Title :
A sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing
Author :
Lorenz, Dirk A. ; Wenger, Stephan ; Schopfer, Frank ; Magnor, Marcus
Author_Institution :
Inst. for Anal. & Algebra, Tech. Univ. Braunschweig, Braunschweig, Germany
Abstract :
An algorithmic framework to compute sparse or minimal-TV solutions of linear systems is proposed. The framework includes both the Kaczmarz method and the linearized Bregman method as special cases and also several new methods such as a sparse Kaczmarz solver. The algorithmic framework has a variety of applications and is especially useful for problems in which the linear measurements are slow and expensive to obtain. We present examples for online compressed sensing, TV tomographic reconstruction and radio interferometry.
Keywords :
compressed sensing; linear systems; TV tomographic reconstruction; linear measurements; linear systems; linearized Bregman method; minimal-TV solutions; online compressed sensing; radio interferometry; sparse Kaczmarz solver; Compressed sensing; Convergence; Image reconstruction; Imaging; Linear systems; Signal processing algorithms; Sparse matrices; Kaczmarz method; Sparse solutions; compressed sensing; linearized Bregman method; radio inter-ferometry;
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
DOI :
10.1109/ICIP.2014.7025269
