Fast depth estimation with cost minimization for structured light field

Abstract

Depth estimation is a fundamental task in light field (LF) related applications. However, conventional light field suffers from the lack of features, which introduces depth ambiguity and heavy computation load to depth estimation. In this paper, we introduce phase light field (PLF), which uses sinusoidal fringes as patterns and the latent phases as the codes. With PLF and the re-formatted phase-epipolar-plane-images (phase EPIs), a global cost minimization framework is proposed to estimate the depth. In general, EPI-based depth estimation tests a set of candidate lines to find the optimal one with most similar intensities, and the slope of the optimal line is converted to disparity and depth. Based on this principle, for phase-EPI, we propose a cost with weighted phase variance in the candidate line, and we prove that the cost is a convex function. After that, the beetle antennae search (BAS) optimization algorithm is utilized to find the optimal line and thus depth can be obtained. Finally, a bilateral filter is incorporated to further improve the depth quality. Simulation and real experimental results demonstrate that, the proposed method can produce accurate depth maps, especially at boundary regions. Moreover, the proposed method achieves an acceleration of about 5.9 times over the state-of-the-art refocus method with comparable depth quality, and thus can facilitate practical applications.