This paper presents a novel image fusion method, suitable for pan-sharpening of multispectral (MS) bands, based on multiresolution analysis (MRA). The low-resolution MS bands are sharpened by injecting highpass directional details extracted from the high-resolution panchromatic (Pan) image by means of the curvelet transform, which is a nonseparable MRA, whose basis function are directional edges with progressively increasing resolution. The advantage with respect to conventional separable MRA, either decimated or not, is twofold: directional detail coefficients matching image edges may be preliminarily soft-thresholded to achieve denoising better than in the separable wavelet domain; modeling of the relationships between high-resolution detail coefficients of MS bands and of the Pan image is more fitting, being carried out in a directional wavelet domain. Experiments carried out on a very-high resolution MS + Pan QuickBird image show that the proposed curvelet method quantitatively outperforms state-of-the art image fusion methods, in terms of geometric, radiometric, and spectral fidelity.
Garzelli, A., Nencini, F., Alparone, L., Baronti, S. (2005). Multiresolution fusion of multispectral and panchromatic images through the curvelet transform. In Proc. IEEE IGARSS'05 (pp.2838-2841). New York, USA : IEEE [10.1109/IGARSS.2005.1525659].
Multiresolution fusion of multispectral and panchromatic images through the curvelet transform
GARZELLI, ANDREA;
2005-01-01
Abstract
This paper presents a novel image fusion method, suitable for pan-sharpening of multispectral (MS) bands, based on multiresolution analysis (MRA). The low-resolution MS bands are sharpened by injecting highpass directional details extracted from the high-resolution panchromatic (Pan) image by means of the curvelet transform, which is a nonseparable MRA, whose basis function are directional edges with progressively increasing resolution. The advantage with respect to conventional separable MRA, either decimated or not, is twofold: directional detail coefficients matching image edges may be preliminarily soft-thresholded to achieve denoising better than in the separable wavelet domain; modeling of the relationships between high-resolution detail coefficients of MS bands and of the Pan image is more fitting, being carried out in a directional wavelet domain. Experiments carried out on a very-high resolution MS + Pan QuickBird image show that the proposed curvelet method quantitatively outperforms state-of-the art image fusion methods, in terms of geometric, radiometric, and spectral fidelity.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/38198
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