Land Mine Detection in Rotationally Invariant Noise Fields
Paper i proceeding, 2001
This paper proposes a method to detect infrared land
mine signatures embedded in rotationally invariant colored
noise. A common problem in statistical image processing
is high dimensionality. This causes a need for
large sets of training data. To overcome this, an alternative
formulation of the Generalized Likelihood Ratio
Test (GLRT) is presented. This formulation makes it
possible to utilize the circular-symmetry, rendering a
substantial decrease in model dimensionality and consequently,
in the amount of training data needed. Simulations
indicate that a significant gain in performance
can be achieved compared to both the non-parameterized
detector and the matched filter.