Anti-occlusion light field depth estimation guided by Gini cost volume

The light field camera can record multi-view information of a three-dimensional scene within one shot, which possesses unique advantage especially in depth estimation. However, the accuracy of the depth information extracted by the existing depth estimation method is significantly reduced when there is complex occlusion in the scene. Aiming at this problem, a method for estimating the depth of anti-occlusion light field based on Gini cost volume is proposed. Firstly, the refocusing images are obtained using the light field refocusing algorithm. Then, the Gini cost volume of the central view and other views are constructed. The initial depth map is calculated according to the principle of minimum cost volume. Finally, the initial depth information is combined with the color map for joint guided filtering, and a high-precision depth map is obtained. The experimental results show that the proposed method is more robust for complex scenes and can obtain better depth estimation results with smaller algorithm complexity. Compared to other advanced methods, the depth images obtained by using the proposed method are more accurate, the edges are clearer, and the MSE100 indicator on HCI dataset is reduced by an average of 7.8 %. © 2020, Editorial Office of Control and Decision. All right reserved.