Compression light field reconstruction and depth estimation

Aiming at the problem of large amount of the light field data and inaccurate depth estimation at the edge, the light field was reconstructed by compressive sensing principle and a depth estimation method based on multiple information fusion was proposed. Firstly, a 5×5 view light-field was reconstructed according to the compressed sensing reconstruction algorithm, and the refocusing was realized by moving the sub-aperture after obtaining the field data. Then, the initial depth and confidence of the scene were calculated by using the defocused response cues and correspondence response of angular patch. Finally, the image edge information was calculated, and the final depth was obtained by fusing the initial depth, confidence and edge information. The compressed light field simulation and physical reconstruction were realized, and the depth estimation of the simulated reconstruction light field and the open optical field data were also achieved. The experimental results show that the method proposed can simulate and reconstruct the 5×5 view light field data, which can be used for depth estimation. The depth estimation results of the proposed method at the edge of the scene is clear and hierarchical, which verifies the feasibility and accuracy of the depth estimation for the reconstructed light field based on compressed sensing theory.