Reflection removal based on single light field capture

Yun Ni, Jie Chen, Lap-Pui Chau

Abstract: Photography through reflective surfaces suffers from the obstruction of reflections, which deteriorates the visibility of background targets and causes challenges for subsequent computer vision applications. In this paper, we propose a novel reflection removal algorithm using light field (LF) cameras. Unlike conventional cameras, LF cameras capture extra directional information of incoming rays which enable our algorithm to remove reflections with only a single shot. We analyze the optical geometry of the background and reflection imagery in a LF camera, and generalize a set of rules that could facilitate our algorithm to differentiate the edges from different optical sources. We show that the proposed method produces significantly better reflection removal results based on the LF data as compared to traditional methods based on multiple-shot image sequences as input.