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25 April 1997 Wavelet-based image denoising using generalized cross validation
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Abstract
De-noising algorithms based on wavelet thresholding replace small wavelet coefficients by zero and keep or shrink the coefficients with absolute value above the threshold. The optimal threshold minimizes the error of the result as compared to the unknown, exact data. To estimate this optimal threshold, we use generalized cross validation. This procedure does not require an estimation for the noise energy. Originally, this method assumes uncorrelated noise, and an orthogonal wavelet transform. In this paper we investigate the possibilities of this method for less restrictive conditions.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maarten Jansen and Adhemar Bultheel "Wavelet-based image denoising using generalized cross validation", Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); https://doi.org/10.1117/12.274110
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