An effective framework of IBP for single facial image super resolution
Wang Cong, Li Weifeng, Wang Longbiao, Liao Qingming
Available Online November 2013.
- https://doi.org/10.2991/icmt-13.2013.122How to use a DOI?
- super-resolution, IBP, wavelet edge detection, PCA
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 3rd International Conference on Multimedia Technology(ICMT-13) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/icmt-13.2013.122 DO - https://doi.org/10.2991/icmt-13.2013.122 ID - Cong2013/11 ER -