Symmetric lifting factorization and matrix representation of biorthogonal wavelet transforms. (English) Zbl 1044.94006
Summary: This paper introduces some properties of symmetric Laurent polynomials, and then extends the Euclidean algorithm to symmetric Laurent polynomials. The new results are used to investigate factorization of polyphase matrices for biorthogonal finite filters. It is shown that there exists one and only one symmetric factorization of the polyphase matrix, and the symmetric factorization can be determined directly and efficiently using the Euclidean algorithm for symmetric Laurent polynomials. Finally, symmetric implementation and matrix representation of biorthogonal wavelet transforms are introduced, and the study demonstrates that the symmetric implementation has the least multiplication number in all lifting implementations and that it is equivalent to a matrix transform on a finite-dimensional vector space.
MSC:
94A12 | Signal theory (characterization, reconstruction, filtering, etc.) |
42C40 | Nontrigonometric harmonic analysis involving wavelets and other special systems |
11A05 | Multiplicative structure; Euclidean algorithm; greatest common divisors |
15A23 | Factorization of matrices |
Keywords:
Euclidean algorithm; polyphase matrix; symmetric Laurent polynomial; symmetric lifting factorization; biorthogonal wavelet transform; symmetric implementation; matrix representation; lossless compressionReferences:
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