Variational local structure estimation for image super-resolution

TL;DR

This paper introduces a variational local structure estimation method for image super-resolution that effectively preserves image details and avoids oversmoothing, especially when only a single low-resolution image is available.

Contribution

It proposes a novel adaptive linear interpolation technique based on variational principles and local linear embedding, improving super-resolution quality over traditional methods.

Findings

Prevents oversmoothing of images.

Preserves image structures effectively.

Outperforms traditional interpolation methods.

Abstract

Super-resolution is an important but difficult problem in image/video processing. If a video sequence or some training set other than the given low-resolution image is available, this kind of extra information can greatly aid in the reconstruction of the high-resolution image. The problem is substantially more difficult with only a single low-resolution image on hand. The image reconstruction methods designed primarily for denoising is insufficient for super-resolution problem in the sense that it tends to oversmooth images with essentially no noise. We propose a new adaptive linear interpolation method based on variational method and inspired by local linear embedding (LLE). The experimental result shows that our method avoids the problem of oversmoothing and preserves image structures well.