Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging

Anatole Chessel; Bertrand Cinquin; Sabine Bardin; Jean Salamero; Charles Kervrann

doi:10.1007/978-3-642-02256-2_64

Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging

Anatole Chessel
, Bertrand Cinquin
, Sabine Bardin
, Jean Salamero
, Charles Kervrann

CNRS
Synchrotron SOLEIL
PICT
Institut Curie
INRIA Institut National de Recherche en Informatique et en Automatique
INRA-MIA

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

7 Citations (Scopus)

Résumé

In this paper a framework for defining scale-spaces, based on the computational geometry concepts of α-shapes, is proposed. In this approach, objects (curves or surfaces) of increasing convexity are computed by selective sub-sampling, from the original shape to its convex hull. The relationships with the Empirical Mode Decomposition (EMD), the curvature motion-based scale-space and some operators from mathematical morphology, are studied. Finally, we address the problem of additive image/signal decomposition in fluorescence video-microscopy. An image sequence is mainly considered as a collection of 1D temporal signals, each pixel being associated with its temporal intensity variation.

langue originale	Anglais
titre	Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings
Pages	770-781
Nombre de pages	12
Les DOIs	https://doi.org/10.1007/978-3-642-02256-2_64
état	Publié - 27 août 2009
Evénement	2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009 - Voss, Norvcge Durée: 1 juin 2009 → 5 juin 2009

Série de publications

Nom	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5567 LNCS
ISSN (imprimé)	0302-9743
ISSN (Electronique)	1611-3349

Une conférence

Une conférence	2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009
Pays/Territoire	Norvcge
La ville	Voss
période	1/06/09 → 5/06/09

Accès au document

10.1007/978-3-642-02256-2_64

Contient cette citation

Chessel, A., Cinquin, B., Bardin, S., Salamero, J., & Kervrann, C. (2009). Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging. Dans Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings (p. 770-781). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 5567 LNCS). https://doi.org/10.1007/978-3-642-02256-2_64

Chessel, Anatole ; Cinquin, Bertrand ; Bardin, Sabine et al. / Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging. Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings. 2009. p. 770-781 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging",

abstract = "In this paper a framework for defining scale-spaces, based on the computational geometry concepts of α-shapes, is proposed. In this approach, objects (curves or surfaces) of increasing convexity are computed by selective sub-sampling, from the original shape to its convex hull. The relationships with the Empirical Mode Decomposition (EMD), the curvature motion-based scale-space and some operators from mathematical morphology, are studied. Finally, we address the problem of additive image/signal decomposition in fluorescence video-microscopy. An image sequence is mainly considered as a collection of 1D temporal signals, each pixel being associated with its temporal intensity variation.",

author = "Anatole Chessel and Bertrand Cinquin and Sabine Bardin and Jean Salamero and Charles Kervrann",

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Chessel, A, Cinquin, B, Bardin, S, Salamero, J & Kervrann, C 2009, Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging. Dans Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOL. 5567 LNCS, p. 770-781, 2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009, Voss, Norvcge, 1/06/09. https://doi.org/10.1007/978-3-642-02256-2_64

Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging. / Chessel, Anatole; Cinquin, Bertrand; Bardin, Sabine et al.
Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings. 2009. p. 770-781 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 5567 LNCS).

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collection › Contribution à une conférence › Revue par des pairs

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T1 - Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging

AU - Chessel, Anatole

AU - Cinquin, Bertrand

AU - Bardin, Sabine

AU - Salamero, Jean

AU - Kervrann, Charles

PY - 2009/8/27

Y1 - 2009/8/27

N2 - In this paper a framework for defining scale-spaces, based on the computational geometry concepts of α-shapes, is proposed. In this approach, objects (curves or surfaces) of increasing convexity are computed by selective sub-sampling, from the original shape to its convex hull. The relationships with the Empirical Mode Decomposition (EMD), the curvature motion-based scale-space and some operators from mathematical morphology, are studied. Finally, we address the problem of additive image/signal decomposition in fluorescence video-microscopy. An image sequence is mainly considered as a collection of 1D temporal signals, each pixel being associated with its temporal intensity variation.

AB - In this paper a framework for defining scale-spaces, based on the computational geometry concepts of α-shapes, is proposed. In this approach, objects (curves or surfaces) of increasing convexity are computed by selective sub-sampling, from the original shape to its convex hull. The relationships with the Empirical Mode Decomposition (EMD), the curvature motion-based scale-space and some operators from mathematical morphology, are studied. Finally, we address the problem of additive image/signal decomposition in fluorescence video-microscopy. An image sequence is mainly considered as a collection of 1D temporal signals, each pixel being associated with its temporal intensity variation.

U2 - 10.1007/978-3-642-02256-2_64

DO - 10.1007/978-3-642-02256-2_64

M3 - Conference contribution

AN - SCOPUS:69049095273

SN - 3642022553

SN - 9783642022555

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 770

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BT - Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings

T2 - 2nd International Conference on Scale Space and Variational Methods in Computer Vision, SSVM 2009

Y2 - 1 June 2009 through 5 June 2009

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Chessel A, Cinquin B, Bardin S, Salamero J, Kervrann C. Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging. Dans Scale Space and Variational Methods in Computer Vision - Second International Conference, SSVM 2009, Proceedings. 2009. p. 770-781. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-02256-2_64

Computational geometry-based scale-space and modal image decomposition application to light video-microscopy imaging

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