Cost-efficient Active Illumination Camera For Hyper-spectral Reconstruction
원문 초록
Hyper-spectral imaging has recently gained increasing attention for use in different applications, including agricultural investigation, ground tracking, remote sensing and many other. However, the high cost, large physical size and complicated operation process stop hyperspectral cameras from being employed for various applications and research fields. In this paper, we introduce a cost-efficient, compact and easy to use active illumination camera that may benefit many applications. We developed a fully functional prototype of such camera. With the hope of helping with agricultural research, we tested our camera for plant root imaging. In addition, a U-Net model for spectral reconstruction was trained by using a reference hyperspectral camera's data as ground truth and our camera's data as input. We demonstrated our camera's ability to obtain additional information over a typical RGB camera. In addition, the ability to reconstruct hyperspectral data from multi-spectral input makes our device compatible to models and algorithms developed for hyperspectral applications with no modifications required.
함께 살펴볼 논문
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UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields
Model-Guided Network with Cluster-Based Operators for Spatio-Spectral Super-Resolution
MP-HSIR: A Multi-Prompt Framework for Universal Hyperspectral Image Restoration
GMSR:Gradient-Guided Mamba for Spectral Reconstruction from RGB Images
Learned Regularization for Inverse Problems: Insights from a Spectral Model
Spec-NeRF: Multi-spectral Neural Radiance Fields
토론
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