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Image Sharpening by Flows Based on Triple Well Potentials
 Guy Gilboa,
 Nir Sochen,
 Yehoshua Y. Zeevi
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Image sharpening in the presence of noise is formulated as a nonconvex variational problem. The energy functional incorporates a gradientdependent potential, a convex fidelity criterion and a high order convex regularizing term. The first term attains local minima at zero and some high gradient magnitude, thus forming a triple wellshaped potential (in the onedimensional case). The energy minimization flow results in sharpening of the dominant edges, while most noisy fluctuations are filtered out.
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 Title
 Image Sharpening by Flows Based on Triple Well Potentials
 Journal

Journal of Mathematical Imaging and Vision
Volume 20, Issue 12 , pp 121131
 Cover Date
 20040101
 DOI
 10.1023/B:JMIV.0000011320.81911.38
 Print ISSN
 09249907
 Online ISSN
 15737683
 Publisher
 Kluwer Academic Publishers
 Additional Links
 Topics
 Keywords

 image filtering
 image enhancement
 image sharpening
 nonlinear diffusion
 hyperdiffusion
 variational image processing
 Industry Sectors
 Authors

 Guy Gilboa ^{(1)}
 Nir Sochen ^{(2)}
 Yehoshua Y. Zeevi ^{(1)} ^{(3)}
 Author Affiliations

 1. Department of Electrical Engineering, Technion—Israel Institute of Technology, Technion City, Haifa, 32000, Israel
 2. Department of Applied Mathematics, University of TelAviv RamatAviv, TelAviv, 69978, Israel
 3. Department of Biomedical Engineering, Columbia University, New York, NY, 10027, USA