Improving Component Substitution Pansharpening Through Multivariate Regression of MS +Pan Data

• Published in: IEEE transactions on geoscience and remote sensing Vol. 45; no. 10; pp. 3230 - 3239
• Main Authors: Aiazzi, B., Baronti, S., Selva, M.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2007; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Band spectra; Bands; Component substitution (CS) pansharpening; Data visualization; Degradation; Gram-Schmidt (GS) spectral sharpening; IKONOS satellite data; Image fusion; Image resolution; Image sensors; intensity-hue-saturation (IHS) transform; Mathematical models; multispectral (MS) imagery; Multivariate regression; Preprocessing; Principal component analysis; QuickBird images; Radiometry; Regression; Satellites; Spatial resolution; Spectra; Studies

In this paper, multivariate regression is adopted to improve spectral quality, without diminishing spatial quality, in image fusion methods based on the well-established component substitution (CS) approach. A general scheme that is capable of modeling any CS image fusion method is presented and dis...