# Correlation Plenoptic Imaging: An Overview
## 1 Introduction  
Plenoptic imaging is a recently established optical imaging technique, characterized by the possibility to simultaneously detect both the spatial distribution and the propagation direction of light in a given scene [1; 2; 3]. The ability to reconstruct light paths can be used, in post-processing, to refocus out-of-focus objects, change the point of view on the scene and extend the DOF. PI is also one of the simplest and fastest methods to obtain three-dimensional images with the current technology [4; 5; 6; 7; 8; 9; 10]; in particular, it is among the imaging methods able to achieve 3D imaging in a single shot [11; 12; 13; 14; 15]. PI does not require either multiple sensors for multiperspective acquisition, or scanning or interferometric methods; single-shot 3D imaging is instead accomplished by a simple modification of ordinary imaging devices (such as cameras and microscopes) that does not involve using multiple excitation beams [13], multifocus gratings combined with aberration corrections [14] or spatial light modulators [15]. The key component of state-of-the-art plenoptic cameras is a microlens array placed in front of the sensor to ensure that a twofold information is encoded in the intensity detected by each pixel: the distribution of light in the object plane, and the direction of light between the object and the imaging device [16; 17; 18; 19; 20]. In the first implemented configuration, the microlenses were inserted in the native image plane, and were employed to reproduce repeated images of the main camera lens on the sensor behind them [3; 21]. Light rays could thus be traced by joining each image \"point\" (i.e., each microlens) with each pixel associated with the image of the camera lens. To this end, the camera lens is divided in \(N_{u}\) portions per side; hence, each portion of the camera lens has linear size \(D/N_{u}\), with \(D\) the lens diameter, and reproduces a \"sub-image\" of the scene. Sub-images are clearly endowed with a larger DOF than the ordinary image reproduced by the whole camera lens; this explains the physical origin of the improved DOF of plenoptic imaging. In addition, the sub-image formed by eachportion of the camera lens offers a different perspective on the scene of interest, as required for 3D imaging. The drawback of these intriguing peculiarities of standard PI is the loss of spatial resolution, which is now defined by the transverse size of the microlenses: resolution worsens by the same factor \(N_{u}\) that fixes directional resolution. Hence, the potentials of plenoptic imaging are strongly limited by the insertion of the microlens array and the use of a single sensor for retrieving both spatial and directional information. Despite its limitation, PI is currently employed in the most diverse applications, including 3D imaging and sensing [5; 22], stereoscopy [2; 23; 24], particle image velocimetry [25], particle tracking and sizing [26], wavefront sensing [6; 27; 28; 29], microscopy [4; 6; 11; 30] and digital cameras with refocusing capabilities [31]. Plenoptic imaging has also been employed in surgical robotics [32], endoscopic applications [33], and blood-flow visualization [34]. In a more recent scheme, called Plenoptic 2.0, the microlenses create redundant images of portions of the scene of interest, in order to somewhat smoothen the compromise between loss of resolution and increased DOF [16; 17; 18; 19]. Attempts to weaken the resolution vs. DOF trade-off have been made by using signal processing and deconvolution [4; 6; 35; 36; 37], and other algorithms and analysis tools have been developed [8; 38]. In this perspective, we have recently proposed a fundamentally different approach to PI, named correlation plenoptic imaging (CPI), which exploits the spatio-temporal correlation properties of light beams to physically decouple the image formation from the retrieval of the directional information [39].