Tesi etd-03262012-123025 |
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Tipo di tesi
Tesi di laurea specialistica
Autore
BAULE, PAOLO
URN
etd-03262012-123025
Titolo
Studio e sviluppo di metodi di rivelazione di punti di interesse per la registrazione di immagini iperspettrali multitemporali
Dipartimento
INGEGNERIA
Corso di studi
INGEGNERIA DELLE TELECOMUNICAZIONI
Relatori
relatore Corsini, Giovanni
relatore Resta, Salvatore
relatore Prof. Diani, Marco
relatore Resta, Salvatore
relatore Prof. Diani, Marco
Parole chiave
- SIFT
- SURF
- feature
- descrittori
- registrazione
- immagini iperspettrali
Data inizio appello
23/04/2012
Consultabilità
Non consultabile
Data di rilascio
23/04/2052
Riassunto
In this work two of the main feature extraction techniques, the Scale Invariant Feature Transform (SIFT) and the Speeded Up Robust Feature (SURF)
algorithms, were analyzed and compared.
Such procedures were originally developed to work on gray level images. In this work we extended the SIFT and SURF procedures to hyperspectral images (HSI) so as to exploit the potentially
different information contents arising from different spectral bands.
In particular we applied the above mentioned techniques to multitemporal HSI registration task. The experimental analysis conducted on different real
hyperspectral dataset with very high spatial resolution highlighted the
effectiveness of the approach, resulting in a consistent improvement of the
registration algorithms performance.
algorithms, were analyzed and compared.
Such procedures were originally developed to work on gray level images. In this work we extended the SIFT and SURF procedures to hyperspectral images (HSI) so as to exploit the potentially
different information contents arising from different spectral bands.
In particular we applied the above mentioned techniques to multitemporal HSI registration task. The experimental analysis conducted on different real
hyperspectral dataset with very high spatial resolution highlighted the
effectiveness of the approach, resulting in a consistent improvement of the
registration algorithms performance.
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