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.

Wavelet and multirate denoising for signal-dependent noise

Bruno Aiazzi;Luciano Alparone;Stefano Baronti;Andrea Garzelli
2000

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.
2000
Istituto di Fisica Applicata - IFAC
0-8194-3764-6
Film-grain noise
generalized rational Laplacian pyramid
LLMMSE local statistics filtering
speckle
wavelet thresholding
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/241806
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