Kuijper, Arjan (2013)
Image Processing by Minimising Lp Norms.
In: Pattern Recognition and Image Analysis, 23 (2)
doi: 10.1134/S105466181302003X
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
In this work, we take a novel line of approaches to evolve images. It is motivated by the total variation method, known for its denoising and edge-preserving effect. Our approach generalises the TV method by taking a general Lp norm of the gradients instead of the L¹ in the TV method. We generalise this method in a series of first and second order derivatives in terms of gauge coordinates. This method also incorporates the well-known blurring by a Gaussian filter and the balanced forward-backward diffusion. The method and its properties are briefly discussed. The practical results are visualised on a real-life image, showing the expected behaviour. When a constraint is added that penalises the distance of the results to the input image, one can vary the desired amount of blurring and denoising.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2013 |
| Autor(en): | Kuijper, Arjan |
| Art des Eintrags: | Bibliographie |
| Titel: | Image Processing by Minimising Lp Norms |
| Sprache: | Englisch |
| Publikationsjahr: | 2013 |
| Verlag: | Springer |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Pattern Recognition and Image Analysis |
| Jahrgang/Volume einer Zeitschrift: | 23 |
| (Heft-)Nummer: | 2 |
| Buchtitel: | Pattern Recognition and Image Analysis |
| DOI: | 10.1134/S105466181302003X |
| Kurzbeschreibung (Abstract): | In this work, we take a novel line of approaches to evolve images. It is motivated by the total variation method, known for its denoising and edge-preserving effect. Our approach generalises the TV method by taking a general Lp norm of the gradients instead of the L¹ in the TV method. We generalise this method in a series of first and second order derivatives in terms of gauge coordinates. This method also incorporates the well-known blurring by a Gaussian filter and the balanced forward-backward diffusion. The method and its properties are briefly discussed. The practical results are visualised on a real-life image, showing the expected behaviour. When a constraint is added that penalises the distance of the results to the input image, one can vary the desired amount of blurring and denoising. |
| Freie Schlagworte: | Image processing, Partial differential equations |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 18 Nov 2019 10:59 |
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