15 October 2015 Are spectral or spatial methods better for pansharpening? An evaluation for four sample methods based on spatial modulation of pixel spectra
Author Affiliations +
Abstract
The majority of pansharpening methods can be classified as spectral or spatial methods, depending on whether they are based on component substitution (CS) or multiresolution analysis (MRA). So far, the suitability of one class or methods rather than another has been seldom discussed. In this paper, through experiments on IKONOS and simulated Pléiades datasets, the authors demonstrate that the performances of spectral methods depend on the extent of spectral matching, measured by the coefficient of determination (CD) of the multivariate regression between MS and P. For data with simulated P, CD is very close to one and all methods perform almost identically. For true IKONOS datasets, the CD is few percent lower and spatial methods, once they have been optimized through the knowledge of the modulation transfer function (MTF) of the imaging system, are always more performing than spectral methods. Since spatial methods are unaffected by the spectral matching, they are preferable whenever such an issue is critical, e.g., for hyperspectral pansharpening.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luciano Alparone, Luciano Alparone, Andrea Garzelli, Andrea Garzelli, Gemine Vivone, Gemine Vivone, } "Are spectral or spatial methods better for pansharpening? An evaluation for four sample methods based on spatial modulation of pixel spectra", Proc. SPIE 9643, Image and Signal Processing for Remote Sensing XXI, 96430V (15 October 2015); doi: 10.1117/12.2196193; https://doi.org/10.1117/12.2196193
PROCEEDINGS
12 PAGES


SHARE
Back to Top