Traditional spectral imagers
require 2-dimensional detectors. We present a new method to implement spectral
imagers with linear detector imager systems based on spectrum compressed. Using
1-dimension detectors instead of 2-dimension detectors to get 3-dimensional
data cubes, the spectral imagers could get both the spectral information and
the spatial information of each ground object. By the method of characteristics
decoupling, we make high precision reconstruction of compressed data.
Theoretical analysis and simulations show that it not only ensures the imaging
quality but also reduces the dimension of the detectors and complexity of
imaging system greatly.
References
[1]
Shen, Z. (2002) The Principle of the Spaceborne Hyperspectrum Imager. Spacecraft Recovery& Remote Sensing, 23, 28-34.
[2]
Arguello, H. and Arce, G.R. (2011) Code Aperture Agile Spectral Imaging (CAASI). OSA Optics and Photonics Congress, 978-1-55752-914-5.
[3]
Arguello, H., Ye, P. and Arce, G.R. (2010) Spectral Aperture Code Design for Multi-Shot Compressive Spectral Imaging. OSA Optics & Photonics Congress, 978-1-55752-887-2.
Bioucas-Dias, J.M. and Figueiredo, M.A. (2007) A New TWIST: Two-Step Iterative Shrinkage, Thresholding Algorithms for Image Restoration. IEEE Trans Image Process, 16, 2992-3004.
http://dx.doi.org/10.1109/TIP.2007.909319