Title :
Minimum spanning tree adaptive image filtering
Author :
Stawiaski, Jean ; Meyer, Fernand
Author_Institution :
CMM-Centre de morphologie Math., Math. et Syst., MINES Paristech, Fontainebleau, France
Abstract :
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.
Keywords :
adaptive filters; image processing; trees (mathematics); adaptive image filtering; anisotropic morphological edge preserving filters; local image features; minimal spanning tree structure; natural images; synthetic images; Adaptive filters; Anisotropic magnetoresistance; Computational efficiency; Filtering; Geophysics computing; Grid computing; Morphology; Pixel; Shape; Smoothing methods; Morphological filter; denoising; edge-preserving; minimal spanning tree;
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2009.5413942