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