http://www.cnr.it/ontology/cnr/individuo/prodotto/ID22825

Multispectral and Panchromatic Data Fusion Assessment Without Reference (Articolo in rivista)

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Multispectral and Panchromatic Data Fusion Assessment Without Reference (Articolo in rivista) (literal)

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Luciano Alparone; Bruno Aiazzi; Stefano Baronti; Andrea Garzelli; Filippo Nencini; Massimo Selva (2008)
Multispectral and Panchromatic Data Fusion Assessment Without Reference
in Photogrammetric engineering and remote sensing; American Society for Photogrammetry and Remote Sensing (ASPRS), Bethesda (Stati Uniti d'America)
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Luciano Alparone; Bruno Aiazzi; Stefano Baronti; Andrea Garzelli; Filippo Nencini; Massimo Selva (literal)

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http://www.asprs.org/a/publications/pers/2008journal/february/2008_feb_193-200.pdf (literal)

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Department of Electronics & Telecommunications, University of Florence Institute of Applied Physics \"Nello Carrara\" IFAC-CNR Institute of Applied Physics \"Nello Carrara\" IFAC-CNR Department of Information Engineering, University of Siena Department of Information Engineering, University of Siena Institute of Applied Physics \"Nello Carrara\" IFAC-CNR (literal)

Titolo

Multispectral and Panchromatic Data Fusion Assessment Without Reference (literal)

Abstract

This paper introduces a novel approach for evaluating the quality of pansharpened multispectral (MS) imagery without resorting to reference originals. Hence, evaluations are feasible at the highest spatial resolution of the panchromatic (PAN) sensor. Wang and Bovik's image quality index (QI) provides a statistical similarity measurement between two monochrome images. The QI values between any couple of MS bands are calculated before and after fusion and used to define a measurement of spectral distortion. Analogously, QI values between each MS band and the PAN image are calculated before and after fusion to yield a measurement of spatial distortion. The rationale is that such QI values should be unchanged after fusion, i.e., when the spectral information is translated from the coarse scale of the MS data to the fine scale of the PAN image. Experimental results, carried out on very high-resolution Ikonos data and simulated Pléiades data, demonstrate that the results provided by the proposed approach are consistent and in trend with analysis performed on spatially degraded data. However, the proposed method requires no reference originals and is therefore usable in all practical cases. (literal)

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