# Edge-enhancing filters with negative weights

@article{Knyazev2015EdgeenhancingFW, title={Edge-enhancing filters with negative weights}, author={Andrew V. Knyazev}, journal={2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)}, year={2015}, pages={260-264} }

In [D01:10.1109/ICMEW.2014.6890711], a graph-based denoising is performed by projecting the noisy image to a lower dimensional Krylov subspace of the graph Laplacian, constructed using nonnegative weights determined by distances between image data corresponding to image pixels. We extend the construction of the graph Laplacian to the case, where some graph weights can be negative. Removing the positivity constraint provides a more accurate inference of a graph model behind the data, and thus… Expand

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