Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
527657 | Image and Vision Computing | 2007 | 10 Pages |
Abstract
This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experiments on grayscale and color images demonstrate that these novel filters outperform classical morphological operations with a fixed, space-invariant structuring element for noise reduction applications. Tests on synthetic 3D images are then performed to show the high noise-reduction capacity of amoeba-based filters.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Romain Lerallut, Étienne Decencière, Fernand Meyer,