CNCS Center for Nonlinear and Complex Systems
   Search Help Login pdf version printable version

Publications [#280377] of David J. Brady

Papers Published

  1. Lim, S; Marks, DL; Brady, DJ, Sampling and processing for compressive holography [Invited]., Applied Optics, vol. 50 no. 34 (December, 2011), pp. H75-H86 [22193030], [doi]
    (last updated on 2019/11/15)

    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.