An effective framework of IBP for single facial image super resolution

DOI

10.2991/icmt-13.2013.122How to use a DOI?

Keywords

super-resolution, IBP, wavelet edge detection, PCA

Abstract

Super-resolution was used to refine the LRI (low resolution image) which was acquired from the existing electric devices. Moreover, it is significant to do this work on the human face. To solve the special facial problem, a novel framework based on IBP (Iterative Back Projection) is proposed, in which the edge detection and edge preserving are taken into account. In the iterative part, we adopt wavelet for edge detection to preserve the details and eliminate the loss of visual information. Furthermore, PCA (Principle Component Analysis) technique is introduced to extract more local high frequency information to refine the LRI. Experimental results show that our framework could efficiently enhance the visual effect. Both PSNR and SSIM of the super-resolution of LRI could be increased. Moreover, some experiments on face recognition are conducted and our method achieves more inspiring results.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Wang Cong
AU  - Li Weifeng
AU  - Wang Longbiao
AU  - Liao Qingming
PY  - 2013/11
DA  - 2013/11
TI  - An effective framework of IBP for single facial image super resolution
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 986
EP  - 993
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.122
DO  - 10.2991/icmt-13.2013.122
ID  - Cong2013/11
ER  -