Preprocessing of AVIRIS and Hyperion hyperspectral data is a challenging and time consuming process. A significant portion of this preprocessing effort is related to the removal of specific bands for the selection of an optimal band set. Bad bands are characterized by criteria such as noise and low responsivity. Noise is the interference resulting from atmospheric absorption phenomena and may be sensor generated. Responsivity refers to the bands representing wavelengths near the extremes of the sensors' focal plane(s).
This research streamlines the preprocessing flow, thus minimizing production time and effort. In addition, this overview will help to expand the user community beyond remote sensing experts and facilitate the accessibility of hyperspectral data to application experts in various fields. This will be accomplished by improving the end user's understanding of the preprocessing steps and their ability to interpret these data types.© (2004) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.