TY - GEN
T1 - Dictionary-based multiple frame video super-resolution
AU - Dai, Qiqin
AU - Yoo, Seunghwan
AU - Kappeler, Armin
AU - Katsaggelos, Aggelos K.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/9
Y1 - 2015/12/9
N2 - In this paper, we propose a multiple-frame super-resolution (SR) algorithm based on dictionary learning and motion estimation. We adopt the use of multiple bilevel dictionaries which have also been used for single-frame SR. Multiple frames compensated through sub-pixel motion are considered. By simultaneously solving for a batch of patches from multiple frames, the proposed multiple-frame SR algorithm improves over single frame SR. We also propose a novel dictionary learning algorithm based on which dictionaries are trained from consecutive video frames, rather than still images or individual video frames, which further improves the performance of the developed video SR algorithm. Extensive experimental comparisons with state-of-the-art SR algorithms verifies the effectiveness of our proposed multiple-frame SR approach.
AB - In this paper, we propose a multiple-frame super-resolution (SR) algorithm based on dictionary learning and motion estimation. We adopt the use of multiple bilevel dictionaries which have also been used for single-frame SR. Multiple frames compensated through sub-pixel motion are considered. By simultaneously solving for a batch of patches from multiple frames, the proposed multiple-frame SR algorithm improves over single frame SR. We also propose a novel dictionary learning algorithm based on which dictionaries are trained from consecutive video frames, rather than still images or individual video frames, which further improves the performance of the developed video SR algorithm. Extensive experimental comparisons with state-of-the-art SR algorithms verifies the effectiveness of our proposed multiple-frame SR approach.
KW - Video super-resolution
KW - dictionary learning
KW - optical flow estimation
KW - sparse coding
UR - http://www.scopus.com/inward/record.url?scp=84956677149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84956677149&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2015.7350764
DO - 10.1109/ICIP.2015.7350764
M3 - Conference contribution
AN - SCOPUS:84956677149
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 83
EP - 87
BT - 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PB - IEEE Computer Society
T2 - IEEE International Conference on Image Processing, ICIP 2015
Y2 - 27 September 2015 through 30 September 2015
ER -