Segmentation of light field image with the structure tensor

We propose a segmentation model for light field images based on superpixels segmentation and graph-cuts algorithm. Unlike traditional images, which do not offer information for different directions, a light field image encodes space data which can be computed on its epipolar plane images (EPI) with some effective methods. In our work, we analyze the structure of EPI and research the computational process of disparity using EPI. On this basis, we present a new method for computing disparity using the modified structure tensor on EPIs. We further apply the computed disparity labels by fusing RGB images and disparity labels to obtain more detailed over-segmentation. Meanwhile, the modified structure tensor algorithm is used to get more accurate image boundaries, which plays a role in computing disparity features. All these processes are applied in an interactive segmentation model. Our experiments on public data sets demonstrate that the proposed light field image segmentation achieves a higher performance compared with state-of-the-art methods.