Single-frame image super-resolution through contourlet learning
EURASIP Journal on Applied Signal Processing
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This paper 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.