23 June 1997 Stochastic clutter characterization in NASA/JPL AIRSAR imagery
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The background or clutter in SAR imagery has a significant stochastic component. It is often desirable to be able to rapidly characterize the clutter distribution and/or classify the background type based on the clutter distribution. We model the stochastic clutter as a piecewise stationary random field. The individual stationary subregions of homogeneity in the field can then be characterized by marginal density functions. This level of characterization is often sufficient for determination of clutter type on a local basis. We present a technique for the simultaneous characterization of the subregions of a random field based on semiparametric density estimation on the entire random field. This technique is based on a borrowed strength methodology that allows the use of observation from potentially dissimilar subregions to improve local density estimation and hence random process characterization. This approach is demonstrated on a set of NASA/JPL AIRSAR images, including an example of clutter dependent crash site detection.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
George W. Rogers, George W. Rogers, Rick D. Roberts, Rick D. Roberts, Houra Rais, Houra Rais, "Stochastic clutter characterization in NASA/JPL AIRSAR imagery", Proc. SPIE 3069, Automatic Target Recognition VII, (23 June 1997); doi: 10.1117/12.277102; https://doi.org/10.1117/12.277102

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