TY - GEN
T1 - A joint perspective towards image super-resolution
T2 - 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014
AU - Wang, Zhangyang
AU - Wang, Zhaowen
AU - Chang, Shiyu
AU - Yang, Jianchao
AU - Huang, Thomas
PY - 2014
Y1 - 2014
N2 - Existing example-based super resolution (SR) methods are built upon either external-examples or self-examples. Although effective in certain cases, both methods suffer from their inherent limitation. This paper goes beyond these two classes of most common example-based SR approaches, and proposes a novel joint SR perspective. The joint SR exploits and maximizes the complementary advantages of external- and self-example based methods. We elaborate on exploitable priors for image components of different nature, and formulate their corresponding loss functions mathematically. Equipped with that, we construct a unified SR formulation, and propose an iterative joint super resolution (IJSR) algorithm to solve the optimization. Such a joint perspective approach leads to an impressive improvement of SR results both quantitatively and qualitatively.
AB - Existing example-based super resolution (SR) methods are built upon either external-examples or self-examples. Although effective in certain cases, both methods suffer from their inherent limitation. This paper goes beyond these two classes of most common example-based SR approaches, and proposes a novel joint SR perspective. The joint SR exploits and maximizes the complementary advantages of external- and self-example based methods. We elaborate on exploitable priors for image components of different nature, and formulate their corresponding loss functions mathematically. Equipped with that, we construct a unified SR formulation, and propose an iterative joint super resolution (IJSR) algorithm to solve the optimization. Such a joint perspective approach leads to an impressive improvement of SR results both quantitatively and qualitatively.
UR - http://www.scopus.com/inward/record.url?scp=84904645410&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904645410&partnerID=8YFLogxK
U2 - 10.1109/WACV.2014.6836048
DO - 10.1109/WACV.2014.6836048
M3 - Conference contribution
AN - SCOPUS:84904645410
SN - 9781479949854
T3 - 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014
SP - 596
EP - 603
BT - 2014 IEEE Winter Conference on Applications of Computer Vision, WACV 2014
PB - IEEE Computer Society
Y2 - 24 March 2014 through 26 March 2014
ER -