Wavelet-based image denoising using generalized cross validation

Maarten Jansen; Adhemar Bultheel

doi:10.1117/12.274110

25 April 1997 Wavelet-based image denoising using generalized cross validation

Maarten Jansen, Adhemar Bultheel

Proceedings Volume 3034, Medical Imaging 1997: Image Processing; (1997) https://doi.org/10.1117/12.274110
Event: Medical Imaging 1997, 1997, Newport Beach, CA, United States

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.

Citation Download Citation

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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