Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 7834-7856 |
| Number of pages | 23 |
| Journal | Optics Express |
| Volume | 27 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 1 Jun 2019 |
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Advanced light-field refocusing through tomographic modeling of the photographed scene. / Viganò, Nicola (Corresponding author); Gil, Pablo Martínez; Herzog, Charlotte; de la Rochefoucauld, Ombeline; van Liere, Robert ; Batenburg, Kees Joost.
In: Optics Express, Vol. 27, No. 6, 01.06.2019, p. 7834-7856.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Advanced light-field refocusing through tomographic modeling of the photographed scene
AU - Viganò, Nicola
AU - Gil, Pablo Martínez
AU - Herzog, Charlotte
AU - de la Rochefoucauld, Ombeline
AU - van Liere, Robert
AU - Batenburg, Kees Joost
PY - 2019/6/1
Y1 - 2019/6/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85063471285&partnerID=8YFLogxK
U2 - 10.1364/OE.27.007834
DO - 10.1364/OE.27.007834
M3 - Article
C2 - 31052612
AN - SCOPUS:85063471285
VL - 27
SP - 7834
EP - 7856
JO - Optics Express
JF - Optics Express
SN - 1094-4087
IS - 6
ER -