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Proceedings Paper

Nonlinear processing of a shift-invariant discrete wavelet transform (DWT) for noise reduction
Author(s): Markus Lang; Haitao Guo; Jan Erik Odegard; C. Sidney Burrus; Raymond O. Wells
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Paper Abstract

A novel approach for noise reduction is presented. Similar to Donoho, we employ thresholding in some wavelet transform domain but use a nondecimated and consequently redundant wavelet transform instead of the usual orthogonal one. Another difference is the shift invariance as opposed to the traditional orthogonal wavelet transform. We show that this new approach can be interpreted as a repeated application of Donoho's original method. The main feature is, however, a dramatically improved noise reduction compared to Donoho's approach, both in terms of the l2 error and visually, for a large class of signals. This is shown by theoretical and experimental results, including synthetic aperture radar (SAR) images.

Paper Details

Date Published: 6 April 1995
PDF: 12 pages
Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); doi: 10.1117/12.205427
Show Author Affiliations
Markus Lang, Rice Univ. (United States)
Haitao Guo, Rice Univ. (United States)
Jan Erik Odegard, Rice Univ. (United States)
C. Sidney Burrus, Rice Univ. (United States)
Raymond O. Wells, Rice Univ. (United States)


Published in SPIE Proceedings Vol. 2491:
Wavelet Applications II
Harold H. Szu, Editor(s)

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