Blind optimization of algorithm parameters for signal denoising by Monte-Carlo SURE
Blind optimization of algorithm parameters for signal denoising by Monte-Carlo SURE
We consider the problem of optimizing the parameters of an arbitrary denoising algorithm by minimizing Stein's unbiased risk estimate (SURE) which provides a means of assessing the true mean-squared-error (MSE) purely from the measured data assuming that it is corrupted by Gaussian noise. To accomplish this, we propose a novel …