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.
© 2011 Optical Society of America
Datasets associated with ISP articles are stored in an online database called MIDAS. Clicking a "View" link in an OSA ISP article will launch the ISP software (if installed) and pull the relevant data from MIDAS. Visit MIDAS to browse and download the datasets directly. A package containing the PDF article and full datasets is available in MIDAS for offline viewing.
Questions or Problems? See the ISP FAQ. Already used the ISP software? Take a quick survey to tell us what you think.
Equations on this page are rendered with MathJax. Learn more.