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Proceedings Paper

Performance of spatial sharpening methods for hyperspectral imagery
Author(s): Brian A. Gorin
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Paper Abstract

“Pan” or single broadband sharpening of multispectral (low spatial resolution) imagery is currently deployed on airborne and satellite systems. The challenges for spatial sharpening of hyperspectral imagery are the focus of the current study, which utilizes high spatial resolution, geo-referenced multispectral imagery available from the QuickBird satellite with low spatial resolution AVIRIS hyperspectral imagery. Performance analysis of a spectral normalization method known as the CN Spectral Sharpening (CNSS) enables correction for the mismatch in spectral radiance levels of the two input images due to differences of sensor platform altitude, date of imaging, atmospheric path and solar irradiance conditions. The BAE Systems Spectral Similarity Scale is utilized to optimize the spectral match between the unsharpened input and of selected regions of interest, combined with computing the spectral correlation difference matrix between the unsharpened input and sharpened output. Performance evaluation includes comparison of the histogram spectral means and standard deviations of selected regions of interest, combined with computing the spectral correlation difference matrix between the unsharpened and sharpened AVIRIS data. Significantly similarity is demonstrated with high spectral correlation, yet high variance change between the green and red MSI channels results in a discontinuity region of the corresponding HSI bands. Future systems incorporating collocated high spatial resolution MSI with lower resolution HSI will enable automated spatial sharpening with improved spectral accuracy.

Paper Details

Date Published: 30 August 2004
PDF: 14 pages
Proc. SPIE 5409, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications, (30 August 2004); doi: 10.1117/12.554336
Show Author Affiliations
Brian A. Gorin, BAE Systems (United States)


Published in SPIE Proceedings Vol. 5409:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications
Arthur A. Andraitis; Gerard J. Leygraaf, Editor(s)

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