www.gusucode.com > 瑞利信道下噪声能量的估计源码程序 > 瑞利信道下噪声能量的估计源码程序/MSP_estimate_version1/ReferenceMethods/Aja_second_order_moment_granularity.m
% Noise estimation based on the local second-order moment of Rayleigh % distribution denoted as Aja's method #1 based on eq. 17 in % S. Aja-Fernandez, et al., Noise and Signal Estimation in Magnitude MRI and Rician Distributed Images: % A LMMSE Approach, IEEE Transactions on Image Processing, vol. 17, no. 8, 2008, pp. 1383-1398 % % 27/12/2013 % % Tomasz Pieciak % AGH university of Science and Technology, Krakow, Poland % pieciak@agh.edu.pl, http://home.agh.edu.pl/pieciak/ % % ARGUMENTS % data - single-coil MRI data % window - sliding window size % granularity - histogram granularity % % FUNCTION RETURNS % sigma - estimated noise level (sigma) % % USAGE % sigma_estimated = Aja_second_order_moment_granularity(data, [7, 7], 5) function [sigma] = Aja_second_order_moment_granularity(data, window, granularity) N = window(1) * window(2); FUNCTION = @(x)( (1/(N-1))*sum(x.^2) ); % function calculates second-order moment; according to eq. 16 EX2 = colfilt(data, window, 'sliding', FUNCTION); % calculate histogram [histogram_x, histogram_p] = CalculateHistogram(EX2(:), granularity); [value, index] = max(histogram_p); sigma = sqrt(0.5*index); % estimation according to eq. 17