Light field imaging involves capturing both angular and spatial distribution of light; it enables new capabilities, such as post-capture digital refocusing, camera aperture adjustment, perspective shift, and depth estimation. Micro-lens array (MLA)-based light field cameras provide a cost-effective approach to light field imaging. There are two main limitations of MLA-based light field cameras: low spatial resolution and narrow baseline. While low spatial resolution limits the general purpose use and applicability of light field cameras, narrow baseline limits the depth estimation range and accuracy. In this paper, we present a hybrid stereo imaging system that includes a light field camera and a regular camera. The hybrid system addresses both spatial resolution and narrow baseline issues of the MLA-based light field cameras while preserving light field imaging capabilities.
Alternative to the standard MLA-based light field camera design @cite_14 , where the MLA is placed at the image plane of the main lens and the sensor is placed at the focal length of the lenslets, there is another design approach where the MLA is placed to relay image from the intermediate image plane of the main lens to the sensor @cite_29 . This design is known as focused plenoptic camera.'' As in the case of the standard light field camera approach, super-resolution restoration for focused plenoptic cameras is also possible @cite_24 .
@cite_24 @cite_29 @cite_14
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Ordinary cameras gather light across the area of their lens aperture, and the light striking a given subregion of the aperture is structured somewhat differently than the light striking an adjacent subregion. By analyzing this optical structure, one can infer the depths of the objects in the scene, i.e. one can achieve single lens stereo. The authors describe a camera for performing this analysis. It incorporates a single main lens along with a lenticular array placed at the sensor plane. The resulting plenoptic camera provides information about how the scene would look when viewed from a continuum of possible viewpoints bounded by the main lens aperture. Deriving depth information is simpler than in a binocular stereo system because the correspondence problem is minimized. The camera extracts information about both horizontal and vertical parallax, which improves the reliability of the depth estimates. > Current methodologies for the generation of 3D point cloud from real world scenes rely upon a set of 2D images capturing the scene from several points of view. Novel plenoptic cameras sample the light field crossing the main camera lens creating a light field image. The information available in a plenoptic image must be processed in order to render a view or create the depth map of the scene. This paper analyses a method for the reconstruction of 3D models. The reconstruction of the model is obtained from a single image shot. Exploiting the properties of plenoptic images, a point cloud is generated and compared with a point cloud of the same object but generated with a different plenoptic camera. Plenoptic images are one type of light field contents produced by using a combination of a conventional camera and an additional optical component in the form of microlens arrays, which are positioned in front of the image sensor surface. This camera setup can capture a sub-sampling of the light field with high spatial fidelity over a small range, and with a more coarsely sampled angle range. The earliest applications that leverage on the plenoptic image content is image refocusing, non-linear distribution of out-of-focus areas, SNR vs. resolution trade-offs, and 3D-image creation. All functionalities are provided by using post-processing methods. In this work, we evaluate a compression method that we previously proposed for a different type of plenoptic image (focused or plenoptic camera 2.0 contents) than the unfocused or plenoptic camera 1.0 that is used in this Grand Challenge. The method is an extension of the state-of-the-art video compression standard HEVC where we have brought the capability of bi-directional inter-frame prediction into the spatial prediction. The method is evaluated according to the scheme set out by the Grand Challenge, and the results show a high compression efficiency compared with JPEG, i.e., up to 6 dB improvements for the tested images. Plenoptic cameras are a promising solution to increase the capabilities of current commercial cameras because they capture the four-dimensional lightfield of a scene. Processing the recorded lightfield, these cameras offer the possibility of focusing the scene after the shot or obtaining 3D information. Conventional photographs focused on determined planes can be obtained through projections of the four-dimensional lightfield onto two spatial dimensions. These photographs can be efficiently computed using the Fourier Slice technique but their resolution is usually less than 1 of the full resolution of the camera sensor. Several super-resolution methods have been recently developed to increase the spatial resolution of plenoptic cameras. In this paper we propose a new super-resolution method based on the Fourier Slice technique. We show how several existing super-resolution methods can be seen as particular cases of this approach. Besides the theoretical interest of this unified view, we also show how to obtain simultaneously spatial and depth super-resolution removing the limitations of previous approaches.