Compressed Sensing (CS) allows to represent sparse signals through a small number of linear projections. Hence, CS can be thought of as a natural candidate for acquisition of hyper spectral images, as the amount of data acquired by conventional sensors creates significant handling problems on satellites or aircrafts. In this paper we develop an algorithm for CS reconstruction of hyperspectral images The proposed algorithm employs iterative local image reconstruction based on a hybrid transform/prediction correlation model, coupled with a proper initialization strategy. Experimental results on raw AVIRIS and AIRS images show that the proposed technique yields a very large reduction of mean-squared error with respect to conventional reconstruction methods.

Abrardo, A., Barni, M., Carretti, C.M., Kuiteng Kamdem, S., Magli, E. (2011). A compressive sampling scheme for iterative hyperspectral image reconstruction. In Proceedings of EUSIPCO 2011, 19th European Signal Processing Conference (pp.1120). Kessariani : EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP.

A compressive sampling scheme for iterative hyperspectral image reconstruction

ABRARDO, ANDREA;BARNI, MAURO;
2011-01-01

Abstract

Compressed Sensing (CS) allows to represent sparse signals through a small number of linear projections. Hence, CS can be thought of as a natural candidate for acquisition of hyper spectral images, as the amount of data acquired by conventional sensors creates significant handling problems on satellites or aircrafts. In this paper we develop an algorithm for CS reconstruction of hyperspectral images The proposed algorithm employs iterative local image reconstruction based on a hybrid transform/prediction correlation model, coupled with a proper initialization strategy. Experimental results on raw AVIRIS and AIRS images show that the proposed technique yields a very large reduction of mean-squared error with respect to conventional reconstruction methods.
2011
Abrardo, A., Barni, M., Carretti, C.M., Kuiteng Kamdem, S., Magli, E. (2011). A compressive sampling scheme for iterative hyperspectral image reconstruction. In Proceedings of EUSIPCO 2011, 19th European Signal Processing Conference (pp.1120). Kessariani : EUROPEAN ASSOC SIGNAL SPEECH & IMAGE PROCESSING-EURASIP.
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11365/4956
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo