Two-dimensional processing of spectrogram data

In this paper we demonstrate a new application of two-dimensional (2-D) signal processing. The 2-D data consists of frequency-time plots or spectrograms derived from non-stationary one-dimensional data. We show that 2-D processing can offer significant advantages over the standard spectral estimation procedures used to obtain spectrograms. These advantages mainly occur because the frequency data is correlated in time, a fact ignored in conventional spectrogram procedures. Recursive fan type filters are designed by the homomorphic method and applied to the spectrogram data. Significant improvement is obtained for a simulation consisting of chirp type signals in white noise.