Two-dimensional spectral representation with applications

A linear technique for two-dimensional (2D), frequency domain, system modeling has been successfully developed by W.B. Mikhael and H. Yu (1993). Based on the same structure, which is the equation error model, a two-dimensional least-square spectral representation algorithm is presented in this paper. The proposed algorithm efficiently characterizes the 2D complex spectra by a 2D all-pole function with real coefficients. The location, magnitude and phase of the dominant transform components can be exactly retrieved in the 2D frequency domain. It is shown that the number of coefficients of the approximating function is (2M+1), where M is the number of dominant transform components. To illustrate the technique´s accuracy and efficieny its application to image representation and reconstruction is given