A Color Tree of Shapes with Illustrations on FilteringSimplification, and Segmentation
From LRDE
- Authors
- Edwin Carlinet, Thierry Géraud
- Where
- Mathematical Morphology and Its Application to Signal and Image Processing – Proceedings of the 12th International Symposium on Mathematical Morphology (ISMM)
- Place
- Reykjavik, Iceland
- Type
- inproceedings
- Publisher
- Springer
- Projects
- Olena
- Keywords
- Image
- Date
- 2015-04-07
Abstract
The Tree of Shapes is a morphological tree that provides a high-level, hierarchical, self-dual, and contrast invariant representation of images, suitable for many image processing tasks. When dealing with color images, one cannot use the Tree of Shapes because its definition is ill-formed on multivariate data. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems (color artifactsloss of invariances, etc.) In this paper, we highlight the need for a self-dual and contrast invariant representation of color images and we provide a method that builds a single Tree of Shapes by merging the shapes computed marginally, while guarantying the most important properties of the ToS. This method does not try to impose an arbitrary total ordering on values but uses only the inclusion relationship between shapes. Eventually, we show the relevance of our method and our structure through some illustrations on filtering, image simplification, and interactive segmentation.
Documents
Bibtex (lrde.bib)
@InProceedings{ carlinet.15.ismm, author = {Edwin Carlinet and Thierry G\'eraud}, title = {A Color Tree of Shapes with Illustrations on Filtering, Simplification, and Segmentation}, booktitle = {Mathematical Morphology and Its Application to Signal and Image Processing -- Proceedings of the 12th International Symposium on Mathematical Morphology (ISMM)}, year = {2015}, series = {Lecture Notes in Computer Science Series}, volume = {9082}, address = {Reykjavik, Iceland}, publisher = {Springer}, editor = {J.A. Benediktsson and J. Chanussot and L. Najman and H. Talbot}, pages = {363--374}, abstract = {The Tree of Shapes is a morphological tree that provides a high-level, hierarchical, self-dual, and contrast invariant representation of images, suitable for many image processing tasks. When dealing with color images, one cannot use the Tree of Shapes because its definition is ill-formed on multivariate data. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems (color artifacts, loss of invariances, etc.) In this paper, we highlight the need for a self-dual and contrast invariant representation of color images and we provide a method that builds a single Tree of Shapes by merging the shapes computed marginally, while guarantying the most important properties of the ToS. This method does not try to impose an arbitrary total ordering on values but uses only the inclusion relationship between shapes. Eventually, we show the relevance of our method and our structure through some illustrations on filtering, image simplification, and interactive segmentation.}, doi = {10.1007/978-3-319-18720-4_31} }