Extraction of Hyperspectral Scene Statistics and Scene Realization

摘要

A method for the extraction of spectral and spatial scene statistics from hyperspectral data is discussed. The method is designed to work on atmospherically compensated data in the visible/SWIR or the Thermal IR (TIR). The statistics are determined from the fractional abundance images obtained from spectral un-mixing of the scene. The statistical quantities that are extracted include endmember abundance means, variances, and correlation lengths. These quantities are used to construct a high spatial resolution reflectance or emissivity/temperature surface using a fast autoregressive texture generation tool. The spectral complexity of the synthetic surfaces have been evaluated by inserting objects for detection and calculating ROC curves. Preliminary results indicate that synthetic scenes with realistic levels of spectral clutter can be generated using spectral and spatial statistics determined from endmember fractional abundance maps. This work is motivated by the need for realistic hyperspectral scene generation capabilities to test future hyperspectral sensor concepts.