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4 December 2000 Wavelet and multirate denoising for signal-dependent noise
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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) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Bruno Aiazzi, Luciano Alparone, Stefano Baronti, and Andrea Garzelli "Wavelet and multirate denoising for signal-dependent noise", Proc. SPIE 4119, Wavelet Applications in Signal and Image Processing VIII, (4 December 2000); https://doi.org/10.1117/12.408674
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