Abstract
The interscale Stein's unbiased risk estimator (SURE)-based approach introduced by Luisier is a recent state of the art in orthonormal wavelet denoising, but it is not very effective for those images that have substantial high-frequency contents. To solve this problem, we introduce an effective integration of the intrascale correlations within the interscale SURE-based approach. We show that the consideration of both the intrascale and interscale dependencies of wavelet coefficients brings more denoising gains than those obtained with the interscale SURE-based approach, especially for denoising of images that have substantial textures such as the Barbara image.
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