3 March 2000 Wavelet-based denoising from multiple noisy realizations: preliminary experiments
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Abstract
Wavelet-based methods are, at the present time, the most efficient methods for the improvement of the signal to-noise ratio of very noisy images. In this paper, we attempt to improve the quality of restored images by considering multiple realizations of noisy images instead of a unique realization, at constant acquisition time. We investigate several variants for thresholding or shrinking the wavelet coefficients, taking into account the relative standard deviation of the wavelet coefficients, over the multiple realizations, at a given scale, orientation and position. Moreover, for simulations, we try to quantify the quality of restoration by other criteria than the usual mean-square error or signal-to-noise ratio. For doing this, we try to quantify the structuration of the residues.
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Philippe Vautrot, Philippe Vautrot, Anne Ricordeau, Anne Ricordeau, Noel Bonnet, Noel Bonnet, } "Wavelet-based denoising from multiple noisy realizations: preliminary experiments", Proc. SPIE 3961, Nonlinear Image Processing XI, (3 March 2000); doi: 10.1117/12.379400; https://doi.org/10.1117/12.379400
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