Paper
7 October 2009 Ameliorating the spatial resolution of Hyperion hyperspectral data
Konstantinos G. Nikolakopoulos, Panagiotis I. Tsombos, George A. Skianis, Dimitrios A. Vaiopoulos
Author Affiliations +
Abstract
In this study seven fusion techniques and more especially the Ehlers, Gram-Schmidt, High Pass Filter, Local Mean Matching (LMM), Local Mean and Variance Matching (LMVM), Pansharp and PCA, were used for the fusion of Hyperion hyperspectral data with ALI panchromatic data. Both sensors are onboard on EO-1 satellite and the data are collected simultaneously. The panchromatic data has a spatial resolution of 10m while the hyperspectral data has a spatial resolution of 30m. All the fusion techniques are designed for use with classical multispectral data. Thus, it is quite interesting to investigate the assessment of the common used fusion algorithms with the hyperspectral data. The area of study is the broader area of North Western Athens near to Thrakomakedones village.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Konstantinos G. Nikolakopoulos, Panagiotis I. Tsombos, George A. Skianis, and Dimitrios A. Vaiopoulos "Ameliorating the spatial resolution of Hyperion hyperspectral data", Proc. SPIE 7478, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IX, 74780G (7 October 2009); https://doi.org/10.1117/12.830272
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KEYWORDS
RGB color model

Image fusion

Spatial resolution

Principal component analysis

Data fusion

Linear filtering

Alternate lighting of surfaces

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