Cargando…
Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising
The use of a mathematical model is proposed in order to denoise X-ray two-dimensional patterns. The method relies on a generalized diffusion equation whose diffusion constant depends on the image gradients. The numerical solution of the diffusion equation provides an efficient reduction of pattern n...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344928/ https://www.ncbi.nlm.nih.gov/pubmed/32570931 http://dx.doi.org/10.3390/ma13122773 |
_version_ | 1783556059555692544 |
---|---|
author | Ladisa, Massimo Lamura, Antonio |
author_facet | Ladisa, Massimo Lamura, Antonio |
author_sort | Ladisa, Massimo |
collection | PubMed |
description | The use of a mathematical model is proposed in order to denoise X-ray two-dimensional patterns. The method relies on a generalized diffusion equation whose diffusion constant depends on the image gradients. The numerical solution of the diffusion equation provides an efficient reduction of pattern noise as witnessed by the computed peak of signal-to-noise ratio. The use of experimental data with different inherent levels of noise allows us to show the success of the method even in the case, experimentally relevant, when patterns are blurred by Poissonian noise. The corresponding MatLab code for the numerical method is made available. |
format | Online Article Text |
id | pubmed-7344928 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73449282020-07-09 Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising Ladisa, Massimo Lamura, Antonio Materials (Basel) Article The use of a mathematical model is proposed in order to denoise X-ray two-dimensional patterns. The method relies on a generalized diffusion equation whose diffusion constant depends on the image gradients. The numerical solution of the diffusion equation provides an efficient reduction of pattern noise as witnessed by the computed peak of signal-to-noise ratio. The use of experimental data with different inherent levels of noise allows us to show the success of the method even in the case, experimentally relevant, when patterns are blurred by Poissonian noise. The corresponding MatLab code for the numerical method is made available. MDPI 2020-06-18 /pmc/articles/PMC7344928/ /pubmed/32570931 http://dx.doi.org/10.3390/ma13122773 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ladisa, Massimo Lamura, Antonio Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising |
title | Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising |
title_full | Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising |
title_fullStr | Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising |
title_full_unstemmed | Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising |
title_short | Diffusion-Driven X-Ray Two-Dimensional Patterns Denoising |
title_sort | diffusion-driven x-ray two-dimensional patterns denoising |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7344928/ https://www.ncbi.nlm.nih.gov/pubmed/32570931 http://dx.doi.org/10.3390/ma13122773 |
work_keys_str_mv | AT ladisamassimo diffusiondrivenxraytwodimensionalpatternsdenoising AT lamuraantonio diffusiondrivenxraytwodimensionalpatternsdenoising |