Constructing an Interpretable Deep Denoiser by Unrolling Graph Laplacian Regularizer

A general framework to construct an interpretable graph-based deep denoiser (GDD) by unrolling a solution to a maximum a posteriori (MAP) problem equipped with a graph Laplacian regularizer (GLR) as signal prior.