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Proceedings Paper

Hyperspectral resolution enhancement with an arbitrary point spread function
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Paper Abstract

Several remote sensing platforms have been developed that include boresighted hyperspectral and panchromatic imaging sensors. The NASA EO-1 platform is a prime example, and includes the hyperspectral Hyperion sensor and multispectral Advanced Land Imager (ALI). Typically in these cases, the panchromatic imagery that is produced is of higher spatial resolution than the hyperspectral imagery. In the NASA EO-1 case, for example, Hyperion exhibits a 30 meter ground sample distance (GSD) and the ALI includes a 10 meter GSD panchromatic band. This paper addresses the issue of combining concurrent imagery from both sources with the goal of deriving a hyperspectral image with the spectral resolution of the hyperspectral data source and the spatial resolution of the panchromatic data source. Specifically, the use of a stochastic mixing model (SMM) along with MAP estimation is extended to the case where the point spread function of the hyperspectral sensor is not assumed to be detector-limited. This case is addressed by using an iterative optimization strategy based on a parametric description of the point spread function of the hyperspectral sensor. Results indicate that the iterative approach appears to find the optimal MAP solution. This paper summarizes the MAP/SMM enhancement method, the iterative optimization strategy, and enhancement results.

Paper Details

Date Published: 15 October 2004
PDF: 11 pages
Proc. SPIE 5546, Imaging Spectrometry X, (15 October 2004); doi: 10.1117/12.553237
Show Author Affiliations
Michael T. Eismann, Air Force Research Lab. (United States)
Russell C. Hardie, Univ. of Dayton (United States)


Published in SPIE Proceedings Vol. 5546:
Imaging Spectrometry X
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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