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Proceedings Paper

Band sharpening technique for multiresolution spectral data sets using regression residuals
Author(s): Virgil S. Lewis
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Paper Abstract

This paper proposes a band sharpening technique for data sets with multiple bands of data at a fine resolution and one or more bands of data at a coarse resolution. A linear prediction model of the coarse resolution data is calculated using the fine resolution data, along with it's associated residual data. A series of smoothing filters was applied to this residual data and added back into the output of the linear predictor for the final result, which was then compared to the original input data with preliminary exploratory analysis. The most effective smoothing filter appears to be a median filter of the order n+1 (with n being the nearest integer to the ratio of coarse resolution to fine resolution data). Initial radiometric comparisons are also presented here.

Paper Details

Date Published: 20 August 2001
PDF: 8 pages
Proc. SPIE 4381, Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII, (20 August 2001); doi: 10.1117/12.437051
Show Author Affiliations
Virgil S. Lewis, National Imagery and Mapping Agency (United States)

Published in SPIE Proceedings Vol. 4381:
Algorithms for Multispectral, Hyperspectral, and Ultraspectral Imagery VII
Sylvia S. Shen; Michael R. Descour, Editor(s)

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