Minimum spanning tree adaptive image filtering
| Autor: | Jean Stawiaski, Fernand Meyer |
|---|---|
| Přispěvatelé: | Centre de Morphologie Mathématique (CMM), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL) |
| Rok vydání: | 2009 |
| Předmět: |
computational efficiency
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 0211 other engineering and technologies Image processing 02 engineering and technology Minimum spanning tree Distributed minimum spanning tree adaptive filters Minimum spanning tree-based segmentation 0202 electrical engineering electronic engineering information engineering [MATH.TR-IMG]Mathematics [math]/domain_math.tr-img Computer vision 021101 geological & geomatics engineering Mathematics Pixel business.industry Pattern recognition Non-local means geophysics computing image processing Adaptive filter trees (mathematics) [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] 020201 artificial intelligence & image processing Artificial intelligence Focus (optics) business |
| Zdroj: | ICIP 16th IEEE International Conference on Image Processing (ICIP) 16th IEEE International Conference on Image Processing (ICIP), Nov 2009, Le Caire, Egypt. pp.2245-2248, ⟨10.1109/ICIP.2009.5413942⟩ |
| DOI: | 10.1109/icip.2009.5413942 |
| Popis: | ISBN : 978-1-4244-5653-6; International audience; The main focus of this paper is related to anisotropic morphological edge preserving filters. We present in this work neighborhood filters defined on the minimal spanning tree (MST) of an image (according to a local dissimilarity measure between adjacent pixels). The designed filters take advantage of the property of the MST to detect and follow the local features of an image. This approach leads to neighborhood filters where the structuring elements adapt their shape to the minimal spanning tree structure and therefore to the local image features. We demonstrate the quality of this method on natural and synthetic images. |
| Databáze: | OpenAIRE |
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