高光谱成像
全光谱成像
编码孔径
光谱成像
压缩传感
数据立方体
成像光谱学
计算机科学
光谱分辨率
成像光谱仪
计算机视觉
迭代重建
人工智能
遥感
分光计
光学
光圈(计算机存储器)
图像分辨率
图像质量
合成孔径雷达
物理
探测器
谱线
地质学
程序设计语言
天文
作者
Gonzalo R. Arce,David J. Brady,Lawrence Carin,Henry Argüello,David S. Kittle
出处
期刊:IEEE Signal Processing Magazine
[Institute of Electrical and Electronics Engineers]
日期:2014-01-01
卷期号:31 (1): 105-115
被引量:487
标识
DOI:10.1109/msp.2013.2278763
摘要
Imaging spectroscopy involves the sensing of a large amount of spatial information across a multitude of wavelengths. Conventional approaches to hyperspectral sensing scan adjacent zones of the underlying spectral scene and merge the results to construct a spectral data cube. Push broom spectral imaging sensors, for instance, capture a spectral cube with one focal plane array (FPA) measurement per spatial line of the scene [1], [2]. Spectrometers based on optical bandpass filters sequentially scan the scene by tuning the bandpass filters in steps. The disadvantage of these techniques is that they require scanning a number of zones linearly in proportion to the desired spatial and spectral resolution. This article surveys compressive coded aperture spectral imagers, also known as coded aperture snapshot spectral imagers (CASSI) [1], [3], [4], which naturally embody the principles of compressive sensing (CS) [5], [6]. The remarkable advantage of CASSI is that the entire data cube is sensed with just a few FPA measurements and, in some cases, with as little as a single FPA shot.
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