Fusion of hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction

Giorgio Licciardi 1 Muhammad Murtaza Khan 2 Jocelyn Chanussot 1 Annick Montanvert 3 Laurent Condat 3 Christian Jutten 4
1 GIPSA-SIGMAPHY - SIGMAPHY
GIPSA-DIS - Département Images et Signal
3 GIPSA-AGPIG - AGPIG
GIPSA-DIS - Département Images et Signal
4 GIPSA-VIBS - VIBS
GIPSA-DIS - Département Images et Signal
Abstract : This article presents a novel method for the enhancement of the spatial quality of hyperspectral (HS) images through the use of a high resolution panchromatic (PAN) image. Due to the high number of bands, the application of a pan-sharpening technique to HS images may result in an increase of the computational load and complexity. Thus a dimensionality reduction preprocess, compressing the original number of measurements into a lower dimensional space, becomes mandatory. To solve this problem, we propose a pan-sharpening technique combining both dimensionality reduction and fusion, making use of non-linear principal component analysis (NLPCA) and Indusion, respectively, to enhance the spatial resolution of a HS image. We have tested the proposed algorithm on HS images obtained from CHRIS-Proba sensor and PAN image obtained from World view 2 and demonstrated that a reduction using NLPCA does not result in any significant degradation in the pan-sharpening results.
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https://hal.archives-ouvertes.fr/hal-00786285
Contributor : Laurent Condat <>
Submitted on : Friday, February 8, 2013 - 11:58:57 AM
Last modification on : Monday, July 8, 2019 - 3:11:30 PM

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Giorgio Licciardi, Muhammad Murtaza Khan, Jocelyn Chanussot, Annick Montanvert, Laurent Condat, et al.. Fusion of hyperspectral and panchromatic images using multiresolution analysis and nonlinear PCA band reduction. EURASIP Journal on Advances in Signal Processing, SpringerOpen, 2012, 2012, pp.207. ⟨10.1186/1687-6180-2012-207⟩. ⟨hal-00786285⟩

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