On plenoptic sub-aperture view recovery

Light field imaging is recently made available tothe mass market by Lytro and Raytrix commercial cameras.Thanks to a grid of microlenses put in front of the sensor, aplenoptic camera simultaneously captures several images of thescene under different viewing angles, providing an enormousadvantage for post-capture applications,e.g., depth estimationand image refocusing. In this paper, we propose a fast frameworkto re-grid, denoise and up-sample the data of any plenopticcamera. The proposed method relies on the prior sub-pixelestimation of micro-images centers and of inter-views disparities.Both objective and subjective experiments show the improvedquality of our results in terms of preserving high frequenciesand reducing noise and artifacts in low frequency content. Sincethe recovery of the pixels is independent of one another, thealgorithm is highly parallelizable on GPU.