diff --git a/image_preprocess.m b/image_preprocess.m
index d9d762cfec9a31536ccd043483a4b316a7fbc289..42fe1a2650580a88f161f74469abb0c4c4ea0abe 100644
--- a/image_preprocess.m
+++ b/image_preprocess.m
@@ -70,6 +70,9 @@ function im_filt = image_preprocess(im, filters)
if isfield(filter, 'n'), n = filter.n; end
thresh = im_med + n*im_std;
im_filt = min(im_filt, thresh);
+ elseif strcmp(filter.type, 'null')
+ %% null filter, do nothing
+ im_filt = im_filt;
else
error('unrecognised filter type %s', filter.type);
end
diff --git a/job_create.m b/job_create.m
index 579a157fbe9244a38417ad50466ecfaa153d5060..199fccb6301079d25c2e263593be21954640e0a6 100644
--- a/job_create.m
+++ b/job_create.m
@@ -9,31 +9,35 @@ addpath(genpath(fileparts(mfilename('fullpath'))));
%% input parameters: file paths
% where to save jobs
-%job_idx = 1;
-job_dir = 'H:\davis\multiscale\Gen1_12\jobs\';
+job_idx = 1;
+job_dir = 'J:\FEE\EFMRL\John\TR-IM7\jobs\';
job_pat = '%s/job%03d.mat';
+% timeseries PIV flag
+% in timeseries PIV, correlations are conducted between subsequent images
+% in a timeseries
+b_timeseries = true;
% path of images to process
-%src_dir = 'H:\davis\multiscale\Gen1_12\U10\U10_x-axis=257.988_x-axis=257.987_x-axis=229.986\';
+src_dir = 'J:\FEE\EFMRL\John\TR-IM7';
src_pat = '%s/B%05d.im7'; % source image to process
-src_range = 1:1000; % range of source images to process
+src_range = 1:3; % range of source images to process
% background & mask
bg_dir = src_dir; % background image directory
bg_pat = '%s/minmax.mat'; % background image (ignore if not using)
msk_dir = [src_dir '/MASK/']; % mask image directory
-msk_pat = '%s/B0001.im7'; % pattern for mask image input (ignore if not using)
+msk_pat = '%s/B0002.im7'; % pattern for mask image input (ignore if not using)
% where to save result
-%vec_dir = [src_dir '/C12']; % directory to save vector fields to
+vec_dir = [src_dir '/C12']; % directory to save vector fields to
vec_pat = '%s/B%05d.mat'; % output vector field file pattern
%% input parameters: processing
% processing flags
-b_use_mask = true; % use mask file?
+b_use_mask = false; % use mask file?
b_overwrite = true; % overwrite existing vector fields?
-b_execute_now = false; % start processing now?
+b_execute_now = true; % start processing now?
% PIV correlation settings
-i_frames = {[1 2],[3 4]}; % indices of frame pairs to cross-correlate
+i_frames = {[1 1],[2 2], [3 3]}; % indices of frame pairs to cross-correlate
n_passes = 3; % number of passes
n_peaks = 3; % number of correlation peaks to detect
wsize = [64 64; 32 32; 32 32];% window size
@@ -52,27 +56,27 @@ min_filt_size = [17 17]; % sliding bg filter size
gauss_filt_size = [3 3]; % gaussian filter size
norm_filt_size = [17 17]; % normalisation filter size
-filters = {};
+filters = {struct('type', 'null')};
-% subtract background image: will require background image to be supplied
-filters{end+1} = struct('type', 'ssbg');
-% subtract sliding minimum
-%filters{end+1} = struct('type', 'ssmin', 'size', min_filt_size);
-% max-clip bright particles at threshold = median(im) + n*sigma(im)
-filters{end+1} = struct('type', 'clip', 'n', 2);
-% 2D Gaussian filter
-filters{end+1} = struct('type', 'gaussian', 'size', gauss_filt_size, 'sigma', 0.67);
-% min-max normalisation filter
-filters{end+1} = struct('type', 'norm', 'size', norm_filt_size, 'max_gain', 1/32);
+% % subtract background image: will require background image to be supplied
+% filters{end+1} = struct('type', 'ssbg');
+% % subtract sliding minimum
+% %filters{end+1} = struct('type', 'ssmin', 'size', min_filt_size);
+% % max-clip bright particles at threshold = median(im) + n*sigma(im)
+% filters{end+1} = struct('type', 'clip', 'n', 2);
+% % 2D Gaussian filter
+% filters{end+1} = struct('type', 'gaussian', 'size', gauss_filt_size, 'sigma', 0.67);
+% % min-max normalisation filter
+% filters{end+1} = struct('type', 'norm', 'size', norm_filt_size, 'max_gain', 1/32);
%% input parameters: plotting features
plt_opts = struct();
plt_opts.c_lim = [0 1]*256;
-plt_opts.font_size = 24; % figure font size
-plt_opts.b_plot_src = false; % plot source images?
-plt_opts.b_plot_u = false; % plot u component field?
-plt_opts.b_plot_v = false; % plot v component field?
-plt_opts.b_plot_cv = false; % plot correlation value?
+plt_opts.font_size = 24; % figure font size
+plt_opts.b_plot_src = true; % plot source images?
+plt_opts.b_plot_u = true; % plot u component field?
+plt_opts.b_plot_v = true; % plot v component field?
+plt_opts.b_plot_cv = true; % plot correlation value?
%% check job directory
job_completed_dir = [job_dir '/completed/'];
@@ -101,6 +105,11 @@ if exist(job_file, 'file')
error('will not overwrite job');
end
end
+% make output directory
+if ~exist(vec_dir, 'dir')
+ fprintf('making output directory ...\n');
+ mkdir(vec_dir);
+end
%% load sample and check all files in range exist
n_src = length(src_range);
@@ -187,6 +196,8 @@ job = struct();
job.job_idx = job_idx;
job.job_dir = job_dir;
job.job_pat = job_pat;
+% timeseries flag
+job.b_timeseries= b_timeseries;
% source images
job.src_dir = src_dir;
job.src_pat = src_pat;
diff --git a/job_execute.m b/job_execute.m
index 3c25f31b8f117011fa1be148e2e12fb694f364a9..6d1d3d6f2718fc7f27f2b19d6be11e812561b8af 100644
--- a/job_execute.m
+++ b/job_execute.m
@@ -8,6 +8,8 @@ function job_execute(job_file)
src_pat = job.src_pat;
src_range = job.src_range;
n_src = length(src_range);
+ % timeseries PIV flag
+ b_timeseries = job.b_timeseries;
% background image
b_use_bg = job.b_use_bg;
bg_dir = job.bg_dir;
@@ -89,8 +91,13 @@ function job_execute(job_file)
% read attributes
atts = readAttributes(imx);
- s = atts('Reference time dt 1');
- piv_dt = 1E-6 * s.value;
+ if isKey(atts, 'Reference time dt 1')
+ s = atts('Reference time dt 1');
+ piv_dt = 1E-6 * s.value;
+ else
+ warning('dt field is missing from IM7 file, dt = 1');
+ piv_dt = 1;
+ end
t_load = toc(t_samp);
%% preprocess images
@@ -109,17 +116,45 @@ function job_execute(job_file)
end
t_preproc = toc(t_preproc);
-
- %% PIV cross-correlation
+ %% create image pairs
+ im_pairs = cell(2, n_correl);
+ im_correl_mask = cell(1, n_correl);
+ if b_timeseries
+ %% time-series cross-correlation
+ % preload first image
+ if n == 1
+ im_filt_prev= im_filt;
+ continue;
+ end
+ % allocate images from timeseries to image pairs
+ for c = 1 : n_correl
+ iA = piv_opts(c).i_frames(1);
+ iB = piv_opts(c).i_frames(2);
+ im_pairs(1,c) = im_filt_prev(iA);
+ im_pairs(2,c) = im_filt(iB);
+ im_correl_mask{c} = im_mask_ary{iA} | im_mask_ary{iB};
+ end
+ % save current pair for next iteration
+ im_filt_prev = im_filt;
+ else
+ %% regular PIV
+ for c = 1 : n_correl
+ iA = piv_opts(c).i_frames(1);
+ iB = piv_opts(c).i_frames(2);
+ im_pairs(1,c) = im_filt(iA);
+ im_pairs(2,c) = im_filt(iB);
+ im_correl_mask{c} = im_mask_ary{iA} | im_mask_ary{iB};
+ end
+ end
+
+ %% cross-corrleate
piv_result = cell(1,n_correl);
t_proc = tic;
for c = 1 : n_correl
%% get images to cross-correlate
- iA = piv_opts(c).i_frames(1);
- iB = piv_opts(c).i_frames(2);
- im_A = im_filt{iA};
- im_B = im_filt{iB};
-
+ im_A = im_pairs{1,c};
+ im_B = im_pairs{2,c};
+
%% plot source, if requested
if plt_opts.b_plot_src
figure(10);
@@ -128,11 +163,11 @@ function job_execute(job_file)
axis equal tight ij;
drawnow;
end
-
+
%% cross-correlate
fprintf(' correlation %d of %d\n', c, n_correl);
piv_result{c} = PIV_2D_wdef(im_A, im_B, ...
- im_mask_ary{iA} | im_mask_ary{iB}, ...
+ im_correl_mask{c}, ...
piv_opts(c));
end
t_proc = toc(t_proc);
@@ -211,6 +246,11 @@ function job_execute(job_file)
ax(c) = gca;
imagesc(V.win_x, V.win_y, V.peak_mag')
axis equal tight ij;
+ hold on;
+ [xm,ym] = ndgrid(V.win_x, V.win_y);
+ ir = 1 : 4 : V.n_windows(1);
+ jr = 1 : 4 : V.n_windows(2);
+ quiversc(xm(ir,jr),ym(ir,jr),V.ux(ir,jr),V.uy(ir,jr),10,'k');
colormap(jet);
colorbar;
set(gca,'clim',[0 1]);