Combination of Single and Multi-frame Image Super-resolution: An Analytical Perspective

TL;DR

This paper provides a theoretical framework for optimally combining single-image and multi-frame super-resolution techniques, supported by simulations that validate the analysis.

Contribution

It introduces a novel theoretical analysis using iterative shrinkage and thresholding to optimize the combination of SISR and MFSR methods.

Findings

Theoretical analysis guides optimal SISR and MFSR combination.

Simulation results validate the theoretical predictions.

Combining SISR and MFSR improves super-resolution quality.

Abstract

Super-resolution is the process of obtaining a high-resolution image from one or more low-resolution images. Single image super-resolution (SISR) and multi-frame super-resolution (MFSR) methods have been evolved almost independently for years. A neglected study in this field is the theoretical analysis of finding the optimum combination of SISR and MFSR. To fill this gap, we propose a novel theoretical analysis based on the iterative shrinkage and thresholding algorithm. We implement and compare several approaches for combining SISR and MFSR, and simulation results support the finding of our theoretical analysis, both quantitatively and qualitatively.