Toward Improved Ranking Metrics
IEEE Transactions on Pattern Analysis and Machine Intelligence
Higher-order statistics based blind estimation of non-Gaussian bidimensional moving average models
Signal Processing - Fractional calculus applications in signals and systems
Time delay estimation with unknown spatially correlated Gaussian noise
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
Blind separation of any source distributions via high-order statistics
Signal Processing
Third-order cumulants based methods for continuous-time errors-in-variables model identification
Automatica (Journal of IFAC)
A Modified Split-Radix FFT With Fewer Arithmetic Operations
IEEE Transactions on Signal Processing
Fast adaptive algorithms for AR parameters estimation using higherorder statistics
IEEE Transactions on Signal Processing
Motion estimation using higher order statistics
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
HOS-based image sequence noise removal
IEEE Transactions on Image Processing
Successive elimination algorithm for motion estimation
IEEE Transactions on Image Processing
Image motion estimation algorithms using cumulants
IEEE Transactions on Image Processing
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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.