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664
Sparse Reconstruction by Separable Approximation
, 2007
"... Finding sparse approximate solutions to large underdetermined linear systems of equations is a common problem in signal/image processing and statistics. Basis pursuit, the least absolute shrinkage and selection operator (LASSO), wavelet-based deconvolution and reconstruction, and compressed sensing ..."
Abstract
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Cited by 373 (38 self)
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of minimizing the sum of a smooth convex function and a nonsmooth, possibly nonconvex, sparsity-inducing function. We propose iterative methods in which each step is an optimization subproblem involving a separable quadratic term (diagonal Hessian) plus the original sparsity-inducing term. Our approach
Curvelet-Wavelet Regularized Split Bregman Iteration for Compressed Sensing
"... Compressed sensing is a new concept in signal processing. Assuming that a signal can be represented or approximated by only a few suitably chosen terms in a frame expansion, compressed sensing allows to recover this signal from much fewer samples than the Shannon-Nyquist theory requires. Many images ..."
Abstract
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Cited by 119 (6 self)
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that they can be understood as special cases of the Douglas-Rachford Split algorithm. Numerical experiments for compressed sensing based Fourier-domain random imaging show good performances of the proposed curvelet-wavelet regularized split Bregman (CWSpB) methods,whereweparticularlyuseacombination of wavelet
ITERATIVELY REGULARIZED GAUSS-NEWTON METHOD FOR ATMOSPHERIC REMOTE SENSING APPLIED TO MIPAS AND SCIAMACHY LIMB SOUNDING OBSERVATIONS
"... In this paper we present a retrieval algorithm for atmospheric remote sensing. The algorithm combines the Tikhonov regularization and the iteratively Gauss–Newton method and is devoted to the solution of multi–parameter inverse problems with simple bounds on the variables. The basic features of the ..."
Abstract
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Cited by 5 (3 self)
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In this paper we present a retrieval algorithm for atmospheric remote sensing. The algorithm combines the Tikhonov regularization and the iteratively Gauss–Newton method and is devoted to the solution of multi–parameter inverse problems with simple bounds on the variables. The basic features
Regularizing method for the determination of the backscatter cross section in lidar data SIGNALS
- Optical Society of America
, 2009
"... The retrieval of the backscatter cross section in lidar data is of great interest in remote sensing. For the numerical calculation of the backscatter cross section, a deconvolution has to be performed; its determination is therefore an ill-posed problem. Most of the common techniques, such as the w ..."
Abstract
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Cited by 2 (0 self)
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The retrieval of the backscatter cross section in lidar data is of great interest in remote sensing. For the numerical calculation of the backscatter cross section, a deconvolution has to be performed; its determination is therefore an ill-posed problem. Most of the common techniques
Building boundary tracing and regularization from airborne LiDAR point clouds, Photogrammetric Engineering and Remote Sensing,
, 2007
"... ..."
Bregman iterative algorithms for ℓ1-minimization with applications to compressed sensing
- SIAM J. IMAGING SCI
, 2008
"... We propose simple and extremely efficient methods for solving the basis pursuit problem min{‖u‖1: Au = f,u ∈ R n}, which is used in compressed sensing. Our methods are based on Bregman iterative regularization, and they give a very accurate solution after solving only a very small number of 1 insta ..."
Abstract
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Cited by 84 (15 self)
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We propose simple and extremely efficient methods for solving the basis pursuit problem min{‖u‖1: Au = f,u ∈ R n}, which is used in compressed sensing. Our methods are based on Bregman iterative regularization, and they give a very accurate solution after solving only a very small number of 1
Article Automatic Vehicle Extraction from Airborne LiDAR Data Using an Object-Based Point Cloud Analysis Method
, 2014
"... remote sensing ..."
Article Shiftable Leading Point Method for High Accuracy Registration of Airborne and Terrestrial LiDAR Data
"... remote sensing ..."
Article A Thin Plate Spline-Based Feature-Preserving Method for Reducing Elevation Points Derived from LiDAR
, 2015
"... remote sensing ..."
Article An Effective Method for Detecting Potential Woodland Vernal Pools Using High-Resolution LiDAR Data and Aerial Imagery
, 2014
"... remote sensing ..."
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