Izvorni znanstveni članak
https://doi.org/10.1080/00051144.2020.1715582
Overcoming spatio-angular trade-off in light field acquisition using compressive sensing
Nicol Dlab
; Department of Electronic Systems and Information Processing, University of Zagreb Faculty of Electrical Engineering and Computing, Zagreb, Croatia
Filip Cimermančić
; Department of Electronic Systems and Information Processing, University of Zagreb Faculty of Electrical Engineering and Computing, Zagreb, Croatia
Ivan Ralašić
; Department of Electronic Systems and Information Processing, University of Zagreb Faculty of Electrical Engineering and Computing, Zagreb, Croatia
Damir Seršić
; Department of Electronic Systems and Information Processing, University of Zagreb Faculty of Electrical Engineering and Computing, Zagreb, Croatia
Sažetak
In contrast to conventional cameras which capture a 2D projection of a 3D scene by integrating the angular domain, light field cameras preserve the angular information of individual light rays by capturing a 4D light field of a scene. On the one hand, light field photography enables powerful post-capture capabilities such as refocusing, virtual aperture, depth sensing and perspective shift. On the other hand, it has several drawbacks, namely, high-dimensionality of the captured light fields and a fundamental trade-off between spatial and angular resolution in the camera design. In this paper, we propose a compressive sensing approach to light field acquisition from a sub-Nyquist number of samples. Using an off-the-shelf measurement setup consisting of a digital projector and a Lytro Illum light field camera, we demonstrate the efficiency of the compressive sensing approach by improving the spatial resolution of the acquired light field. This paper presents a proof of concept with a simplified 3D scene as the scene of interest. Results obtained by the proposed method show significant improvement in the spatial resolution of the light field as well as preserved post-capture capabilities.
Ključne riječi
Compressive sensing (CS); light field; camera; projector; measurement setup; sparse optimization
Hrčak ID:
239868
URI
Datum izdavanja:
16.3.2020.
Posjeta: 1.094 *