TY - GEN
T1 - Multi-scale non-local kernel regression for super resolution
AU - Zhang, Haichao
AU - Yang, Jianchao
AU - Zhang, Yanning
AU - Huang, Thomas S.
PY - 2011
Y1 - 2011
N2 - In this paper, we propose an extension of the Non-Local Kernel Regression (NL-KR) method and apply it to super-resolution (SR) tasks. The proposed method extends NL-KR via generalizing the self-similarity from single-scale to multi-scale, and propose an effective SR algorithm using the proposed multi-scale NL-KR model. Experimental results on both synthetic and real images demonstrate the effectiveness of the proposed method.
AB - In this paper, we propose an extension of the Non-Local Kernel Regression (NL-KR) method and apply it to super-resolution (SR) tasks. The proposed method extends NL-KR via generalizing the self-similarity from single-scale to multi-scale, and propose an effective SR algorithm using the proposed multi-scale NL-KR model. Experimental results on both synthetic and real images demonstrate the effectiveness of the proposed method.
KW - Non-Local Kernel Regression
KW - image restoration
KW - local structural regularity
KW - multi-scale self-similarity
KW - super resolution
UR - http://www.scopus.com/inward/record.url?scp=84863070599&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863070599&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2011.6115688
DO - 10.1109/ICIP.2011.6115688
M3 - Conference contribution
AN - SCOPUS:84863070599
SN - 9781457713033
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1353
EP - 1356
BT - ICIP 2011
T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011
Y2 - 11 September 2011 through 14 September 2011
ER -