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Cite Details

Rick Chartrand and Valentina Staneva, "A quasi-Newton method for total variation regularization of images corrupted by non-Gaussian noise", IET Image Process., vol. 2, pp. 295--303, 2008

Abstract

Our aim is to obtain efficient algorithms for image regularization optimized for removing different types of noise. To accomplish this, we combine total variation regularization with a noise-specific way to measure the fidelity between the noisy image and the reconstruction. We find a minimum of the resulting functional with a quasi-Newton method, which converges faster than the common method of gradient descent. As examples we consider Poisson noise and impulse noise. We prove convergence of the algorithm for a large class of fidelity terms.

BibTeX Entry

@article{chartrand-2007-quasi,
author = {Rick Chartrand and Valentina Staneva},
title = {A quasi-Newton method for total variation regularization of images corrupted by non-Gaussian noise},
year = {2008},
urlpdf = {http://math.lanl.gov/Research/Publications/Docs/chartrand-2007-quasi.pdf},
journal = {IET Image Process.},
volume = {2},
pages = {295--303}
}