Image Denoising by Pointwise Thresholding of the Undecimated Wavelet Coefficients: A Global Sure Optimum
F. Luisier, T. Blu
Proceedings of the Thirty-Second International Conference on Acoustics, Speech, and Signal Processing (ICASSP'07), Honolulu HI, USA, April 15-20, 2007, in press.
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We devise a new undecimated wavelet thresholding for denoising images corrupted by additive Gaussian white noise. The first key point of our approach is the use of a linearly parameterized pointwise thresholding function. The second key point consists in optimizing the parameters globally by minimizing Stein's unbiased MSE estimate (SURE) directly in the image-domain, and not separately in the wavelet subbands.
Amazingly, our method gives similar results to the best state-of-the-art algorithms, despite using only a simple pointwise thresholding function; we demonstrate it in simulations over a wide range of noise levels for a representative set of standard grayscale images.