Image Resolution Enhancement based on Curvelet Transform

Zehira Haddad, Adrien Chan Hon Tong, Jaime Lopez Krahe

2017

Abstract

We present an image resolution enhancement method based on Curvelet transform. This transform is used to decompose the input image into different subbands. After this decomposition, a nonlinear function is applied to the Curvelet coefficients in order to enhance the content of the different frequency subbands. These enhanced frequency subbands are then interpolated. We increase the enhancement results by a fusion of the obtained data and the interpolated input image. An image database is used for experiments. The visual results are showing the superiority of the proposed technique compared to two state-of-art image resolution enhancement techniques. These results have been confirmed by quantitative image quality metrics.

Paper Citation

in Harvard Style

Haddad Z., Tong A. and Krahe J. (2017). Image Resolution Enhancement based on Curvelet Transform . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 167-173. DOI: 10.5220/0006127201670173

in Bibtex Style

@conference{visapp17,
author={Zehira Haddad and Adrien Chan Hon Tong and Jaime Lopez Krahe},
title={Image Resolution Enhancement based on Curvelet Transform},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={167-173},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006127201670173},
isbn={978-989-758-225-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Image Resolution Enhancement based on Curvelet Transform
SN - 978-989-758-225-7
AU - Haddad Z.
AU - Tong A.
AU - Krahe J.
PY - 2017
SP - 167
EP - 173
DO - 10.5220/0006127201670173