期刊
OPTICA
卷 7, 期 10, 页码 1298-1307出版社
Optica Publishing Group
DOI: 10.1364/OPTICA.397214
关键词
-
类别
资金
- National Science Foundation [DGE 1752814, DMR 1548924]
- Gordon and Betty Moore Foundation [GBMF4562]
Hyperspectral imaging is useful for applications ranging from medical diagnostics to agricultural crop monitoring; however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot techniques exist but are often confined to bulky benchtop setups or have lowspatio-spectral resolution. In this paper, we propose a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging. Our system consists of a tiled spectral filter array placed directly on the image sensor and a diffuser placed close to the sensor. Each point in the world maps to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. By solving a sparsity-constrained inverse problem, we recover the hyperspectral volume with sub-super-pixel resolution. Our hyperspectral imaging framework is flexible and can be designed with contiguous or non-contiguous spectral filters that can be chosen for a given application. We provide theory for system design, demonstrate a prototype device, and present experimental results with high spatio-spectral resolution. (C) 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据