5 December 2001 Optimal rejection of multiplicative noise via adaptive shrinkage of undecimated wavelet coefficients
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Abstract
In this paper speckle reduction is approached as a Wiener-like filtering performed in the wavelet domain by means of an adaptive shrinkage of the detail coefficients of an undecimated decomposition. The amplitude of each coefficient is divided by the variance ratio of the noisy coefficient to the noise-free one. All the above quantities are analytically calculated from the speckled image, the speckle variance, and the wavelet filters. On the test image Lenna corrupted by synthetic speckle, the proposed method outperforms Kuan's LLMMSE filtering by almost 3 dB SNR. Experiments carried out on true and synthetic speckled images demonstrate that the visual quality of the results is excellent in terms of both background smoothing and preservation of edge sharpness and textures. The absence of decimation in the wavelet decomposition avoids the typical ringing impairments produced by critically-subsampled wavelet-based denoising.
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Luciano Alparone, Luciano Alparone, Nicola Anghele, Nicola Anghele, Fabrizio Argenti, Fabrizio Argenti, } "Optimal rejection of multiplicative noise via adaptive shrinkage of undecimated wavelet coefficients", Proc. SPIE 4478, Wavelets: Applications in Signal and Image Processing IX, (5 December 2001); doi: 10.1117/12.449723; https://doi.org/10.1117/12.449723
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