Efficient Propagation of Light Field Edits

Abstract

Light field editing is a complex task, due to the large amount of data and the need to keep consistency between views. This has hampered the creation of efficient edit propagation methods, similar to those existing for single images. We propose a framework to edit light fields at interactive rates, by propagating some sparse user edits in the full light field. This propagation is guided by a novel affinity function, which forces similar pixels (defined by our affinity space) to receive similar edits, thus ensuring consistency. To manage the light field's large amount of data, we propose a novel multi-dimensional downsampling technique: we first cluster pixels with high affinity, and then perform edit propagation over the downsampled data. We finally upsample back to the original full resolution, maintaining visual fidelity and view consistency between views.