Difference between revisions of "Publications/carlinet.19.ismm"

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(Created page with "{{Publication | published = true | date = 2019-03-13 | authors = Edwin Carlinet, Thierry Géraud | title = Introducing Multivariate Connected Openings and Closings | booktitle...")
 
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| title = Introducing Multivariate Connected Openings and Closings
 
| title = Introducing Multivariate Connected Openings and Closings
 
| booktitle = Mathematical Morphology and Its Application to Signal and Image Processing – Proceedings of the 14th International Symposium on Mathematical Morphology (ISMM)
 
| booktitle = Mathematical Morphology and Its Application to Signal and Image Processing – Proceedings of the 14th International Symposium on Mathematical Morphology (ISMM)
| volume =
 
 
| series = Lecture Notes in Computer Science Series
 
| series = Lecture Notes in Computer Science Series
 
| address = Saarbrücken, Germany
 
| address = Saarbrücken, Germany
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| pages = 1 to 12
 
| pages = 1 to 12
 
| lrdeprojects = Olena
 
| lrdeprojects = Olena
| abstract = The component trees provide a high-level, hierarchicaland contrast invariant representations of images, suitable for many image processing tasks. Yet their definition is ill-formed on multivariate data, e.g., color imagesmulti-modality images, multi-band images, and so on. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems, such as artifacts, loss of invariances, etc. In this paper, inspired by the way the Multivariate Tree of Shapes (MToS) has been defined, we propose a definition for a Multivariate min-tree or max-tree. We do not impose an arbitrary total ordering on values; we use only the inclusion relationship between components. As a straightforward consequence, we thus have a new class of multivariate connected openings and closings.
+
| abstract = The component trees provide a high-level, hierarchicaland contrast invariant representations of images, suitable for many image processing tasks. Yet their definition is ill-formed on multivariate data, e.g., color imagesmulti-modality images, multi-band images, and so on. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems, such as artifacts, loss of invariances, etc. In this paper, inspired by the way the Multivariate Tree of Shapes (MToS) has been defined, we propose a definition for a Multivariate min-tree or max-tree. We do not impose an arbitrary total ordering on values; we use only the inclusion relationship between components. As a straightforward consequence, we thus have a new class of multivariate connected openings and closings.
 
| lrdepaper = http://www.lrde.epita.fr/dload/papers/carlinet.19.ismm.pdf
 
| lrdepaper = http://www.lrde.epita.fr/dload/papers/carlinet.19.ismm.pdf
  +
| lrdeposter = http://www.lrde.epita.fr/dload/papers/carlinet.19.ismm.poster.pdf
  +
| lrdeinc = Publications/carlinet.19.ismm.inc
 
| lrdekeywords = Image
 
| lrdekeywords = Image
 
| lrdenewsdate = 2019-03-13
 
| lrdenewsdate = 2019-03-13
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Symposium on Mathematical Morphology (ISMM)<nowiki>}</nowiki>,
 
Symposium on Mathematical Morphology (ISMM)<nowiki>}</nowiki>,
 
year = 2019,
 
year = 2019,
editor = <nowiki>{</nowiki><nowiki>}</nowiki>,
 
volume = <nowiki>{</nowiki><nowiki>}</nowiki>,
 
 
series = <nowiki>{</nowiki>Lecture Notes in Computer Science Series<nowiki>}</nowiki>,
 
series = <nowiki>{</nowiki>Lecture Notes in Computer Science Series<nowiki>}</nowiki>,
 
address = <nowiki>{</nowiki>Saarbr\"ucken, Germany<nowiki>}</nowiki>,
 
address = <nowiki>{</nowiki>Saarbr\"ucken, Germany<nowiki>}</nowiki>,
 
publisher = <nowiki>{</nowiki>Springer<nowiki>}</nowiki>,
 
publisher = <nowiki>{</nowiki>Springer<nowiki>}</nowiki>,
 
pages = <nowiki>{</nowiki>1--12<nowiki>}</nowiki>,
 
pages = <nowiki>{</nowiki>1--12<nowiki>}</nowiki>,
month = <nowiki>{</nowiki>July<nowiki>}</nowiki>,
+
month = jul,
 
abstract = <nowiki>{</nowiki>The component trees provide a high-level, hierarchical,
 
abstract = <nowiki>{</nowiki>The component trees provide a high-level, hierarchical,
 
and contrast invariant representations of images, suitable
 
and contrast invariant representations of images, suitable

Revision as of 10:20, 21 August 2019

Abstract

The component trees provide a high-level, hierarchicaland contrast invariant representations of images, suitable for many image processing tasks. Yet their definition is ill-formed on multivariate data, e.g., color imagesmulti-modality images, multi-band images, and so on. Common workarounds such as marginal processing, or imposing a total order on data are not satisfactory and yield many problems, such as artifacts, loss of invariances, etc. In this paper, inspired by the way the Multivariate Tree of Shapes (MToS) has been defined, we propose a definition for a Multivariate min-tree or max-tree. We do not impose an arbitrary total ordering on values; we use only the inclusion relationship between components. As a straightforward consequence, we thus have a new class of multivariate connected openings and closings.

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Bibtex (lrde.bib)

@InProceedings{	  carlinet.19.ismm,
  author	= {Edwin Carlinet and Thierry G\'eraud},
  title		= {Introducing Multivariate Connected Openings and Closings},
  booktitle	= {Mathematical Morphology and Its Application to Signal and
		  Image Processing -- Proceedings of the 14th International
		  Symposium on Mathematical Morphology (ISMM)},
  year		= 2019,
  series	= {Lecture Notes in Computer Science Series},
  address	= {Saarbr\"ucken, Germany},
  publisher	= {Springer},
  pages		= {1--12},
  month		= jul,
  abstract	= {The component trees provide a high-level, hierarchical,
		  and contrast invariant representations of images, suitable
		  for many image processing tasks. Yet their definition is
		  ill-formed on multivariate data, e.g., color images,
		  multi-modality images, multi-band images, and so on. Common
		  workarounds such as marginal processing, or imposing a
		  total order on data are not satisfactory and yield many
		  problems, such as artifacts, loss of invariances, etc. In
		  this paper, inspired by the way the Multivariate Tree of
		  Shapes (MToS) has been defined, we propose a definition for
		  a Multivariate min-tree or max-tree. We do not impose an
		  arbitrary total ordering on values; we use only the
		  inclusion relationship between components. As a
		  straightforward consequence, we thus have a new class of
		  multivariate connected openings and closings.}
}