Compressive Sensing (CS) is receiving increasing attention as a way to lower storage and compression requirements for on-board acquisition of remote-sensing images. In the case of multi-and hyperspectral images, however, exploiting the spectral correlation poses severe computational problems. Yet, exploiting such a correlation would provide significantly better performance in terms of reconstruction quality. In this paper, we build on a recently proposed 2D CS scheme based on blind source separation to develop a computationally simple, yet accurate, prediction-based scheme for acquisition and iterative reconstruction of hyperspectral images in a CS setting. Preliminary experiments carried out on different hyperspectral images show that our approach yields a dramatic reduction of computational time while ensuring reconstruction performance similar to those of much more complicated 3D reconstruction schemes.
Kuiteng, S.K., Barni, M. (2014). Iterative compressive sampling for hyperspectral images via source separation. In IMAGE SENSORS AND IMAGING SYSTEMS 2014 (pp.UNSP 90220T). Bellingham : SPIE [10.1117/12.2037794].
Iterative compressive sampling for hyperspectral images via source separation
BARNI, MAURO
2014-01-01
Abstract
Compressive Sensing (CS) is receiving increasing attention as a way to lower storage and compression requirements for on-board acquisition of remote-sensing images. In the case of multi-and hyperspectral images, however, exploiting the spectral correlation poses severe computational problems. Yet, exploiting such a correlation would provide significantly better performance in terms of reconstruction quality. In this paper, we build on a recently proposed 2D CS scheme based on blind source separation to develop a computationally simple, yet accurate, prediction-based scheme for acquisition and iterative reconstruction of hyperspectral images in a CS setting. Preliminary experiments carried out on different hyperspectral images show that our approach yields a dramatic reduction of computational time while ensuring reconstruction performance similar to those of much more complicated 3D reconstruction schemes.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/981791
Attenzione
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo