Proceedings PaperAnalysis Of Spatially Correlated Images With Implications For Independent Sampling And Linear Correlator Image Detection
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For an image not dominated by regular features or structures, it is often desireable to quantify its "information content" in terms of an effective number of independent samples, Ni. This quantity is useful in several applications such as understanding the performance of certain image detection and registration schemes or calculating data redundancy. This paper offers a definition for Ni and applies it to three types of correlation functions postulated as spanning the range of "real world" image correlation: exponential, Whittle, and Gaussian correlation models. As an illustration of its use and importance, Ni is calculated for all three models at three distinct stages of a matched filter image detection system. Limited analysis of one type of aerial imagery supports the hypothesis that a Whittle model may be the canonical form of image correlation.