Five-Dimensional Depth-Velocity Filtering for Enhancing Moving Objects in Light Field Videos
Five-dimensional (5-D) light field video (LFV) (also known as plenoptic video) is a more powerful form of representing information of dynamic scenes compared to conventional three-dimensional (3-D) video. In this paper, the 5-D spectrum of an object in an LFV is derived for the important practical case of objects moving with constant velocity and at constant depth.
In particular, it is shown that the region of support (ROS) of the 5-D spectrum is a skewed 3-D hyperfan in the 5-D frequency domain, with the degree of skew depending on the velocity and depth of the moving object. Based on this analysis, a 5-D depth-velocity digital filter to enhance moving objects in LFVs is proposed, described and implemented. Further, by means of the commercially available Lytro light-field camera, LFVs of real scenes are generated and used to test and confirm the performance of the 5-D depth-velocity filters for enhancing such objects.