Sampling and processing for compressive holography [Invited].

TitleSampling and processing for compressive holography [Invited].
Publication TypeJournal Article
Year of Publication2011
AuthorsS Lim, DL Marks, and DJ Brady
JournalApplied Optics
Start PageH75
PaginationH75 - H86
Date Published12/2011

Compressive holography applies sparsity priors to data acquired by digital holography to infer a small number of object features or basis vectors from a slightly larger number of discrete measurements. Compressive holography may be applied to reconstruct three-dimensional (3D) images from two-dimensional (2D) measurements or to reconstruct 2D images from sparse apertures. This paper is a tutorial covering practical compressive holography procedures, including field propagation, reference filtering, and inverse problems in compressive holography. We present as examples 3D tomography from a 2D hologram, 2D image reconstruction from a sparse aperture, and diffuse object estimation from diverse speckle realizations.

Short TitleApplied Optics