Paper Info
Title
A Data-Adaptive Compressed Sensing Approach to Polarimetric SAR Tomography of Forested Areas
Abstract
Super-resolution imaging via compressed sensing (CS)-based spectral estimators has been recently introduced to synthetic aperture radar (SAR) tomography. In the case of partial scatterers, the mainstream has so far been twofold, in that the tomographic reconstruction is conducted by either directly working with multiple looks and/or polarimetric channels or by exploiting the corresponding single-channel second-order statistics. In this letter, we unify these two methodologies in the context of covariance fitting. In essence, we exploit the fact that both vertical structures and the unknown polarimetric signatures can be approximated in a low-dimensional subspace. For this purpose, we make use of a wavelet basis in order to sparsely represent vertical structures. Additionally, we synthesize a data-adaptive orthonormal basis that spans the space of polarimetric signatures. Finally, we validate this approach by using fully polarimetric L-band data acquired by the E-SAR sensor of the German Aerospace Center (DLR).
Year
DOI
Venue
2013
10.1109/LGRS.2012.2212693
Geoscience and Remote Sensing Letters, IEEE
Keywords
Field
DocType
data compression,forestry,geophysical signal processing,radar polarimetry,remote sensing by radar,signal reconstruction,synthetic aperture radar,tomography,vegetation mapping,wavelet transforms,DLR,E-SAR sensor,German Aerospace Center,compressed sensing based spectral estimators,covariance fitting,data adaptive compressed sensing approach,data adaptive orthonormal basis,forested areas,fully polarimetric L-band data,low dimensional subspace,multiple looks,multiple polarimetric channels,partial scatterers,polarimetric SAR tomography,single channel second order statistics,superresolution imaging,synthetic aperture radar,tomographic reconstruction,unknown polarimetric signatures,vertical structures,wavelet basis,Distributed compressed sensing (DCS),Kronecker basis,polarimetry,synthetic aperture radar (SAR) tomography,wavelets
Iterative reconstruction,Computer vision,Tomographic reconstruction,Polarimetry,Synthetic aperture radar,Remote sensing,Orthonormal basis,Artificial intelligence,Compressed sensing,Mathematics,Wavelet transform,Wavelet
Journal
Volume
Issue
ISSN
10
3
1545-598X
Citations 
PageRank 
References 
10
0.57
12
Authors
3
Name
Order
Citations
PageRank
Esteban Aguilera1281.44
Matteo Nannini214315.30
Andreas Reigber367070.53