Open AccessAdvanced light-field refocusing through tomographic modeling of the photographed scene
Author(s) -
Nicola Viganò,
Pablo Martínez Gil,
Charlotte Herzog,
Ombeline de La Rochefoucauld,
Robert van Liere,
Kees Joost Batenburg
Publication year - 2019
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.27.007834
Subject(s) - optics , point spread function , tomographic reconstruction , depth of field , computer science , tomography , light field , regularization (linguistics) , computer vision , iterative reconstruction , artificial intelligence , physics
Recently we have shown that light-field photography images can be interpreted as limited-angle cone-beam tomography acquisitions. Here, we use this property to develop a direct-space tomographic refocusing formulation that allows one to refocus both unfocused and focused light-field images. We express the reconstruction as a convex optimization problem, thus enabling the use of various regularization terms to help suppress artifacts, and a wide class of existing advanced tomographic algorithms. This formulation also supports super-resolved reconstructions and the correction of the optical system's limited frequency response (point spread function). We validate this method with numerical and real-world examples.