Flexible Krylov Methods for Edge Enhancement in Imaging

Many successful variational regularization methods employed to solve linear inverse problems in imaging applications (such as image deblurring, image inpainting, and computed tomography) aim at enhancing edges in the solution, and often involve non-smooth regularization terms (e.g., total variation)...

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Detalles Bibliográficos
Autores principales: Gazzola, Silvia, Scott, Sebastian James, Spence, Alastair
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540705/
https://www.ncbi.nlm.nih.gov/pubmed/34677302
http://dx.doi.org/10.3390/jimaging7100216

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8540705/
https://www.ncbi.nlm.nih.gov/pubmed/34677302
http://dx.doi.org/10.3390/jimaging7100216

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