Abstract
A novel image restoration method is developed based an AdaBoost algorithm. A sliding-window method is employed to extract image features and to obtain the input and output of BP neural network. An AdaBoost algorithm is established for image restoration, in which BP neural network is considered as a weak learner. Experimental results indicate that the proposed method is superior to tradition BP neural network in the field of image restoration and can be applied to restore turbulence-degraded images.
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Cai, N., Jin, F., Pan, Q., Xu, Sq., Li, F. (2012). Image Restoration Based on an AdaBoost Algorithm. In: Zhao, M., Sha, J. (eds) Communications and Information Processing. Communications in Computer and Information Science, vol 288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31965-5_35
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DOI: https://doi.org/10.1007/978-3-642-31965-5_35
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31964-8
Online ISBN: 978-3-642-31965-5
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