A Study of Efficient Light Field Subsampling and Reconstruction Strategies

TL;DR

This paper investigates various subsampling and reconstruction strategies for light fields to address limited angular resolution, evaluating their effectiveness on real and synthetic datasets to inform future applications.

Contribution

It systematically compares different light field subsampling methods and proposes optimal strategies for view reconstruction and sampling.

Findings

Row-wise and column-wise sampling strategies analyzed

Reconstruction methods effectively generate intermediate views

Optimal sampling strategies improve angular resolution

Abstract

Limited angular resolution is one of the main obstacles for practical applications of light fields. Although numerous approaches have been proposed to enhance angular resolution, view selection strategies have not been well explored in this area. In this paper, we study subsampling and reconstruction strategies for light fields. First, different subsampling strategies are studied with a fixed sampling ratio, such as row-wise sampling, column-wise sampling, or their combinations. Second, several strategies are explored to reconstruct intermediate views from four regularly sampled input views. The influence of the angular density of the input is also evaluated. We evaluate these strategies on both real-world and synthetic datasets, and optimal selection strategies are devised from our results. These can be applied in future light field research such as compression, angular super-resolution, and design of camera systems.