27 September 2011 Mismatch and resolution in compressive imaging
Author Affiliations +
Abstract
Highly coherent sensing matrices arise in discretization of continuum problems such as radar and medical imaging when the grid spacing is below the Rayleigh threshold as well as in using highly coherent, redundant dictionaries as sparsifying operators. Algorithms (BOMP, BLOOMP) based on techniques of band exclusion and local optimization are proposed to enhance Orthogonal Matching Pursuit (OMP) and deal with such coherent sensing matrices. BOMP and BLOOMP have provably performance guarantee of reconstructing sparse, widely separated objects independent of the redundancy and have a sparsity constraint and computational cost similar to OMP's. Numerical study demonstrates the effectiveness of BLOOMP for compressed sensing with highly coherent, redundant sensing matrices.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Albert Fannjiang, Albert Fannjiang, Wenjing Liao, Wenjing Liao, "Mismatch and resolution in compressive imaging", Proc. SPIE 8138, Wavelets and Sparsity XIV, 81380Y (27 September 2011); doi: 10.1117/12.892434; https://doi.org/10.1117/12.892434
PROCEEDINGS
9 PAGES


SHARE
RELATED CONTENT


Back to Top