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July 1972 (vol. 21 no. 7)
pp. 636-641
W.K. Pratt, Department of Electrical Engineering, University of Southern California
The classical signal processing technique known as Wiener filtering has been extended to the processing of one-and two-dimensional discrete data by digital operations with emphasis on reduction of the computational requirements. In the generalized Wiener filtering process a unitary transformation, such as the discrete Fourier, Hadamard, or Karhunen-Lo?ve transform is performed on the data that is assumed to be composed of additive signal and noise components. The transformed data is then modified by a filter function, and the inverse transformation is performed to obtain the discrete system output. The filter function is chosen to provide the best mean square estimate of the signal portion of the input data.
Index Terms:
Data transforms, filtering, Fourier transform, Hadamard transform, image enhancement, Karhunen-Lo?ve transform, two-dimensional signal processing, Wiener filter.
Citation:
W.K. Pratt, "Generalized Wiener Filtering Computation Techniques," IEEE Transactions on Computers, vol. 21, no. 7, pp. 636-641, July 1972, doi:10.1109/T-C.1972.223567
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