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Proceedings Paper

Advantages of Laplacian pyramids over ''à trous'' wavelet transforms for pansharpening of multispectral images
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Paper Abstract

The advantages provided by the generalized Laplacian pyramid (GLP) over the widespread “`a trous” wavelet (ATW) transform for multispectral (MS) pansharpening based on multiresolution analysis (MRA) are investigated. The most notable difference depends on the way GLP and ATW deal with aliasing possibly occurring in the MS data, which is originated by insufficient sampling step size, or equivalently by a too high amplitude value of the modulation transfer function (MTF) at Nyquist frequency and may generate annoying jagged patterns that survive in the sharpened image. In this paper, it is proven that GLP is capable of compensating the aliasing of MS, unlike ATW, and analogously to component substitution (CS) fusion methods, thanks to the decimation and interpolation stages present in its flowchart. Experimental results will be presented in terms of quality/distortion global score indexes (SAM, ERGAS and Q4) for increasing amounts of aliasing, measured by the amplitude at Nyquist frequency of the Gaussian-like lowpass filter simulating the average MTF of the individual spectral channels of the instrument. GLP and ATW-based methods, both using the same MTF filters and the same global injection gain, will be compared to show the advantages of GLP over ATW in the presence of aliasing of the MS bands.

Paper Details

Date Published: 8 November 2012
PDF: 10 pages
Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 853704 (8 November 2012); doi: 10.1117/12.976298
Show Author Affiliations
Bruno Aiazzi, Istituto di Fisica Applicata Nello Carrara (Italy)
Luciano Alparone, Istituto di Fisica Applicata Nello Carrara (Italy)
Univ. of Florence (Italy)
Stefano Baronti, Istituto di Fisica Applicata Nello Carrara (Italy)
Andrea Garzelli, Istituto di Fisica Applicata Nello Carrara (Italy)
Univ. of Siena (Italy)
Massimo Selva, Istituto di Fisica Applicata Nello Carrara (Italy)


Published in SPIE Proceedings Vol. 8537:
Image and Signal Processing for Remote Sensing XVIII
Lorenzo Bruzzone, Editor(s)

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