On generalized sampling for image-based rendering data

TL;DR: In this paper, the authors apply generalized sampling to image-based rendering (IBR) data, more specifically, the lightfield, and show that, in theory, the lowest sampling rate of a lightfield when they use generalized sampling can be as low as half of that when we use rectangular sampling.

Abstract: We apply generalized sampling to image-based rendering (IBR) data, more specifically, the lightfield. We show that, in theory, the lowest sampling rate of a lightfield when we use generalized sampling can be as low as half of that when we use rectangular sampling. However, in practice, rectangular sampling has several advantages over generalized sampling. We analyze the pros and cons for each sampling approach, and explain why, in practice, rectangular sampling is still preferable.