sigpy.monte_carlo_sure¶

sigpy.monte_carlo_sure(f, y, sigma, eps=1e-10)[source]¶

Monte Carlo Stein Unbiased Risk Estimator (SURE).

Monte carlo SURE assumes the observation y = x + e, where e is a white Gaussian array with standard deviation sigma. Monte carlo SURE provides an unbiased estimate of mean-squared error, ie: 1 / n || f(y) - x ||_2^2

Parameters:	f (function) – x -> f(x). y (array) – observed measurement. sigma (float) – noise standard deviation.
Returns:	SURE.
Return type:	float

References

Ramani, S., Blu, T. and Unser, M. 2008. Monte-Carlo Sure: A Black-Box Optimization of Regularization Parameters for General Denoising Algorithms. IEEE Transactions on Image Processing 17, 9 (2008), 1540-1554.