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Spatial statistics of natural-terrain imagery. I. Non-Gaussian IR backgrounds and long-range correlations

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Abstract

We report on an analysis of statistical correlations in midwave IR imagery acquired from an airborne sensor flying over dense forest and sparsely covered terrain. We test for wide-sense stationarity, compute ensemble histograms, and estimate the autocovariance functions with associated error bars. We find that the statistics are stationary but non-Gaussian. Contrary to previous studies, we do not find that the correlations are described by decaying exponential functions. In fact, we find evidence for long-range correlations in the imagery, with autocovariance functions described by a relatively simple formula with power-law falloff.

© 1997 Optical Society of America

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