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

Abstract

A new approach toward mineral mapping front imaging spectrometer data is presented, using a spectral matching algorithm- based on the cross correlograrn. A cross correlograin is constructed b y 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 spectrum 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 I. 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 correlograin spectral snatching algorithm was designed and tested on 1994 data from the airborne visible/infrared imaging spectrometer of the Cuprite mining area. Accurrate mapping of kaolinite, alunite, and buddingtonite was achieved by extracting three parameters from the cross correlograins that were constructed on a pixel-by-pixel basis: the correlation coefficient at match position zero, the rrurrrtent 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).