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Fractal Characterization of Hyperspectral ImageryTwo Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral images selected from the Los Angeles area, one representing urban and the other, rural, were used to examine their spatial complexity across their entire spectrum of the remote sensing data. Using the ICAMS (Image Characterization And Modeling System) software, we computed the fractal dimension values via the isarithm and triangular prism methods for all 224 bands in the two AVIRIS scenes. The resultant fractal dimensions reflect changes in image complexity across the spectral range of the hyperspectral images. Both the isarithm and triangular prism methods detect unusually high D values on the spectral bands that fall within the atmospheric absorption and scattering zones where signature to noise ratios are low. Fractal dimensions for the urban area resulted in higher values than for the rural landscape, and the differences between the resulting D values are more distinct in the visible bands. The triangular prism method is sensitive to a few random speckles in the images, leading to a lower dimensionality. On the contrary, the isarithm method will ignore the speckles and focus on the major variation dominating the surface, thus resulting in a higher dimension. It is seen where the fractal curves plotted for the entire bandwidth range of the hyperspectral images could be used to distinguish landscape types as well as for screening noisy bands.
Document ID
19990054705
Acquisition Source
Marshall Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Qiu, Hon-Iie
(NASA Marshall Space Flight Center Huntsville, AL United States)
Lam, Nina Siu-Ngan
(NASA Marshall Space Flight Center Huntsville, AL United States)
Quattrochi, Dale A.
(NASA Marshall Space Flight Center Huntsville, AL United States)
Gamon, John A.
(NASA Marshall Space Flight Center Huntsville, AL United States)
Date Acquired
August 19, 2013
Publication Date
January 1, 1999
Subject Category
Earth Resources And Remote Sensing
Distribution Limits
Public
Copyright
Other

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