Demosaicing and Denoising on Simulated Light Field Images
Light field cameras use an array of microlens to capture the 4D radiance of as scene. Standard image processing techniques with light field data do not utilize all four dimensions to demosaic or denoise captured images. In this paper, we formulate demosaicing as an optimization problem and enforce a TV prior on different dimensions of the light field. We apply our method on simulated light field data created from 3D virtual scenes. Because our data is simulated, we can use ground truth images to evaluate the effectiveness of our method. For certain combinations of dimensions, we achieve better overall PSNR values than the standard demosaicing technique described in Malvar et al. [1] Despite the improvement in PSNR, we introduce more color artifacts in areas of high frequency in the image. Our method also improves PNSR values for scenes with low illumination levels.