Open AccessFeasibility study for compressive multi-dimensional integral imaging
Author(s) -
Ryoichi Horisaki,
Xiao Xiao,
Jun Tanida,
Bahram Javidi
Publication year - 2013
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.21.004263
Subject(s) - integral imaging , compressed sensing , computer science , computer vision , spectral imaging , optics , polarimetry , synthetic aperture radar , iterative reconstruction , artificial intelligence , pixel , physics , image (mathematics) , scattering
This paper describes a generalized framework for single-exposure acquisition of multi-dimensional scene information using integral imaging system based on compressive sensing. In the proposed system, a multi-dimensional scene containing a plurality of information such as 3D coordinates, spectral and polarimetric data is captured by integral imaging optics. The image sensor uses pixel-wise filtering elements arranged randomly. The multi-dimensional original object is reconstructed using an algorithm with a sparsity constraint. The proposed system is demonstrated with simulations and feasible optical experiments based on synthetic aperture integral imaging using multi-dimensional objects including 3D coordinates, spectral, and polarimetric information.