Functional data analysis in hyperspectral remote sensing : application to the study of agri-forest landscape

Autor: Zullo, Anthony

Publikováno v: Functional Analysis [math.FA]. Université Paul Sabatier-Toulouse III, 2016. English. ⟨NNT : 2016TOU30135⟩
Traitement des images [eess.IV]. 2016. Français

In hyperspectral imaging, each pixel is associated with a spectrum derived from observed reflectance in d measurement points (i.e., wavelengths). We are often facing a situation where the sample size n is relatively low compared to the number d of va

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::e48777e564e23f7bd8c3dd5f3237a119
https://tel.archives-ouvertes.fr/tel-01492876/document

A new denoising procedure based on empirical mode decomposition for SHM purpose

Autor: Mukhopadhyay, S., Betti, R., Galli, E., Savoia, M., Loris Vincenzi

Publikováno v: Safety, Reliability, Risk and Life-Cycle Performance of Structures and Infrastructures ISBN: 9781138000865
Scopus-Elsevier

In this work, a signal processing method based on the Empirical Mode Decomposition (EMD) to denoise a recorded signal is proposed. EMD expresses the signal as an expansion of basis functions (Intrinsic Mode Functions - IMFs) that are signal dependent

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::81e436aeb434ac87d6ab01d96c87f65e
https://hdl.handle.net/11380/1012719

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