Details

Autor(en) / Beteiligte

• Licciardi, Giorgio Antonino
• Khan, Muhammad Murtaza
• Chanussot, Jocelyn
• Montanvert, Annick
• Condat, Laurent
• Jutten, Christian

Titel

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

Ist Teil von

• EURASIP journal on advances in signal processing, 2012-09, Vol.2012 (1), p.1-17, Article 207

Ort / Verlag

Cham: Springer International Publishing

Erscheinungsjahr

2012

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• 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.