k-Wave User Forum » Topic: use addnoise function does not work in simulation process

k-Wave User Forum » Topic: use addnoise function does not work in simulation process http://www.k-wave.org/forum/topic/use-addnoise-function-does-not-work-in-simulation-process Support for the k-Wave MATLAB toolbox en-US Wed, 13 May 2026 01:49:33 +0000 http://bbpress.org/?v=1.0.2 <![CDATA[Search]]> q http://www.k-wave.org/forum/search.php zhangguangjie on "use addnoise function does not work in simulation process" http://www.k-wave.org/forum/topic/use-addnoise-function-does-not-work-in-simulation-process#post-6640 Thu, 08 Nov 2018 05:56:54 +0000 zhangguangjie 6640@http://www.k-wave.org/forum/ Hello Brad: Thank you very much! Now,I meet a new problem. setting signal_to_noise_ratio = 1, which means SNR=1.12. However,the reconstruction result CNR is lager, which means the noise does not exert a important effect to the reconstruction imaging. why ? I am confused. Thanks in advance. Look forward to your reply. Bradley Treeby on "use addnoise function does not work in simulation process" http://www.k-wave.org/forum/topic/use-addnoise-function-does-not-work-in-simulation-process#post-6634 Tue, 06 Nov 2018 21:46:17 +0000 Bradley Treeby 6634@http://www.k-wave.org/forum/ It looks like you store the sensor data with noise as <code>sensor_data1</code>, but assign the noise-free data to <code>sensor.time_reversal_boundary_data</code>. Brad. zhangguangjie on "use addnoise function does not work in simulation process" http://www.k-wave.org/forum/topic/use-addnoise-function-does-not-work-in-simulation-process#post-6633 Tue, 06 Nov 2018 10:44:13 +0000 zhangguangjie 6633@http://www.k-wave.org/forum/ Hello everyone: I add addnoise function in 3D Time Reversal Reconstruction For A Planar Sensor Example. However, I find it is not impact the reconstruction result whether or not add noise. My code is as follows. I eager to get help from you. % 3D Time Reversal Reconstruction For A Planar Sensor Example % % This example demonstrates the use of k-Wave for the reconstruction of a % three-dimensional photoacoustic wave-field recorded over a planar array % of sensor elements. The sensor data is simulated and then time-reversed % using kspaceFirstOrder3D. It builds on the 3D FFT Reconstruction For A % Planar Sensor and 2D Time Reversal Reconstruction For A Line Sensor % examples. % % author: Bradley Treeby % date: 10th July 2009 % last update: 20th June 2017 % % This function is part of the k-Wave Toolbox (<a href="http://www.k-wave.org" rel="nofollow">http://www.k-wave.org</a>) % Copyright (C) 2009-2017 Bradley Treeby % This file is part of k-Wave. k-Wave is free software: you can % redistribute it and/or modify it under the terms of the GNU Lesser % General Public License as published by the Free Software Foundation, % either version 3 of the License, or (at your option) any later version. % % k-Wave is distributed in the hope that it will be useful, but WITHOUT ANY % WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS % FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for % more details. % % You should have received a copy of the GNU Lesser General Public License % along with k-Wave. If not, see <http://www.gnu.org/licenses/>. clearvars; % ========================================================================= % SIMULATION % ========================================================================= % change scale to 2 to reproduce the higher resolution figures used in the % help file scale = 1; % create the computational grid PML_size = 10; % size of the PML in grid points Nx = 32 * scale - 2 * PML_size; % number of grid points in the x direction Ny = 64 * scale - 2 * PML_size; % number of grid points in the y direction Nz = 64 * scale - 2 * PML_size; % number of grid points in the z direction dx = 0.2e-3 / scale; % grid point spacing in the x direction [m] dy = 0.2e-3 / scale; % grid point spacing in the y direction [m] dz = 0.2e-3 / scale; % grid point spacing in the z direction [m] kgrid = kWaveGrid(Nx, dx, Ny, dy, Nz, dz); % define the properties of the propagation medium medium.sound_speed = 1500; % [m/s] % create initial pressure distribution using makeBall ball_magnitude = 10; % [Pa] ball_radius = 3 * scale; % [grid points] p0 = ball_magnitude * makeBall(Nx, Ny, Nz, Nx/2, Ny/2, Nz/2, ball_radius); % smooth the initial pressure distribution and restore the magnitude p0 = smooth(kgrid, p0, true); % assign to the source structure source.p0 = p0; % define a binary planar sensor sensor.mask = zeros(kgrid.Nx, kgrid.Ny, kgrid.Nz); sensor.mask(1, :, :) = 1; % create the time array kgrid.makeTime(medium.sound_speed); % set the input arguements input_args = {'PMLSize', PML_size, 'PMLInside', false, ... 'PlotPML', false, 'Smooth', false, 'DataCast', 'single'}; % run the simulation sensor_data = kspaceFirstOrder3D(kgrid, medium, source, sensor, input_args{:}); % reset the initial pressure source.p0 = 0; signal_to_noise_ratio = 6; % [dB] [sensor_data1, snr]= addNoise(sensor_data, signal_to_noise_ratio,'peak'); % assign the time reversal data sensor.time_reversal_boundary_data = sensor_data; % run the time-reversal reconstruction p0_recon = kspaceFirstOrder3D(kgrid, medium, source, sensor, input_args{:}); % add first order compensation for only recording over a half plane p0_recon = 2 * p0_recon; % apply a positivity condition p0_recon(p0_recon < 0) = 0; % ========================================================================= % VISUALISATION % ========================================================================= % plot the initial pressure figure; plot_scale = [-10, 10]; subplot(2, 2, 1); imagesc(kgrid.y_vec * 1e3, kgrid.x_vec * 1e3, squeeze(p0(:, :, Nz/2)), plot_scale); title('x-y plane'); axis image; subplot(2, 2, 2); imagesc(kgrid.z_vec * 1e3, kgrid.x_vec * 1e3, squeeze(p0(:, Ny/2, :)), plot_scale); title('x-z plane'); axis image; xlabel('(All axes in mm)'); subplot(2, 2, 3); imagesc(kgrid.z_vec * 1e3, kgrid.y_vec * 1e3, squeeze(p0(Nx/2, :, :)), plot_scale); title('y-z plane'); axis image; colormap(getColorMap); % plot the reconstructed initial pressure figure; subplot(2, 2, 1); imagesc(kgrid.y_vec * 1e3, kgrid.x_vec * 1e3, squeeze(p0_recon(:, :, Nz/2)), plot_scale); title('x-y plane'); axis image; subplot(2, 2, 2); imagesc(kgrid.z_vec * 1e3, kgrid.x_vec * 1e3, squeeze(p0_recon(:, Ny/2, :)), plot_scale); title('x-z plane'); axis image; xlabel('(All axes in mm)'); subplot(2, 2, 3); imagesc(kgrid.z_vec * 1e3, kgrid.y_vec * 1e3, squeeze(p0_recon(Nx/2, :, :)), plot_scale); title('y-z plane'); axis image; colormap(getColorMap); Thanks in advance!