The acquisition of light field images with high angular resolution is costly. Although many
methods have been proposed to improve the angular resolution of a sparsely-sampled light …

Exploiting spatial-angular correlation is crucial to light field (LF) image super-resolution
(SR), but is highly challenging due to its non-local property caused by the disparities among …

A novel light field super-resolution algorithm to improve the spatial and angular resolutions
of light field images is proposed in this work. We develop spatial and angular super …

Light field images taken by plenoptic cameras often have a tradeoff between spatial and
angular resolutions. In this paper, we propose a novel spatial super-resolution approach for …

Light field (LF) images acquired by hand-held devices usually suffer from low spatial
resolution as the limited sampling resources have to be shared with the angular dimension …

The low spatial resolution of light-field image poses significant difficulties in exploiting its
advantage. To mitigate the dependency of accurate depth or disparity information as priors …

Light Field (LF) cameras are considered to have many potential applications since angular
and spatial information is captured simultaneously. However, the limited spatial resolution …

Deep learning provides a new avenue for light field super-resolution (SR). However, the
domain gap caused by drastically different light field acquisition conditions poses a main …

Light field (LF) cameras can record scenes from multiple perspectives, and thus introduce
beneficial angular information for image super-resolution (SR). However, it is challenging to …

Data augmentation (DA) is an efficient strategy for improving the performance of deep neural
networks. Recent DA strategies have demonstrated utility in single image super-resolution …