TR2015-142
Edge-enhancing filters with negative weights
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- "Edge-Enhancing Filters with Negative Weights", IEEE Global Conference on Signal and Information Processing (GlobalSIP), DOI: 10.1109/GlobalSIP.2015.7418197, December 2015, pp. 260-264.BibTeX TR2015-142 PDF
- @inproceedings{Knyazev2015dec1,
- author = {Knyazev, A.},
- title = {Edge-Enhancing Filters with Negative Weights},
- booktitle = {IEEE Global Conference on Signal and Information Processing (GlobalSIP)},
- year = 2015,
- pages = {260--264},
- month = dec,
- doi = {10.1109/GlobalSIP.2015.7418197},
- url = {https://www.merl.com/publications/TR2015-142}
- }
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- "Edge-Enhancing Filters with Negative Weights", IEEE Global Conference on Signal and Information Processing (GlobalSIP), DOI: 10.1109/GlobalSIP.2015.7418197, December 2015, pp. 260-264.
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Research Area:
Abstract:
In [doi:10.1109/ICMEW.2014.6890711], a graphbased denoising is performed by projecting the noisy image to a lower dimensional Krylov subspace of the graph Laplacian, constructed using non-negative 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 can improve quality of filters for graphbased signal processing, e.g., denoising, compared to the standard construction, without affecting the computational costs.
Related News & Events
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NEWS MERL presented 3 papers at the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP) Date: December 15, 2015
Where: 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)
MERL Contact: Hassan Mansour
Research Area: Machine LearningBrief- MERL researcher Andrew Knyazev gave 3 talks at the 2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP). The papers were published in IEEE conference proceedings.