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/Sijbers_Aja.m
% Sijbers-Aja's method based on eq. 24, page 1400 in % S. Aja-Fern醤dez, et al., Noise estimation in single-and multiple-coil magnetic resonance data based on statistical models, % Magnetic Resonance Imaging, vol. 27(10), pp. 1397-1409, 2009 % % 05/01/2013 % % 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 % bins - histogram bins % % FUNCTION RETURNS % sigma - estimated noise level (sigma) % % USAGE % sigma_estimated = Sijbers_Aja(data, [7, 7], 1000) function [sigma] = Sijbers_Aja(data, window, bins) N = window(1) * window(2); FUNCTION = @(x)( (1/(N-1))*sum(x.^2) ); % function calculates second-order moment EX2 = colfilt(data, window, 'sliding', FUNCTION); EX2 = sqrt(EX2); % initial noise level searching [histogram_p, histogram_x] = hist(EX2(:), bins); histogram_p_filtered = filtfilt(ones(1,25), 1, histogram_p); % low-pass filter (window 1x25) [value, index] = max(histogram_p_filtered); fc = histogram_x(2*index); % minimization procedure - least-squares fitting procedure [n, l] = hist(EX2(EX2 <= fc), bins); % letters according to eq. 2 in 'Noise estimation in single-and multiple-coil magnetic resonance data based on statistical models', p. 1400 Nk = sum(n); K = bins; F_MIN = @(x) ( Nk*log( gammainc(N, (l(1).^2) .* (N./(2*x.^2)), 'upper') - gammainc(N, (l(K).^2) .* (N./(2*x.^2)), 'upper') ) - sum(n(2:K) .* log( gammainc(N, (l(1:K-1).^2) .* (N./(2*x.^2)), 'upper') - gammainc(N, (l(2:K).^2) .* (N./(2*x.^2)), 'upper') )) ); % according to eq. 24, p.1340 % x - sigma sigma0 = histogram_x(index); [sigma, fval, exitflag] = fminsearch(F_MIN, sigma0); if(exitflag == 0) fprintf('<strong> Sijbers-Aja error! </strong>\n') end