| 高光谱成像与应用技术发展 |
| Hyperspectral Imaging and Application Technology Development |
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| 中文摘要: |
| 介绍了高光谱成像的需求应用、光谱成像技术的现状与发展。高光谱成像已在产品分选、精准农业、环境监测、文物保护、刑事侦查、伪装识别等行业得到应用。但传统的棱镜光栅色散型、连续可调谐滤光型、傅里叶变换干涉型等光谱成像分光方式成本高、体积大、速度慢，目前仍主要作为研究设备。为促进产业化应用，需要发展体积小、成本低、速度快的光谱成像技术。计算层析、压缩编码、胶体量子点CQDs光谱成像技术仍需理论突破，短时间难以实用。积分视场、离散采样光谱成像技术原理简单、技术成熟，可用于空间分辨率要求不高的场合。复眼滤光式、像素滤光式光谱成像技术通过单片集成像素级滤光片，既能在权衡光谱分辨率与空间分辨率的基础上实现实时性，又能极大地减小体积、降低成本。 |
| 英文摘要: |
| The hyperspectral industry application, hyperspectral imaging technology and its development are introduced. Hyperspectral imaging data has been used in product sorting, precision agriculture, environmental monitoring, cultural relics preservation, criminal investigation, camouflage identification and other industries. However, the traditional spectroscopic imaging methods, such as prism grating dispersion, continuous tunable filter and Fourier transform interferometry, are still mainly used as scientific research equipment because of their high cost, large volume and slow speed. To promote massive industrial application, spectral imaging technology with compact size, low cost and fast speed is needed. Computational tomography, compressive coding and CQDs (colloidal quantum dots) spectral imaging still need theoretical breakthroughs and are difficult to be applied in a short time. The integral field unit and the discrete sampling spectral imaging technology are simple in principle and mature in technology, which can be used in the occasion of low spatial resolution requirements. The compound-eye filter and the pixel filter spectral imaging technology can achieve real-time performance on the basis of balancing spectral resolution and spatial resolution through a single integrated pixel filter, and can greatly reduce volume and cost. |
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| 中文关键词: 高光谱成像 光谱检测识别 产业应用 光谱分光方式 傅里叶变换光谱仪 实时快照式光谱仪 |
| 英文关键词:hyperspectral imaging spectral detection and recognition industry applications spectrum-dividing techniques fourier transform spectrometer real-time snapshot spectrometer |
| 基金项目: |
| DOI：10.11823/j.issn.1674-5795.2019.04.03 |
| 引用本文：高泽东1,2，郝群1，刘宇2,1，朱院院2，曹杰1，孟合民2，刘杰2，程洪亮2.高光谱成像与应用技术发展[J].计测技术,2019,39(4):. |
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