Bridging Compression to Wavelet Thresholding as a Denoising Method

Some past work has suggested that lossy compression can be a good denoising tool. Building on this theme, we make the connection that quantization of transform coefficients approximates the operation of Donoho-Johnstone's wavelet thresholding, to conclude that compression (via coefficient quantization) is appropriate for filtering noise from signal. The method of quantization is scale adaptive and is facilitated by a criterion similar to Rissanen's minimum description length principle. Results show that a small number of quantization levels achieves almost the same performance of full precision thresholding, suggesting that denoising is mainly due to the zero-zone and that the full precision of the thresheld coefficients is of secondary importance.

Published in:
Proceedings Conference on Information Sciences and Systems, 568-573
Presented at:
Conference on Information Sciences and Systems, 1997

 Record created 2005-04-18, last modified 2018-01-27

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