Enhanced morphological filtering for wavelet-based changepoint detection

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Résumé

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.

langue originaleAnglais
titreProceedings - 15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
rédacteurs en chefKokou Yetongnon, Albert Dipanda, Gabriella Sanniti di Baja, Luigi Gallo, Richard Chbeir
EditeurInstitute of Electrical and Electronics Engineers Inc.
Pages56-60
Nombre de pages5
ISBN (Electronique)9781728156866
Les DOIs
étatPublié - nov. 2019
Evénement15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019 - Sorrento, Italie
Durée: 26 nov. 201929 nov. 2019

Série de publications

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

Une conférence

Une conférence15th International Conference on Signal Image Technology and Internet Based Systems, SISITS 2019
Pays/TerritoireItalie
La villeSorrento
période26/11/1929/11/19

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