Title
Snapshot Spectral Imaging Via Compressive Random Convolution
Abstract
Spectral imaging is of interest in many applications, including wide-area airborne surveillance, remote sensing, and tissue spectroscopy. Coded aperture spectral snapshot imaging (CASSI) provides an efficient mechanism to capture a 3D spectral cube with a single shot 2D measurement. CASSI uses a focal plane array (FPA) measurement of a spectrally dispersed, aperture coded, source. The spectral cube is then attained using a compressive sensing reconstruction algorithm. In this paper, we explore a new approach referred to as random convolution snapshot spectral imaging (RCSSI). It is based on FPA measurements of spectrally dispersed coherent sources that have been randomly convoluted by a spatial light modulator. The new method, based on the theory of compressive sensing via random convolutions, is shown to outperform traditional CASSI systems in terms of PSNR spectral image cube reconstructions.
Year
DOI
Venue
2011
10.1109/ICASSP.2011.5946769
2011 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING
Keywords
Field
DocType
Compressed spectral imaging, coherent illumination, compressed sensing, multispectral imaging
Aperture,Iterative reconstruction,Computer vision,Full spectral imaging,Spectral imaging,Coded aperture,Convolution,Computer science,Multispectral image,Reconstruction algorithm,Artificial intelligence
Conference
ISSN
Citations 
PageRank 
1520-6149
1
0.35
References 
Authors
4
2
Name
Order
Citations
PageRank
Yao Wu13412.69
Gonzalo R. Arce21061134.94