A Single-Parameter Factor-Graph Image Prior

TL;DR

This paper introduces a new image prior model based on factor graphs with adaptive local parameters, enabling effective denoising and contrast enhancement through iterative algorithms.

Contribution

It presents a novel piecewise smooth image model with automatically adapted local parameters using factor graphs and NUP priors, advancing image processing techniques.

Findings

Effective denoising demonstrated

Contrast enhancement improved

Model adapts to various images

Abstract

We propose a novel piecewise smooth image model with piecewise constant local parameters that are automatically adapted to each image. Technically, the model is formulated in terms of factor graphs with NUP (normal with unknown parameters) priors, and the pertinent computations amount to iterations of conjugate-gradient steps and Gaussian message passing. The proposed model and algorithms are demonstrated with applications to denoising and contrast enhancement.