Open AccessPreconditioning for multiplexed imaging with spatially coded PSFs
Author(s) -
Ryoichi Horisaki,
Jun Tanida
Publication year - 2011
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.19.012540
Subject(s) - preconditioner , tikhonov regularization , multiplexing , computer science , iterative method , compressed sensing , convolution (computer science) , algorithm , iterative reconstruction , optics , matrix (chemical analysis) , regularization (linguistics) , computer vision , artificial intelligence , inverse problem , physics , mathematics , materials science , telecommunications , mathematical analysis , artificial neural network , composite material
We propose a preconditioning method to improve the convergence of iterative reconstruction algorithms in multiplexed imaging based on convolution-based compressive sensing with spatially coded point spread functions (PSFs). The system matrix is converted to improve the condition number with a preconditioner matrix. The preconditioner matrix is calculated by Tikhonov regularization in the frequency domain. The method was demonstrated with simulations and an experiment involving a range detection system with a grating based on the multiplexed imaging framework. The results of the demonstrations showed improved reconstruction fidelity by using the proposed preconditioning method.