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27 October 1999 Autocorrelogram approach for estimating the spectral-spatial variability of hyperspectral images
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Abstract
The amount of information contained in a single hyperspectral image is overwhelming for the human operator. As a result, assessing the spatial and spectral variability of a hyperspectral image is very difficult. The existing techniques mainly rely on different preprocessing algorithms that reduce the high-dimensionality of the hyperspectral data down to a few images that can be visualized using traditional RGB or RGBI combinations. The proposed auto-correlogram approach provides a simple framework for reducing a hyperspectral image cube to a single grayscale image that is easy to interpret and screen for spectral anomalies.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dimitry Y. Frolov "Autocorrelogram approach for estimating the spectral-spatial variability of hyperspectral images", Proc. SPIE 3753, Imaging Spectrometry V, (27 October 1999); https://doi.org/10.1117/12.366307
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