Using Steins Unbiased Risk Estimate to Optimize Level of Decomposition in Stationary Wavelet Transform Denoising
Abstract
A method of determining the optimum number of levels of decomposition in soft-thresholding wavelet denoising using Stationary Wavelet Transform is presented here. The method calculates the risk at each level of decomposition using Steins Unbiased Risk Estimate, analogous to calculating the sum square error of the denoising process. The SURE risk is found to reach minimum at the same level of decomposition as the sum square error. The advantage of this method is that the clean signal need not be known a priori. The method can be used with either a priori known noise variance or an estimate of the noise variance. This allows the determination of the optimum level of decomposition for wavelet denoising of an unknown signal so long as the noise variance can be estimated.
Keywords
Cite
@article{arxiv.1701.03594,
title = {Using Steins Unbiased Risk Estimate to Optimize Level of Decomposition in Stationary Wavelet Transform Denoising},
author = {Mohd Rozni Md Yusof and Ahmad Kamal bin Ariffin},
journal= {arXiv preprint arXiv:1701.03594},
year = {2017}
}
Comments
23 pages, to submit either to Signal Processing or Digital Signal Processing