Title :
Resolution enhancement by AdaBoost
Author :
Wu, Junwen ; Trivedi, Mohan ; Rao, Bhaskar
Author_Institution :
CVRR Lab, UC San Diego, La Jolla, CA, USA
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;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1333916