Light field denoising: exploiting the redundancy of an epipolar sequence representation
Alireza Sepas‐Moghaddam, Paulo Lobato Correia, Fernando M. B. Pereira · 2016
Many current light field cameras are based on a single sensor with an overlaid micro lenses array, making them more susceptible to noise. This paper proposes a novel light field denoising solution to reduce the effect of Gaussian noise as this is the most commonly assumed type of noise at the acquisition process. The proposed solution takes a noisy light field image and converts it to a sequence of epipolar images, using as intermediate step a representation based on the ordered sequence of the sub-aperture images. The created epipolar sequence is finally processed by a powerful, generic video denoising engine. The performance of the proposed denoising solution has been assessed using the PSNR and SSIM metrics for a representative set of rendered 2D views. The obtained results for two representative datasets compare favorably against state-of-the-art light field denoising methods, both in terms of objective assessment and visual appearance.