DocumentCode
3429728
Title
Resolution enhancement by AdaBoost
Author
Wu, Junwen ; Trivedi, Mohan ; Rao, Bhaskar
Author_Institution
CVRR Lab, UC San Diego, La Jolla, CA, USA
Volume
4
fYear
2004
fDate
23-26 Aug. 2004
Firstpage
893
Abstract
This work proposes a learning scheme based still image super-resolution reconstruction algorithm. Super-resolution reconstruction is proposed as a binary classification problem and can be solved by conditional class probability estimation. Assuming the probability takes the form of additive logistic regression function, AdaBoost algorithm is used to predict the probability. Experiments on face images validate the algorithm.
Keywords
image reconstruction; image resolution; probability; regression analysis; AdaBoost algorithm; additive logistic regression function; binary classification problem; conditional class probability estimation; face images; still image super-resolution reconstruction algorithm; Frequency; Image reconstruction; Image resolution; Image storage; Interpolation; Logistics; Probability; Space technology; Statistical learning; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN
1051-4651
Print_ISBN
0-7695-2128-2
Type
conf
DOI
10.1109/ICPR.2004.1333916
Filename
1333916
Link To Document