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arXiv · 1503.01587

On debiasing restoration algorithms: applications to total-variation and nonlocal-means

Charles-Alban Deledalle·Nicolas Papadakis·Joseph Salmon
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Abstract

Bias in image restoration algorithms can hamper further analysis, typically when the intensities have a physical meaning of interest, e.g., in medical imaging. We propose to suppress a part of the bias -- the method bias -- while leaving unchanged the other unavoidable part -- the model bias. Our debiasing technique can be used for any locally affine estimator including \^a1 regularization, anisotropic total-variation and some nonlocal filters.

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Charles-Alban Deledalle, Nicolas Papadakis, Joseph Salmon. 2015-03-05. On debiasing restoration algorithms: applications to total-variation and nonlocal-means. https://arxiv.org/abs/1503.01587

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