Thürck, Daniel ; Kuijper, Arjan (2013)
Cosine-Driven Non-linear Denoising.
Image Analysis and Recognition.
doi: 10.1007/978-3-642-39094-4_28
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
The Perona-Malik model is an effective but ill-posed model for denoising digital images by anisotropic diffusion. Instead of complex regularizations, we propose a new continuous model which is well-posed and show that it is nevertheless effective for denoising. In addition, an extension of our model offers the possibility of inducing a convergence for the discretization. A comparison to the original Perona-Malik model is carried out using an human vision-centered quality index which shows the improvements of our model when it comes to denoising.
Typ des Eintrags: | Konferenzveröffentlichung |
---|---|
Erschienen: | 2013 |
Autor(en): | Thürck, Daniel ; Kuijper, Arjan |
Art des Eintrags: | Bibliographie |
Titel: | Cosine-Driven Non-linear Denoising |
Sprache: | Englisch |
Publikationsjahr: | 2013 |
Verlag: | Springer, Berlin; Heidelberg; New York |
Reihe: | Lecture Notes in Computer Science (LNCS); 7950 |
Veranstaltungstitel: | Image Analysis and Recognition |
DOI: | 10.1007/978-3-642-39094-4_28 |
Kurzbeschreibung (Abstract): | The Perona-Malik model is an effective but ill-posed model for denoising digital images by anisotropic diffusion. Instead of complex regularizations, we propose a new continuous model which is well-posed and show that it is nevertheless effective for denoising. In addition, an extension of our model offers the possibility of inducing a convergence for the discretization. A comparison to the original Perona-Malik model is carried out using an human vision-centered quality index which shows the improvements of our model when it comes to denoising. |
Freie Schlagworte: | Digital image processing, Image processing, Partial differential equations, Image enhancement, Image restoration |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
Hinterlegungsdatum: | 12 Nov 2018 11:16 |
Letzte Änderung: | 10 Dez 2021 07:23 |
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