Goal of this work is to present a general and formal solution to the problem of multisensor image data fusion and to apply its results to a specific case study concerning multi-spectral observations: Landsat TM (30m resolution) and MOMS-2P (18m). The proposed scheme relies on the generalized Laplacian pyramid (GLP), which is a non-dyadic band-pass analysis structure unconstrained from the ground scales of the imaged data: for a p/q > 1 ratio only one low-pass filter with cut-off at 1/p of the spatial frequency content is needed. Filter design is easy and noncritical for performances. Thus, the pyramid method is simple to be designed and generalized to images having whatsoever ground resolution, as in most applications involving new-generation sensors.
Multispectral fusion of multisensor image data by the generalized Laplacian pyramid
Bruno Aiazzi;Luciano Alparone;Stefano Baronti;Ivan Pippi
1999
Abstract
Goal of this work is to present a general and formal solution to the problem of multisensor image data fusion and to apply its results to a specific case study concerning multi-spectral observations: Landsat TM (30m resolution) and MOMS-2P (18m). The proposed scheme relies on the generalized Laplacian pyramid (GLP), which is a non-dyadic band-pass analysis structure unconstrained from the ground scales of the imaged data: for a p/q > 1 ratio only one low-pass filter with cut-off at 1/p of the spatial frequency content is needed. Filter design is easy and noncritical for performances. Thus, the pyramid method is simple to be designed and generalized to images having whatsoever ground resolution, as in most applications involving new-generation sensors.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
