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Proceedings Paper

Wavelet and multirate denoising for signal-dependent noise
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Paper Abstract

In this paper, after reviewing a general model to deal with signal-dependent image noise, the well known local linear minimum mean squared error (LLMMSE) filter is derived for the most general case. Signal-dependent noise filtering is approached in a multiresolution framework either by LLMMSE processing ratios of combinations of lowpass images, which are tailored to the noise model in order to mitigate its signal-dependence, or by thresholding a normalized nonredundant wavelet transform designed to yield signal- independent noisy coefficients as well. Experimental results demonstrate that the Laplacian pyramid approach largely outperform LLMMSE filtering on a unique scale and is still superior to wavelet denoising by soft-thresholding.

Paper Details

Date Published: 4 December 2000
PDF: 10 pages
Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); doi: 10.1117/12.408674
Show Author Affiliations
Bruno Aiazzi, Research Institute on Electromagnetic Waves (Italy)
Luciano Alparone, Univ. degli Studi di Firenze (Italy)
Stefano Baronti, Research Institute on Electromagnetic Waves (Italy)
Andrea Garzelli, Univ. degli Studi di Siena (Italy)


Published in SPIE Proceedings Vol. 4119:
Wavelet Applications in Signal and Image Processing VIII
Akram Aldroubi; Andrew F. Laine; Michael A. Unser, Editor(s)

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