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A Spatio-Angular Filter for High Quality Sparse Light Field Refocusing

Publication by Martin Alain, Aljosa Smolic
Related to the Smart Asset re-Use in Creative Environments (SAUCE) project
Published in 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), 2021


The ability to render synthetic depth-of-field effects post capture is a flagship application of light field imaging. However, it is known that many existing light field refocusing methods suffer from severe artefacts when applied to sparse light fields, known as angular aliasing. We propose in this paper a method for high quality sparse light field refocusing based on insights from depth-based bokeh rendering techniques. We first provide an in-depth analysis of the geometry of the defocus blur in light field refocusing by analogy with the defocus geometry in a traditional camera using the thin lens model. Based on this analysis, we propose a filter for removing angular aliasing artefacts in light field refocusing, which consists in modifying the well known shift-and-sum algorithm to apply a depth-dependent blur to the light field in between the shift and the sum operations. We show that our method can achieve significant quality improvements compared to existing approaches for a reasonable computational cost.