Image Sharpening by Flows Based on Triple Well Potentials

Guy Gilboa*, Nir Sochen, Yehoshua Y. Zeevi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


Image sharpening in the presence of noise is formulated as a non-convex variational problem. The energy functional incorporates a gradient-dependent 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 well-shaped potential (in the one-dimensional case). The energy minimization flow results in sharpening of the dominant edges, while most noisy fluctuations are filtered out.

Original languageEnglish
Pages (from-to)121-131
Number of pages11
JournalJournal of Mathematical Imaging and Vision
Issue number1-2
StatePublished - Jan 2004


FundersFunder number
Aurora Foundation


    • Hyper-diffusion
    • Image enhancement
    • Image filtering
    • Image sharpening
    • Nonlinear diffusion
    • Variational image processing


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