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Two-dimensional spectral factorization with applications in recursive digital filtering

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2 Author(s)
M. Ekstrom ; University of California, Livermore, CA, USA ; J. Woods

The concept of spectral factorization is extended to two dimensions in such a way as to preserve the analytic characteristics of the factors. The factorization makes use of a homomorphic transform procedure due to Wiener. The resulting factors are shown to be recursively computable and stable in agreement with one-dimensional (1-D) spectral factorization. The factors are not generally two-dimensional (2-D) polynomials, but can be approximated as such. These results are applied to 2-D recursive filtering, filter design, and a computationally attractive stability test for recursive filters.

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IEEE Transactions on Acoustics, Speech, and Signal Processing  (Volume:24 ,  Issue: 2 )