Cross correlogram spectral matching: Application to surface mineralogical mapping by using AVIRIS data from Cuprite, Nevada

A new approach toward mineral mapping from imaging spectrometer data is presented, using a spectral matching algorithm based on the cross correlogram. A cross correlogram is constructed by calculating the cross correlation at different match positions, m, between a test spectrum (i.e., a pixel spectrum) and a reference spectrum (i.e., a laboratory mineral spectrum or a pixel spect-nlm Known to represent a mineral of interest) by shifting the reference spectrum over subsequent channel positions. The cross correlogram for perfectly matching reference and test spectra is a parabola around the central matching number (m = 0) with a peak correlation of 1. In laboratory spectra, deviations from this shape indicate differences in mineralogy, whereas, in image data, this may be partly attributed to spectral mixing, noise, changes in atmospheric and illumination conditions, and other scene and sensor-dependent variables. A cross correlogram spectral matching algorithm was designed and tested on 1994 data from the airborne visible/infrared imaging spectrometer of the Cuprite mining area. Accurate mapping of kaolinite, alunite, and buddingtonite was achieved by extracting three parameters from the cross correlograms that were constructed on a pixel-by-pixel basis: the correlation coefficient at match position. zero, the moment of skewness (based on the correlation differences between match numbers of equal but reversed signs; e.g., m = 4 and m = -4), and the significance (based on a Student's t-test of the validity of the correlation coefficients). (C) Elsevier Science Inc., 1997.