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Erschienen in:
2017 | OriginalPaper | Buchkapitel
A Note on Boosting Algorithms for Image Denoising
verfasst von : Cory Falconer, C. Sean Bohun, Mehran Ebrahimi
Erschienen in: Image Analysis and Recognition
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Abstract
In recent years, non-local methods have been among most efficient tools to address the classical problem of image denoising. Recently, Romano et al. have proposed a novel algorithm aimed at “boosting” of a number of non-local denoising algorithms as a “black-box.” In this manuscript, we consider this algorithm and derive an analytical expression corresponding to successive applications of their proposed “boosting scheme.” Mathematically, we prove that such successive application does not always enhance the input image and is equivalent to a re-parameterization of the original “boosting” algorithm. We perform a set of computational experiments on test images to support this claim. Finally, we conclude that considering the blind application of such boosting methods as a general remedy for all denoising schemes is questionable.