Double Sparse Multi-Frame Image Super Resolution

TL;DR

This paper introduces a unified optimization approach for multi-frame image super resolution that combines image registration and sparse coding into a single objective, improving efficiency and effectiveness.

Contribution

It proposes a novel method that jointly optimizes image registration and sparse coding for multi-frame super resolution, simplifying previous multi-step processes.

Findings

Numerical experiments demonstrate the effectiveness of the proposed approach.

The method outperforms traditional separate registration and sparse coding techniques.

Unified optimization improves super resolution quality and computational efficiency.

Abstract

A large number of image super resolution algorithms based on the sparse coding are proposed, and some algorithms realize the multi-frame super resolution. In multi-frame super resolution based on the sparse coding, both accurate image registration and sparse coding are required. Previous study on multi-frame super resolution based on sparse coding firstly apply block matching for image registration, followed by sparse coding to enhance the image resolution. In this paper, these two problems are solved by optimizing a single objective function. The results of numerical experiments support the effectiveness of the proposed approch.