Numerical approximation of the fractional Laplacian via \(hp\)-finite elements, with an application to image denoising
DOI10.1007/s10915-014-9959-1zbMath1329.65272OpenAlexW2067513555MaRDI QIDQ898427
Publication date: 9 December 2015
Published in: Journal of Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10915-014-9959-1
convergencenumerical examplesboundary layerdegenerate elliptic equationimage denoisingMuckenhoupt weightfractional Laplacianautomatic adaptivityGibbs phenomen\(hp\)-finite elements
Stability and convergence of numerical methods for boundary value problems involving PDEs (65N12) Finite element, Rayleigh-Ritz and Galerkin methods for boundary value problems involving PDEs (65N30) Degenerate elliptic equations (35J70) Numerical aspects of computer graphics, image analysis, and computational geometry (65D18) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Reflected symmetric \(\alpha\)-stable processes and regional fractional Laplacian
- The resolution of the Gibbs phenomenon for ``spliced functions in one and two dimensions
- A fully automatic \(hp\)-adaptivity
- A PDE approach to fractional diffusion in general domains: a priori error analysis
- A concave—convex elliptic problem involving the fractional Laplacian
- Extension Problem and Harnack's Inequality for Some Fractional Operators
- Regularity of Radial Extremal Solutions for Some Non-Local Semilinear Equations
- Weighted Sobolev spaces and embedding theorems
- An Extension Problem Related to the Fractional Laplacian
- Projection-based interpolation and automatic hp-adaptivity for finite element discretizations of elliptic and maxwell problems
- Computing with hp-ADAPTIVE FINITE ELEMENTS
This page was built for publication: Numerical approximation of the fractional Laplacian via \(hp\)-finite elements, with an application to image denoising