An efficient and fast algorithm for estimating the frequencies of 2-D superimposed exponential signals in presence of zero-mean multiplicative and additive noise

In this paper, a computationally efficient algorithm is proposed for estimating the parameters of two-dimensional (2-D) superimposed exponential signals in presence of independently and identically distributed (i.i.d.) zero-mean multiplicative and additive noise. It is observed that the estimator is consistent and works quite well in terms of biases and mean squared errors. Moreover, the algorithm is efficient when multiple 2-D frequencies pairs share a same 1-D frequency component and the estimators attain the same convergence rate with the least squares estimator (LSE) in presence of additive noise. Finally, it is observed that the algorithm can be used to estimate the frequencies of the evanescent component of texture accurately.