Open AccessComputer ScienceEngineeringMathematics

Yingying Li, S. Osher

2009.7.1Inverse Problems and Imaging

DOI: 10.3934/ipi.2009.3.487

tlooto Summary

This work proposes a fast algorithm for solving the Basis Pursuit problem, min u, and claims that in combination with a Bregman iterative method, this algorithm will achieve a solution with speed and accuracy competitive with some of the leading methods for the basis pursuit problem.

Abstract

We propose a fast algorithm for solving the Basis Pursuit problem, min u $\{|u|_1\: \Au=f\}$, which has application to compressed sensing. We design an efficient method for solving the related unconstrained problem min u $E(u) = |u|_1 + \lambda \||Au-f\||^2_2$ based on a greedy coordinate descent method. We claim that in combination with a Bregman iterative method, our algorithm will achieve a solution with speed and accuracy competitive with some of the leading methods for the basis pursuit problem.

Citation format

LI, Yingying; OSHER, S. Coordinate descent optimization for l 1 minimization with application to compressed sensing; a greedy algorithm. Inverse Problems and Imaging, 2009, 3: 487–503.