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bmode_picmus_experiment.m
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bmode_picmus_experiment.m
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% Reproduce the PICMUS experiment of Section V.B of the paper
% "Non-stationary Blur Evaluation for Ultrasound Image Restoration",
% submitted to IEEE Transactions on Computational imaging
% Author: Adrien Besson
% Signal Processing Laboratory 5 (LTS5), EPFL
% email address: adrien.besson@epfl.ch
% July 2018
clear all;
close all;
clc
%-- Add path
addpath(genpath('utils'));
%-- Output filename
list_filename_output = {'results/picmus_varying_15.mat','results/picmus_est_15.mat', 'results/picmus_constant_15.mat'; 'results/picmus_varying_13.mat','results/picmus_est_13.mat', 'results/picmus_constant_13.mat'};
%-- Parameters
flag_psf_meth = [3 2 1];
list_p = [1.5, 1.3];
maximum_iterations = 100;
flag_display = 0;
regularization_parameters = [5e-6, 4.2, 8; 2.5e-5, 1.4, 2.6];
%-- Loop to generate the B-mode images of the carotids
for kk = 1:numel(list_p)
%-- Considered regularization parameters
reg_param_kk = regularization_parameters(kk, :);
%-- Considered value of p
p = list_p(kk);
%-- Considered output filenames
output_filenames = list_filename_output(kk, :);
for pp = 1:numel(flag_psf_meth)
%-- Current PSF method
psf_meth = flag_psf_meth(pp);
%-- Current output filename
filename_out = output_filenames{pp};
%-- Current regularization parameter
reg_parameter = reg_param_kk(pp);
%-- Experiment
deconvolution_picmus(psf_meth, flag_display, filename_out, p, reg_parameter, maximum_iterations);
end
%-- Compute the metrics
compute_picmus_metrics(output_filenames);
%-- Display the lateral PSF
display_lat_psf(output_filenames);
end