Paper Info
Title
Fast classified pansharpening with spectral and spatial distortion optimization
Abstract
This paper presents a fast method suitable for pansharpening of MS imagery. Key points of the novel method, which falls in the category of component substitution (CS) methods, are optimization of the intensity component, achieved through multivariate regression of Pan to MS, and adjustment of the modulus of the spatial detail vector to be injected, based on a minimization of spatial distortion. Spatial distortion is measured at full scale according to the QNR protocol on land cover classes defined by NDVI thresholding. Experiments carried out on IKONOS data demonstrate that results are competitive with those of the most advanced methods, with a computational complexity comparable with that of Brovey transform fusion, which is the baseline version of the proposed method.
Year
DOI
Venue
2012
10.1109/IGARSS.2012.6351614
Geoscience and Remote Sensing Symposium
Keywords
DocType
ISSN
computational complexity,distortion,image fusion,image segmentation,optimisation,regression analysis,transforms,Brovey transform fusion,CS methods,IKONOS data,MS imagery pansharpening,MS multivariate regression,NDVI thresholding,Pan multivariate regression,QNR protocol,component substitution methods,computational complexity,fast classified pansharpening,intensity component optimization,land cover classes,spatial distortion minimization,spatial distortion optimization,spectral distortion optimization,Brovey transform,pansharpening,spatial distortion,spectral distortion
Conference
2153-6996 E-ISBN : 978-1-4673-1158-8
ISBN
Citations 
PageRank 
978-1-4673-1158-8
0
0.34
References 
Authors
5
4
Name
Order
Citations
PageRank
Luciano Alparone190180.27
Bruno Aiazzi227527.84
Stefano Baronti355950.87
Andrea Garzelli457441.36