- Title
- Approximation of noisy data using multivariate splines and finite element methods
- Creator
- Lamichhane, Bishnu P.; Harris, Elizabeth; Le Gia, Quoc Thong
- Relation
- Journal of Algorithms and Computational Technology Vol. 15, p. 1-12
- Publisher Link
- http://dx.doi.org/10.1177/17483026211008405
- Publisher
- Sage
- Resource Type
- journal article
- Date
- 2021
- Description
- We compare a recently proposed multivariate spline based on mixed partial derivatives with two other standard splines for the scattered data smoothing problem. The splines are defined as the minimiser of a penalised least squares functional. The penalties are based on partial differential operators, and are integrated using the finite element method. We compare three methods to two problems: to remove the mixture of Gaussian and impulsive noise from an image, and to recover a continuous function from a set of noisy observations.
- Subject
- sobolev space; scattered data interpolation; gaussian noise; impulsive noise
- Identifier
- http://hdl.handle.net/1959.13/1456226
- Identifier
- uon:45195
- Identifier
- ISSN:1748-3018
- Rights
- © The Author(s) 2021. Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons AttributionNonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us. sagepub.com/en-us/nam/open-access-at-sage).
- Language
- eng
- Full Text
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