Current computational methods for light field photography model the ray-tracing geometry inside the plenoptic camera. This representation of the problem, and some common approximations, can lead to errors in the estimation of object sizes and positions. We propose a representation that leads to the correct reconstruction of object sizes and distances to the camera, by showing that light field images can be interpreted as limited angle cone-beam tomography acquisitions. We then quantitatively analyze its impact on image refocusing, depth estimation and volumetric reconstructions, comparing it against other possible representations. Finally, we validate these results with numerical and real-world examples.

Plenoptic cameras provide single-shot 3D imaging capabilities, based on the acquisition of the Light-Field, which corresponds to a spatial and directional sampling of all the rays of a scene reaching a detector. Specific algorithms applied on raw Light-Field data allow for the reconstruction of an object at different depths of the scene.Two different plenoptic imaging geometries have been reported, associated with two reconstruction algorithms: the traditional or unfocused plenoptic camera, also known as plenoptic camera 1.0, and the focused plenoptic camera, also called plenoptic camera 2.0. Both systems use the same optical elements, but placed at different locations: a main lens, a microlens array and a detector. These plenoptic systems have been presented as independent. Here we show the continuity between them, by simply moving the position of an object. We also compare the two reconstruction methods. We theoretically show that the two algorithms are intrinsically based on the same principle and could be applied to any LightField data. However, the resulting images resolution and quality depend on the chosen algorithm.

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.

A focused plenoptic camera has the ability to record and separate spatial and directional information of the incoming light. Combined with the appropriate algorithm, 3D scene could be reconstructed from a single acquisition, over a depth range called plenoptic Depthof-Field. In this article, we study the contrast variations with depth as a way to assess plenoptic Depth-of-Field. We take into account the impact of diffraction, defocus and, magnification on the resulting contrast. We measure the contrast directly on both simulated and acquired images. We demonstrate the importance of diffraction and magnification in the final contrast. Contrary to classical optics, the maximum of contrast is not centered around the main object plane, but around a shifted position, with a fast and non-symmetric decrease of contrast.

X-ray computed tomography (CT) is an invaluable technique for generating three-dimensional (3D) images of inert or living specimens. X-ray CT is used in many scientific, industrial, and societal fields. Compared to conventional 2D X-ray imaging, CT requires longer acquisition times because up to several thousand projections are required for reconstructing a single high-resolution 3D volume. Plenoptic imaging—an emerging technology in visible light field photography—highlights the potential of capturing quasi-3D information with a single exposure. Here, we show the first demonstration of a flexible plenoptic microscope operating with hard X-rays; it is used to computationally reconstruct images at different depths along the optical axis. The experimental results are consistent with the expected axial refocusing, precision, and spatial resolution. Thus, this proof-of-concept experiment opens the horizons to quasi-3D X-ray imaging, without sample rotation, with spatial resolution of a few hundred nanometres.