Reconstruction of compressively sampled light fields using a weighted 4D-DCT basis

The coded aperture/mask technique enables us to capture light field data in a compressive way through a single camera. A pixel value recorded by such a camera is a summation of the light rays that pass though different positions on the coded aperture/mask. The target light field can be reconstructed from the recorded pixel values by using prior information of the light field signal. As prior information, a dictionary (light field atoms), which was learned from training datasets, was used in the current state of the art. Meanwhile, it was reported that general bases such as DCT were not suitable to efficiently represent prior information. In this work, however, we demonstrate that a 4D-DCT basis works surprisingly better if it is combined with a weighting scheme in which the amplitude difference in DCT coefficients is considered. Simulation results using 18 light field datasets are reported to show the superior performance of the weighted 4D-DCT basis to the learned dictionary.