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SURE-Based Wavelet Thresholding Integrating Inter-Scale Dependencies

F. Luisier, T. Blu, M. Unser

Proceedings of the 2006 IEEE International Conference on Image Processing (ICIP'06), Atlanta GA, USA, October 8-11, 2006, pp. 1457-1460.



We propose here a new pointwise wavelet thresholding function that incorporates inter-scale dependencies. This non-linear function depends on a set of four linear parameters per subband which are set by minimizing Stein's unbiased MSE estimate (SURE). Our approach assumes additive Gaussian white noise.

In order for the inter-scale dependencies to be faithfully taken into account, we also develop a rigorous feature alignment processing, that is adapted to arbitrary wavelet filters (e.g. non-symmetric filters).

Finally, we demonstrate the efficiency of our denoising approach in simulations over a wide range of noise levels for a representative set of standard images.


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