Signal-dependent noise may be described by a unique parametric model yielding additive, multiplicative, and film-grain noise. For such a model, adaptive filtering can be written as LLMMSE filtering. Multiresolution processing is exploited to achieve adaptivity also across scale, as SNR increases with the scale of the decomposition, in natural images. A Generalized Laplacian pyramid (GLP) is designed to match the signal-dependent nature of noise, thus allowing LLMMSE filtering to be carried out on its layers. Results from images affected by several types of synthetic noise are pretty superior to those achieved without multiresolution context, by 1 to 2 dB, on an average.
Multiresolution adaptive filtering of signal-dependent noise based on a generalized Laplacian pyramid / Aiazzi, Bruno; Baronti, Stefano; Alparone, Luciano. - STAMPA. - 1:(1997), pp. 381-384. (Intervento presentato al convegno Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) tenutosi a Santa Barbara, CA, USA nel 26 - 29 October 1997) [10.1109/ICIP.1997.647786].
Multiresolution adaptive filtering of signal-dependent noise based on a generalized Laplacian pyramid
ALPARONE, LUCIANO
1997
Abstract
Signal-dependent noise may be described by a unique parametric model yielding additive, multiplicative, and film-grain noise. For such a model, adaptive filtering can be written as LLMMSE filtering. Multiresolution processing is exploited to achieve adaptivity also across scale, as SNR increases with the scale of the decomposition, in natural images. A Generalized Laplacian pyramid (GLP) is designed to match the signal-dependent nature of noise, thus allowing LLMMSE filtering to be carried out on its layers. Results from images affected by several types of synthetic noise are pretty superior to those achieved without multiresolution context, by 1 to 2 dB, on an average.
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