W4414633358Canonical identifier for this work in OpenAlex
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https://doi.org/10.1364/oe.574609Digital Object Identifier
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Spectral Reflectance Imaging with Dual-Illumination and RGB Camera via Regularized End-to-End LearningWork title
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enPrimary language
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2025Year of publication
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2025-09-30Full publication date if available
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Hao Sha, Jeroen Cerpentier, Shining Ma, Ping Zhao, Yue Liu, Yongtian Wang, Youri MeuretList of authors in order
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https://doi.org/10.1364/oe.574609Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1364/oe.574609Direct OA link when available
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