Exploiting stochastic partitions for minefield detection

Carey E. Priebe; Tim E. Olson; Dennis M. Healy Jr.

doi:10.1117/12.280879

22 July 1997 Exploiting stochastic partitions for minefield detection

Carey E. Priebe, Tim E. Olson, Dennis M. Healy Jr.

Author Affiliations +

Proceedings Volume 3079, Detection and Remediation Technologies for Mines and Minelike Targets II; (1997) https://doi.org/10.1117/12.280879
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

In many applications one wishes to perform an analysis of the homogeneity of a point process, often as a precursor to more advanced analysis. In general, rejection of the null hypothesis of homogeneity may imply a requirement for further analysis. In remote sensing for minefield detection, for example, homogeneity may correspond to the 'no minefield' case while regions of nonhomogeneity warrant closer inspection. This paper considers a version of the spatial scan process which uses stochastic and disjoint scan regions. The associated test for nonhomogeneity has the potential for improved power over conventional alternative sin applications where the point process is embedded in a general random field. Specifically, when the locations of any subregions of nonhomogeneity in the point process correspond to regions in the underlying field which can be segmented as distinct from their surroundings, the test derived here is recommended. The application to the detection of point clusters in gray-scale imagery, particularly minefields in multispectral imagery, is investigated.

Citation Download Citation

Carey E. Priebe, Tim E. Olson, and Dennis M. Healy Jr. "Exploiting stochastic partitions for minefield detection", Proc. SPIE 3079, Detection and Remediation Technologies for Mines and Minelike Targets II, (22 July 1997); https://doi.org/10.1117/12.280879

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