Light Field Denoising with Adaptive Stochastic Gradient Langevin Dynamics

Abstract

We propose a self-supervised learning method for light field denoising (LFDN). Numerical experiments on a simulated light field dataset verified that our LFDN model within the Adaptive Stochastic Gradient Langevin Dynamics framework is superior to the classical denoising methods.