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

机译:自然地形图像的空间统计。一,非高斯红外背景和远距离相关

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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.
机译:我们报告了中波红外图像中的统计相关性分析,该图像是从飞越茂密的森林和稀疏覆盖的地形的机载传感器获取的。我们测试广义的平稳性,计算整体直方图,并估计带有相关误差线的自协方差函数。我们发现统计量是平稳的,但不是高斯的。与以前的研究相反,我们没有发现相关性是通过衰减指数函数来描述的。实际上,我们发现了图像中存在远距离相关性的证据,其中自协方差函数由具有幂律衰减的相对简单的公式描述。

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