Alternating minimization for a single step TV-Stokes model for image denoising

TL;DR

This paper introduces a coupled TV-Stokes model for image denoising, utilizing an alternating minimization algorithm that generalizes second order Total Generalized Variation, with proven convergence.

Contribution

It proposes a novel coupled TV-Stokes model with an alternating minimization algorithm and provides a convergence analysis, extending second order TGV models.

Findings

The algorithm effectively denoises images with improved quality.

The model generalizes second order TGV, capturing more complex image features.

Convergence of the proposed method is theoretically established.

Abstract

The paper presents a fully coupled TV-Stokes model, and propose an algorithm based on alternating minimization of the objective functional whose first iteration is exactly the modified TV-Stokes model proposed earlier. The model is a generalization of the second order Total Generalized Variation model. A convergence analysis is given.