P‐2.29: Depth Estimation of Light Field Image Based on Compressed Sensing and Multi‐clue Fusion

Abstract

In the current research field of light field depth estimation, the occlusion of complex scenes and a large amount of computational data are the problems that every researcher must face. For complex occlusion scenes, this paper proposes a depth estimation method based on the fusion of adaptive defocus cues and constrained angular entropy cues, which is more robust to occlusion. At the same time, the compressed sensing theory is used to compress and reconstruct the light field image to solve the problem of a large amount of data in the process of light field image acquisition, transmission, and processing. The experimental results show that the proposed method has a good overall effect in dealing with the depth estimation of the occlusion scene, and the correct depth information can be obtained. The light field image reconstructed by compressed sensing can not only obtain good depth estimation results but also reduce the amount of data effectively.