A Study of Efficient Light Field Subsampling and Reconstruction Strategies
This work addresses a domain-specific problem for light field applications like compression and camera design, but it is incremental as it builds on existing methods without introducing new paradigms.
The paper tackled the problem of limited angular resolution in light fields by studying subsampling and reconstruction strategies, evaluating them on real-world and synthetic datasets to devise optimal selection strategies.
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.