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author | Willem Jan Palenstijn <Willem.Jan.Palenstijn@cwi.nl> | 2018-07-17 16:54:13 +0200 |
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committer | Willem Jan Palenstijn <Willem.Jan.Palenstijn@cwi.nl> | 2018-07-17 16:54:13 +0200 |
commit | 4d741fc8e6c7930f7a8e27f54c55e0ad4949ed07 (patch) | |
tree | e78ac8d69f659b7c9c59e121f7dfb9cba8e5004f /samples/matlab | |
parent | 9bce55d46758bc79ef2504f68cda6e79c81f4cba (diff) | |
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Add sample scripts
Diffstat (limited to 'samples/matlab')
-rw-r--r-- | samples/matlab/s023_FBP_filters.m | 96 |
1 files changed, 96 insertions, 0 deletions
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); |