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Thermography applications in buried object detection, which are appropriate for antipersonnel mines detection in the humanitarian demining, have been limited to mine-contaminated regions with homogeneous and vegetationless soils. Realistic non-homogeneity generally brings about considerable noise convoluted with the buried object thermal response. One source of the noise is surface non-homogeneity, interpretable as quasi-random signal which screens the buried object thermal response. This interpretation makes possible the noise reduction using advanced thermogram processing algorithms, such as Independent component analysis. We apply it to thermograms obtained using controllable experimental conditions and realistic three-dimensional, non-stationary heat transfer program. Numerical estimates of the degree of soil non-homogeneity, which can be reduced in thermograms, are obtained for a particular, representative class of buried objects and soil surface non-homogeneity. In particular, dependence of the results on concentration of surface point-like non-homogeneities is determined.
thermography; buried objects; antipersonnel landmines detection; random noise; independent component analysis
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