Intersensor Statistical Matching for Pansharpening: Theoretical Issues and Practical Solutions

In this paper, the authors investigate the statistical matching of the panchromatic (Pan) image to the multispectral (MS) bands, also known as the histogram matching, for the two main classes of pansharpening methods, i.e., those based on component substitution (CS) or spectral methods and those bas...

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Bibliographic Details
Published in:	IEEE transactions on geoscience and remote sensing 2017-08, Vol.55 (8), p.4682-4695
Main Authors:	Alparone, Luciano, Garzelli, Andrea, Vivone, Gemine
Format:	Article
Language:	eng
Subjects:	Additives Dynamics Histograms Injection Instruments Matching Methods Multiresolution analysis Multiresolution techniques multisensor systems optical transfer functions Remote sensing Satellites Solutions Spatial analysis Spatial resolution Spectral methods Statistics Wavelet analysis
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Summary:	In this paper, the authors investigate the statistical matching of the panchromatic (Pan) image to the multispectral (MS) bands, also known as the histogram matching, for the two main classes of pansharpening methods, i.e., those based on component substitution (CS) or spectral methods and those based on multiresolution analysis (MRA) or spatial methods. Also, hybrid methods combining CS with MRA, like the widespread additive wavelet luminance proportional (AWLP), are investigated. It is shown that all spectral, spatial, and hybrid methods must perform a dynamics matching of the enhancing Pan to the individual MS bands for MRA or a combination of them (the component that shall be substituted) for CS. For hybrid methods, the problem is more complex and both types of histogram matching may be suitable. Such an intersensor balance may be either explicit or implicitly performed by the detail-injection model, e.g., the popular projective and multiplicative injection models. An experimental setup exploiting IKONOS and WorldView-2 data sets demonstrates that a correct histogram matching is the key to attain extra performance from established methods. As a first result of this paper, the AWLP method has been revisited and its performance significantly improved by simply performing the histogram matching of Pan to the individual MS bands, rather than to the intensity component, thereby losing the original proportionality feature.
ISSN:	0196-2892 1558-0644