Iterative reconstruction of scene depth with fidelity based on light field data

Depth reconstruction from the light field, as a depth extracting approach, is a vibrant research field in computational imaging. In this paper, depth reconstruction from the light field was approached as an optimization problem by analyzing the forward and inverse models. The forward and inverse models present the connection between the light field and the depth of the scene. We proposed an iterative method for scene depth reconstruction with fidelity from 4D light field data. The objective function of the optimization problem entails three terms, of which the matching term is used as the fidelity term, while the gradient term and classification term constitute the penalty terms. The iterative method minimized the objective function by correcting mismatching pixels iteratively. In this way, the reconstruction accuracy of the scene depth was significantly improved with high robustness, especially in the weak texture and occlusion regions. The experimental results show that the depth map can be reconstructed with high accuracy by the iterative method, in alignment with high depth resolution in the weak texture and occlusion regions. An accurate 3D surface in the field of view can be achieved using the depth information reconstructed from the 4D light field.