Image Denoising by Pointwise Thresholding of the Undecimated Wavelet Coefficients: A Global SURE Optimum

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.

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Proceedings of the Thirty-Second IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP'07), Honolulu HI, USA, I-593–I-596

 Record created 2015-09-18, last modified 2018-10-07

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