A Fourier Disparity Layer representation for Light Fields31st May 2019
The Fourier Disparity Layer (FDL) model, is a representation of Light Fields allowing efficient processing by fully exploiting the parallelisation capabilities of modern GPUs.
In the FDL representation, the scene is decomposed into a set of additive layers and each layer of index k is associated to a disparity value dk representing its depth. Any view of the light field at angular coordinate (u,v) is directly reconstructed as the sum of the layers shifted with a translation vector (u.dk, v.dk).
The construction of layers from light field views is performed efficiently in the Fourier Domain thanks to a linear least squares optimisation problem formulated independently for each frequency component (efficiently solved with parallel processing on a GPU). This is made possible by the fact that in the Fourier domain, the shifting operation simply consists in multiplying each frequency component by a complex weight, hence resulting in a linear relationship between views and layers.
- The paper , presents the theoretical foundations of the model and various applications including calibration of angular coordintates and disparity values, view interpolation, denoising, real-time rendering (see demo video below).
- Extensions of the FDL construction for light field super-resolution, demosaicing and completion applications are presented in . By performing completion jointly with super-resolution and demosaicing, the method also allows the extraction of high quality views from RAW lenslet data of plenoptic cameras (see examples of results below).
- The compression of light fields is addressed in  with a view prediction scheme based on the FDL view interpolation.
- Another light field compression and streaming method that directly encodes the FDL model is presented in . It constructs a binary tree structure from the layers to encode the FDL in a hierarchical manner, thus providing a scalable representation for light field streaming.
 M. Le Pendu and A. Smolic “High Resolution Light Field Recovery with Fourier Disparity Layer Completion, Demosaicing, and Super-Resolution”, IEEE International Conference on Computational Photography (ICCP) Apr. 2020. (watch the talk here)
The matlab code is available on github: here!
|Demonstration of the applications in |
|Examples of view extraction from lenslet RAW data of a Lytro Illum camera  (click on images for full resolution)|
|FDL Extraction||Lytro Desktop (official Lytro software)|