Fast Frequency Template Matching Using Higher Order Statistics

This correspondence proposes a novel template matching technique using a fourth central moment. The fourth central moment is an established estimator which uses higher order statistics theory, important in the presence of an additive Gaussian noise. By use of some substitutions and complex arithmetic, computation of the fourth central moment is derived from correlation functions of substituting functions. The fourth central moment can be computed using the fast Fourier transform (FFT) approach. Simulation results show that the proposed algorithm performs better than the classical estimators in terms of robustness, while the extra computational cost is negligible.