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Proceedings Paper

Nonlocal evolutions for image regularization
Author(s): Guy Gilboa; Stanley Osher
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Paper Abstract

A nonlocal quadratic functional of weighted differences is examined. The weights are based on image features and represent the affinity between different pixels in the image. By prescribing different formulas for the weights, one can generalize many local and nonlocal linear denoising algorithms, including nonlocal means and bilateral filters. The steepest descent for minimizing the functional can be interpreted as a nonlocal diffusion process. We show state of the art denoising results using the nonlocal flow.

Paper Details

Date Published: 28 February 2007
PDF: 10 pages
Proc. SPIE 6498, Computational Imaging V, 64980U (28 February 2007); doi: 10.1117/12.714701
Show Author Affiliations
Guy Gilboa, Univ. of California, Los Angeles (United States)
Stanley Osher, Univ. of California, Los Angeles (United States)


Published in SPIE Proceedings Vol. 6498:
Computational Imaging V
Charles A. Bouman; Eric L. Miller; Ilya Pollak, Editor(s)

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