Single Image Super-resolution using Vectorization and Texture Synthesis

Kaoning Hu, Dongeun Lee, Tianyang Wang

2021

Abstract

Image super-resolution is a very useful tool in science and art. In this paper, we propose a novel method for single image super-resolution that combines image vectorization and texture synthesis. Image vectorization is the conversion from a raster image to a vector image. While image vectorization algorithms can trace the fine edges of images, they will sacrifice color and texture information. In contrast, texture synthesis techniques, which have been previously used in image super-resolution, can reasonably create high-resolution color and texture information, except that they sometimes fail to trace the edges of images correctly. In this work, we adopt the image vectorization to the edges of the original image, and the texture synthesis based on the Kolmogorov–Smirnov test (KS test) to the non-edge regions of the original image. The goal is to generate a plausible, visually pleasing detailed higher resolution version of the original image. In particular, our method works very well on the images of natural animals.

Paper Citation

in Harvard Style

Hu K., Lee D. and Wang T. (2021). Single Image Super-resolution using Vectorization and Texture Synthesis. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 512-519. DOI: 10.5220/0010325505120519

in Bibtex Style

@conference{visapp21,
author={Kaoning Hu and Dongeun Lee and Tianyang Wang},
title={Single Image Super-resolution using Vectorization and Texture Synthesis},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={512-519},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010325505120519},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Single Image Super-resolution using Vectorization and Texture Synthesis
SN - 978-989-758-488-6
AU - Hu K.
AU - Lee D.
AU - Wang T.
PY - 2021
SP - 512
EP - 519
DO - 10.5220/0010325505120519
PB - SciTePress