From 4d741fc8e6c7930f7a8e27f54c55e0ad4949ed07 Mon Sep 17 00:00:00 2001
From: Willem Jan Palenstijn <Willem.Jan.Palenstijn@cwi.nl>
Date: Tue, 17 Jul 2018 16:54:13 +0200
Subject: Add sample scripts

---
 samples/matlab/s023_FBP_filters.m | 96 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 96 insertions(+)
 create mode 100644 samples/matlab/s023_FBP_filters.m

(limited to 'samples/matlab')

diff --git a/samples/matlab/s023_FBP_filters.m b/samples/matlab/s023_FBP_filters.m
new file mode 100644
index 0000000..4abec7e
--- /dev/null
+++ b/samples/matlab/s023_FBP_filters.m
@@ -0,0 +1,96 @@
+% -----------------------------------------------------------------------
+% This file is part of the ASTRA Toolbox
+% 
+% Copyright: 2010-2018, imec Vision Lab, University of Antwerp
+%            2014-2018, CWI, Amsterdam
+% License: Open Source under GPLv3
+% Contact: astra@astra-toolbox.com
+% Website: http://www.astra-toolbox.com/
+% -----------------------------------------------------------------------
+
+
+% This sample script illustrates three ways of passing filters to FBP.
+% They work with both the FBP (CPU) and the FBP_CUDA (GPU) algorithms.
+
+N = 256;
+
+vol_geom = astra_create_vol_geom(N, N);
+proj_geom = astra_create_proj_geom('parallel', 1.0, N, linspace2(0,pi,180));
+
+proj_id = astra_create_projector('strip', proj_geom, vol_geom);
+
+P = phantom(256);
+
+[sinogram_id, sinogram] = astra_create_sino(P, proj_id);
+
+rec_id = astra_mex_data2d('create', '-vol', vol_geom);
+
+cfg = astra_struct('FBP');
+cfg.ReconstructionDataId = rec_id;
+cfg.ProjectionDataId = sinogram_id;
+cfg.ProjectorId = proj_id;
+
+
+% 1. Use a standard Ram-Lak filter
+cfg.FilterType = 'ram-lak';
+
+alg_id = astra_mex_algorithm('create', cfg);
+astra_mex_algorithm('run', alg_id);
+rec_RL = astra_mex_data2d('get', rec_id);
+astra_mex_algorithm('delete', alg_id);
+
+
+% 2. Define a filter in Fourier space
+% This is assumed to be symmetric, and ASTRA therefore expects only half
+
+% The full filter size should be the smallest power of two that is at least
+% twice the number of detector pixels.
+fullFilterSize = 2*N;
+kernel = [linspace2(0, 1, floor(fullFilterSize / 2)) linspace2(1, 0, ceil(fullFilterSize / 2))];
+halfFilterSize = floor(fullFilterSize / 2) + 1;
+filter = kernel(1:halfFilterSize);
+
+filter_geom = astra_create_proj_geom('parallel', 1.0, halfFilterSize, [0]);
+filter_id = astra_mex_data2d('create', '-sino', filter_geom, filter);
+
+cfg.FilterType = 'projection';
+cfg.FilterSinogramId = filter_id;
+
+alg_id = astra_mex_algorithm('create', cfg);
+astra_mex_algorithm('run', alg_id);
+rec_filter = astra_mex_data2d('get', rec_id);
+astra_mex_algorithm('delete', alg_id);
+
+% 3. Define a (spatial) convolution kernel directly
+% For a kernel of odd size 2*k+1, the central component is at kernel(k+1)
+% For a kernel of even size 2*k, the central component is at kernel(k+1)
+
+kernel = zeros(1, N);
+for i = 0:floor(N/4)-1
+  f = pi * (2*i + 1);
+  val = -2.0 / (f * f);
+  kernel(floor(N/2) + 1 + (2*i+1)) = val;
+  kernel(floor(N/2) + 1 - (2*i+1)) = val;
+end
+kernel(floor(N/2)+1) = 0.5;
+
+kernel_geom = astra_create_proj_geom('parallel', 1.0, N, [0]);
+kernel_id = astra_mex_data2d('create', '-sino', kernel_geom, kernel);
+
+cfg.FilterType = 'rprojection';
+cfg.FilterSinogramId = kernel_id;
+
+alg_id = astra_mex_algorithm('create', cfg);
+astra_mex_algorithm('run', alg_id);
+rec_kernel = astra_mex_data2d('get', rec_id);
+astra_mex_algorithm('delete', alg_id);
+
+figure(1); imshow(P, []);
+figure(2); imshow(rec_RL, []);
+figure(3); imshow(rec_filter, []);
+figure(4); imshow(rec_kernel, []);
+
+
+astra_mex_data2d('delete', rec_id);
+astra_mex_data2d('delete', sinogram_id);
+astra_mex_projector('delete', proj_id);
-- 
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