Improving depth estimation from a plenoptic camera by patterned illumination

Plenoptic (light-field) imaging is a technique that allows a simple CCD-based imaging device to acquire both spatially and angularly resolved information about the “light-field” from a scene. It requires a microlens array to be placed between the objective lens and the sensor of the imaging device1 and the images under each microlens (which typically span many pixels) can be computationally post-processed to shift perspective, digital refocus, extend the depth of field, manipulate the aperture synthetically and generate a depth map from a single image. Some of these capabilities are rigid functions that do not depend upon the scene and work by manipulating and combining a well-defined set of pixels in the raw image. However, depth mapping requires specific features in the scene to be identified and registered between consecutive microimages. This process requires that the image has sufficient features for the registration, and in the absence of such features the algorithms become less reliable and incorrect depths are generated. The aim of this study is to investigate the generation of depth-maps from light-field images of scenes with insufficient features for accurate registration, using projected patterns to impose a texture on the scene that provides sufficient landmarks for the registration methods.