DocumentCode :
6841
Title :
Sparsity and Structure in Hyperspectral Imaging : Sensing, Reconstruction, and Target Detection
Author :
Willett, Rebecca M. ; Duarte, Marco F. ; Davenport, Mark A. ; Baraniuk, R.G.
Author_Institution :
Electr. & Comput. Eng., Duke Univ., Durham, NC, USA
Volume :
31
Issue :
1
fYear :
2014
fDate :
Jan. 2014
Firstpage :
116
Lastpage :
126
Abstract :
Hyperspectral imaging is a powerful technology for remotely inferring the material properties of the objects in a scene of interest. Hyperspectral images consist of spatial maps of light intensity variation across a large number of spectral bands or wavelengths; alternatively, they can be thought of as a measurement of the spectrum of light transmitted or reflected from each spatial location in a scene. Because chemical elements have unique spectral signatures, observing the spectra at a high spatial and spectral resolution provides information about the material properties of the scene with much more accuracy than is possible with conventional three-color images. As a result, hyperspectral imaging is used in a variety of important applications, including remote sensing, astronomical imaging, and fluorescence microscopy.
Keywords :
geophysical image processing; hyperspectral imaging; image colour analysis; image reconstruction; remote sensing; astronomical imaging; chemical elements; fluorescence microscopy; hyperspectral imaging; image color analysis; light intensity variation; material properties; reconstruction detection; remote sensing; sensing detection; spatial location; spatial maps; spatial resolution; spectral bands; spectral resolution; spectral signatures; target detection; Hyperspectral imaging; Hyperspectral sensors; Image coding; Noise measurement; Spatial resolution;
fLanguage :
English
Journal_Title :
Signal Processing Magazine, IEEE
Publisher :
ieee
ISSN :
1053-5888
Type :
jour
DOI :
10.1109/MSP.2013.2279507
Filename :
6678233
Link To Document :
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