Enhanced morphological filtering for wavelet-based changepoint detection

Mattia Stasolla; Xavier Neyt

doi:10.1109/SITIS.2019.00021

Enhanced morphological filtering for wavelet-based changepoint detection

Remote Sensing

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

2 Zitate (Scopus)

Abstract

This paper presents a new method for the detection of abrupt changes (i.e. mean shifts) in time series. It is a follow-up to a previous article by the authors where, for the first time, the possibility of combining the multi-scale analysis capabilities of wavelets with mathematical morphology, a theoretical framework for the analysis of spatial structures, had been explored. The processing chain has been revised and enhanced in order to improve the overall results, and a performance assessment has been carried out to evaluate the accuracy and robustness of the method to noise, also providing a comparison with its original implementation.

Originalsprache	Englisch
Titel	Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
Redakteure/-innen	Kokou Yetongnon, Albert Dipanda, Gabriella Sanniti di Baja, Luigi Gallo, Richard Chbeir
Herausgeber (Verlag)	Institute of Electrical and Electronics Engineers Inc.
Seiten	56-60
Seitenumfang	5
ISBN (elektronisch)	9781728156866
DOIs	https://doi.org/10.1109/SITIS.2019.00021
Publikationsstatus	Veröffentlicht - Nov. 2019
Veranstaltung	15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 - Sorrento, Italien Dauer: 26 Nov. 2019 → 29 Nov. 2019

Publikationsreihe

Name	Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019

Konferenz

Konferenz	15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
Land/Gebiet	Italien
Ort	Sorrento
Zeitraum	26/11/19 → 29/11/19

Zugriff auf Dokument

10.1109/SITIS.2019.00021

Andere Dateien und Links

Verknüpfung zur Publikation in Scopus

EORegions-Science: EORegions-Science
Neyt, X. (Leitende(r) Forscher/-in) & Stasolla, M. (Forschende)
1/11/16 → 31/08/18
Projekt: Forschung › Research

Dieses zitieren

Stasolla, M., & Neyt, X. (2019). Enhanced morphological filtering for wavelet-based changepoint detection. in K. Yetongnon, A. Dipanda, G. Sanniti di Baja, L. Gallo, & R. Chbeir (Hrsg.), Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 (S. 56-60). Artikel 9067954 (Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SITIS.2019.00021

Stasolla, Mattia ; Neyt, Xavier. / Enhanced morphological filtering for wavelet-based changepoint detection. Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019. Hrsg. / Kokou Yetongnon ; Albert Dipanda ; Gabriella Sanniti di Baja ; Luigi Gallo ; Richard Chbeir. Institute of Electrical and Electronics Engineers Inc., 2019. S. 56-60 (Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019).

@inproceedings{440cdb8a98564e4095fad2b87a8fe21f,

title = "Enhanced morphological filtering for wavelet-based changepoint detection",

abstract = "This paper presents a new method for the detection of abrupt changes (i.e. mean shifts) in time series. It is a follow-up to a previous article by the authors where, for the first time, the possibility of combining the multi-scale analysis capabilities of wavelets with mathematical morphology, a theoretical framework for the analysis of spatial structures, had been explored. The processing chain has been revised and enhanced in order to improve the overall results, and a performance assessment has been carried out to evaluate the accuracy and robustness of the method to noise, also providing a comparison with its original implementation.",

keywords = "Changepoint detection, Mathematical morphology, Time series, Wavelets",

author = "Mattia Stasolla and Xavier Neyt",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 ; Conference date: 26-11-2019 Through 29-11-2019",

year = "2019",

month = nov,

doi = "10.1109/SITIS.2019.00021",

language = "English",

series = "Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "56--60",

editor = "Kokou Yetongnon and Albert Dipanda and \{Sanniti di Baja\}, Gabriella and Luigi Gallo and Richard Chbeir",

booktitle = "Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019",

}

Stasolla, M & Neyt, X 2019, Enhanced morphological filtering for wavelet-based changepoint detection. in K Yetongnon, A Dipanda, G Sanniti di Baja, L Gallo & R Chbeir (Hrsg.), Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019., 9067954, Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019, Institute of Electrical and Electronics Engineers Inc., S. 56-60, 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019, Sorrento, Italien, 26/11/19. https://doi.org/10.1109/SITIS.2019.00021

Enhanced morphological filtering for wavelet-based changepoint detection. / Stasolla, Mattia ; Neyt, Xavier.
Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019. Hrsg. / Kokou Yetongnon; Albert Dipanda; Gabriella Sanniti di Baja; Luigi Gallo; Richard Chbeir. Institute of Electrical and Electronics Engineers Inc., 2019. S. 56-60 9067954 (Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019).

Publikation: Beitrag in Buch/Bericht/Konferenzband › Konferenzbeitrag › Begutachtung

TY - GEN

T1 - Enhanced morphological filtering for wavelet-based changepoint detection

AU - Stasolla, Mattia

AU - Neyt, Xavier

PY - 2019/11

Y1 - 2019/11

N2 - This paper presents a new method for the detection of abrupt changes (i.e. mean shifts) in time series. It is a follow-up to a previous article by the authors where, for the first time, the possibility of combining the multi-scale analysis capabilities of wavelets with mathematical morphology, a theoretical framework for the analysis of spatial structures, had been explored. The processing chain has been revised and enhanced in order to improve the overall results, and a performance assessment has been carried out to evaluate the accuracy and robustness of the method to noise, also providing a comparison with its original implementation.

AB - This paper presents a new method for the detection of abrupt changes (i.e. mean shifts) in time series. It is a follow-up to a previous article by the authors where, for the first time, the possibility of combining the multi-scale analysis capabilities of wavelets with mathematical morphology, a theoretical framework for the analysis of spatial structures, had been explored. The processing chain has been revised and enhanced in order to improve the overall results, and a performance assessment has been carried out to evaluate the accuracy and robustness of the method to noise, also providing a comparison with its original implementation.

KW - Changepoint detection

KW - Mathematical morphology

KW - Time series

KW - Wavelets

UR - https://www.scopus.com/pages/publications/85084838920

U2 - 10.1109/SITIS.2019.00021

DO - 10.1109/SITIS.2019.00021

M3 - Conference contribution

AN - SCOPUS:85084838920

T3 - Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019

SP - 56

EP - 60

BT - Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019

A2 - Yetongnon, Kokou

A2 - Dipanda, Albert

A2 - Sanniti di Baja, Gabriella

A2 - Gallo, Luigi

A2 - Chbeir, Richard

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019

Y2 - 26 November 2019 through 29 November 2019

ER -

Stasolla M , Neyt X. Enhanced morphological filtering for wavelet-based changepoint detection. in Yetongnon K, Dipanda A, Sanniti di Baja G, Gallo L, Chbeir R, Hrsg., Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. S. 56-60. 9067954. (Proceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019). doi: 10.1109/SITIS.2019.00021

Enhanced morphological filtering for wavelet-based changepoint detection

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