A spatio-angular filter for high quality sparse light field refocusing

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Abstract

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.

This paper has been accepted at the Second ICME Workshop on Hyper-Realistic Multimedia for Enhanced Quality of Experience 2021. You can watch the presentation below.

Implementation

The code will soon be available.

Presentation

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