Latest Analysis scripts.
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@ -61,40 +61,6 @@ else
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od_imgs{i} = absimages(:, :, i);
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end
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end
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%% Display Images
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figure(1)
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clf
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set(gcf,'Position',[50 50 950 750])
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% Calculate the x and y limits for the cropped image
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y_min = center(1) - span(2) / 2;
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y_max = center(1) + span(2) / 2;
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x_min = center(2) - span(1) / 2;
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x_max = center(2) + span(1) / 2;
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% Generate x and y arrays representing the original coordinates for each pixel
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x_range = linspace(x_min, x_max, span(1));
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y_range = linspace(y_min, y_max, span(2));
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% Display the cropped image
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for k = 1 : length(od_imgs)
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imagesc(x_range, y_range, od_imgs{k})
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axis equal tight;
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hcb = colorbar;
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hL = ylabel(hcb, 'Optical Density', 'FontSize', 16);
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set(hL,'Rotation',-90);
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colormap jet;
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set(gca,'CLim',[0 3.0]);
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set(gca,'YDir','normal')
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set(gca, 'YTick', linspace(y_min, y_max, 5)); % Define y ticks
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set(gca, 'YTickLabel', flip(linspace(y_min, y_max, 5))); % Flip only the labels
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xlabel('Horizontal', 'Interpreter', 'tex','FontSize',16);
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ylabel('Vertical', 'Interpreter', 'tex','FontSize',16);
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drawnow
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pause(0.5)
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end
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%% Get rotation angles
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theta_values = zeros(1, length(files));
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@ -116,7 +82,8 @@ end
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fft_imgs = cell(1, nimgs);
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% Create VideoWriter object for movie
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videoFile = VideoWriter('Single_Shot_FFT.avi', 'Motion JPEG AVI');
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videoFile = VideoWriter('Single_Shot_FFT.mp4', 'MPEG-4');
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videoFile.Quality = 100; % Set quality to maximum (0–100)
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videoFile.FrameRate = 2; % Set the frame rate (frames per second)
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open(videoFile); % Open the video file to write
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@ -127,10 +94,10 @@ for k = 1 : length(od_imgs)
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figure(2);
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clf
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set(gcf,'Position',[50 50 1500 550])
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set(gca,'FontSize',16,'Box','On','Linewidth',2);
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t = tiledlayout(1, 3, 'TileSpacing', 'compact', 'Padding', 'compact'); % 1x2 grid
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set(gcf,'Position',[500 100 1000 800])
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t = tiledlayout(2, 2, 'TileSpacing', 'compact', 'Padding', 'compact'); % 1x4 grid
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font = 'Bahnschrift';
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% Calculate the x and y limits for the cropped image
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y_min = center(1) - span(2) / 2;
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y_max = center(1) + span(2) / 2;
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@ -142,57 +109,100 @@ for k = 1 : length(od_imgs)
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y_range = linspace(y_min, y_max, span(2));
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% Display the cropped image
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nexttile
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ax1 = nexttile;
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imagesc(x_range, y_range, IMG)
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% Define normalized positions (relative to axis limits)
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x_offset = 0.025; % 5% offset from the edges
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y_offset = 0.025; % 5% offset from the edges
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% Top-right corner (normalized axis coordinates)
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text(1 - x_offset, 1 - y_offset, ['Angle: ', num2str(theta_values(k), '%.1f')], ...
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hText = text(1 - x_offset, 1 - y_offset, ['Angle: ', num2str(theta_values(k), '%.1f')], ...
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'Color', 'white', 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontSize', 20, 'Units', 'normalized', 'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
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axis equal tight;
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hcb = colorbar;
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hL = ylabel(hcb, 'Optical Density', 'FontSize', 16);
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colormap(ax1, 'jet');
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set(gca, 'FontSize', 14); % For tick labels only
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hL = ylabel(hcb, 'Optical Density');
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set(hL,'Rotation',-90);
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set(gca,'YDir','normal')
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set(gca, 'YTick', linspace(y_min, y_max, 5)); % Define y ticks
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set(gca, 'YTickLabel', flip(linspace(y_min, y_max, 5))); % Flip only the labels
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xlabel('X', 'Interpreter', 'tex','FontSize',16);
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ylabel('Y', 'Interpreter', 'tex','FontSize',16);
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hXLabel = xlabel('X (pixels)', 'Interpreter', 'tex');
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hYLabel = ylabel('Y (pixels)', 'Interpreter', 'tex');
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hTitle = title('OD Image', 'Interpreter', 'tex');
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set([hXLabel, hYLabel, hL, hText], 'FontName', font)
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set([hXLabel, hYLabel, hL], 'FontSize', 14)
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set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title
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nexttile
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ax2 = nexttile;
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imagesc(x_range, y_range, IMGBIN)
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axis equal tight;
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hcb = colorbar;
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colormap(ax2, 'parula');
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set(gca, 'FontSize', 14); % For tick labels only
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set(gca,'YDir','normal')
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set(gca, 'YTick', linspace(y_min, y_max, 5)); % Define y ticks
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set(gca, 'YTickLabel', flip(linspace(y_min, y_max, 5))); % Flip only the labels
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xlabel('X', 'Interpreter', 'tex','FontSize',16);
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ylabel('Y', 'Interpreter', 'tex','FontSize',16);
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title('Denoised - Masked - Binarized','FontSize',16);
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hXLabel = xlabel('X (pixels)', 'Interpreter', 'tex');
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hYLabel = ylabel('Y (pixels)', 'Interpreter', 'tex');
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hTitle = title('Denoised - Masked - Binarized', 'Interpreter', 'tex');
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nexttile
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set([hXLabel, hYLabel, hL], 'FontName', font)
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set([hXLabel, hYLabel, hL], 'FontSize', 14)
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set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title
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ax3 = nexttile;
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[rows, cols] = size(IMGFFT);
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zoom_size = 50; % Zoomed-in region around center
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mid_x = floor(cols/2);
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mid_y = floor(rows/2);
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zoom_size = 50; % Zoomed-in region around center
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mid_x = floor(cols/2);
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mid_y = floor(rows/2);
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zoomedIMGFFT = IMGFFT(mid_y-zoom_size:mid_y+zoom_size, mid_x-zoom_size:mid_x+zoom_size);
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fft_imgs{k} = zoomedIMGFFT;
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fft_imgs{k} = zoomedIMGFFT;
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imagesc(log(1 + zoomedIMGFFT));
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% Define normalized positions (relative to axis limits)
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x_offset = 0.025; % 5% offset from the edges
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y_offset = 0.025; % 5% offset from the edges
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% Top-right corner (normalized axis coordinates)
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text(1 - x_offset, 1 - y_offset, ['Angle: ', num2str(theta_values(k), '%.1f')], ...
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'Color', 'white', 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontSize', 20, 'Units', 'normalized', 'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
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% hText = text(1 - x_offset, 1 - y_offset, ['Angle: ', num2str(theta_values(k), '%.1f')], ...
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% 'Color', 'white', 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontSize', 20, 'Units', 'normalized', 'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
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axis equal tight;
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hcb = colorbar;
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colormap(ax3, 'jet');
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set(gca, 'FontSize', 14); % For tick labels only
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set(gca,'YDir','normal')
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xlabel('X', 'Interpreter', 'tex','FontSize',16);
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ylabel('Y', 'Interpreter', 'tex','FontSize',16);
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title('Fourier Power Spectrum','FontSize',16);
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hXLabel = xlabel('X (pixels)', 'Interpreter', 'tex');
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hYLabel = ylabel('Y (pixels)', 'Interpreter', 'tex');
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hTitle = title('Fourier Power Spectrum', 'Interpreter', 'tex');
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set([hXLabel, hYLabel, hL, hText], 'FontName', font)
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set([hXLabel, hYLabel, hL], 'FontSize', 14)
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set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title
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% Plot the angular structure factor
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%{
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nexttile
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[theta_vals, angular_intensity] = computeAngularDistribution(zoomedIMGFFT, 10, 20, 100, 75);
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polarhistogram('BinEdges', theta_vals, 'BinCounts', angular_intensity, ...
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'FaceColor', [0.2 0.6 0.9], 'EdgeColor', 'k');
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set(gca, 'FontSize', 14); % For tick labels only
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hTitle = title('Angular Distribution', 'Interpreter', 'tex');
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set(hTitle, 'FontName', font)
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set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title
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%}
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% Plot the angular structure factor
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nexttile
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[theta_vals, S_theta] = computeAngularStructureFactor(zoomedIMGFFT, 10, 20, 180, 75, 2);
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plot(theta_vals/pi, S_theta,'Linewidth',2);
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set(gca, 'FontSize', 14); % For tick labels only
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hXLabel = xlabel('\theta (\pi)', 'Interpreter', 'tex');
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hYLabel = ylabel('S(\theta)', 'Interpreter', 'tex');
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hTitle = title('Angular Structure Factor', 'Interpreter', 'tex');
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set([hXLabel, hYLabel, hL, hText], 'FontName', font)
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set([hXLabel, hYLabel, hL], 'FontSize', 14)
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set(hTitle, 'FontName', font, 'FontSize', 16, 'FontWeight', 'bold'); % Set font and size for title
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grid on
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drawnow
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pause(0.5)
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@ -204,61 +214,6 @@ end
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% Close the video file
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close(videoFile);
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%% Averaged FFT
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% Assuming od_imgs is a cell array of size 4*n
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n = length(fft_imgs) / 4; % Calculate n
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fft_imgs_avg = cell(1, n); % Initialize the new cell array to hold the averaged images
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for i = 1:n
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% Take the 4 corresponding images from od_imgs
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img1 = fft_imgs{4*i-3}; % 1st image in the group
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img2 = fft_imgs{4*i-2}; % 2nd image in the group
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img3 = fft_imgs{4*i-1}; % 3rd image in the group
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img4 = fft_imgs{4*i}; % 4th image in the group
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% Compute the average of these 4 images
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avg_img = (img1 + img2 + img3 + img4) / 4;
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% Store the averaged image in the new cell array
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fft_imgs_avg{i} = avg_img;
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end
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% Create VideoWriter object for movie
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videoFile = VideoWriter('Averaged_FFT.avi', 'Motion JPEG AVI');
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videoFile.FrameRate = 2; % Set the frame rate (frames per second)
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open(videoFile); % Open the video file to write
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figure(3)
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clf
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set(gcf,'Position',[50 50 950 750])
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% Display the cropped image
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for k = 1 : length(fft_imgs_avg)
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imagesc(log(1 + fft_imgs_avg{k}));
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% Define normalized positions (relative to axis limits)
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x_offset = 0.025; % 5% offset from the edges
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y_offset = 0.025; % 5% offset from the edges
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% Top-right corner (normalized axis coordinates)
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text(1 - x_offset, 1 - y_offset, ['Angle: ', num2str(theta_values(k), '%.1f')], ...
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'Color', 'white', 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontSize', 20, 'Units', 'normalized', 'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
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axis equal tight;
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hcb = colorbar;
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set(gca,'YDir','normal')
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xlabel('X', 'Interpreter', 'tex','FontSize',16);
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ylabel('Y', 'Interpreter', 'tex','FontSize',16);
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title('Averaged Fourier Power Spectrum','FontSize',16);
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drawnow
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pause(0.5)
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% Capture the current frame and write it to the video
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frame = getframe(gcf); % Capture the current figure as a frame
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writeVideo(videoFile, frame); % Write the frame to the video
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end
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% Close the video file
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close(videoFile);
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%% Helper Functions
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function [IMGFFT, IMGBIN] = computeFourierTransform(I)
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% computeFourierSpectrum - Computes the 2D Fourier power spectrum
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@ -271,65 +226,121 @@ function [IMGFFT, IMGBIN] = computeFourierTransform(I)
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% F_mag - 2D Fourier power spectrum (shifted)
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% Preprocessing: Denoise
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I_filt = imgaussfilt(I, 1); % adjust sigma as needed
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filtered = imgaussfilt(I, 10);
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I_filt = I - filtered; % adjust sigma as needed
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% Elliptical mask parameters
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[rows, cols] = size(I_filt);
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[X, Y] = meshgrid(1:cols, 1:rows);
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cx = cols / 2;
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cy = rows / 2;
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[rows, cols] = size(I_filt);
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[X, Y] = meshgrid(1:cols, 1:rows);
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cx = cols / 2;
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cy = rows / 2;
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% Shifted coordinates
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x = X - cx;
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y = Y - cy;
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x = X - cx;
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y = Y - cy;
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% Ellipse semi-axes
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rx = 0.4 * cols;
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ry = 0.2 * rows;
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rx = 0.4 * cols;
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ry = 0.2 * rows;
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% Rotation angle in degrees -> radians
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theta_deg = 30; % Adjust as needed
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theta = deg2rad(theta_deg);
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theta_deg = 30; % Adjust as needed
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theta = deg2rad(theta_deg);
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% Rotated ellipse equation
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cos_t = cos(theta);
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sin_t = sin(theta);
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cos_t = cos(theta);
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sin_t = sin(theta);
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x_rot = (x * cos_t + y * sin_t);
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y_rot = (-x * sin_t + y * cos_t);
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x_rot = (x * cos_t + y * sin_t);
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y_rot = (-x * sin_t + y * cos_t);
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ellipseMask = (x_rot.^2) / rx^2 + (y_rot.^2) / ry^2 <= 1;
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ellipseMask = (x_rot.^2) / rx^2 + (y_rot.^2) / ry^2 <= 1;
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% Apply cutout mask
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I_masked = I_filt .* ellipseMask;
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I_masked = I_filt .* ellipseMask;
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% Apply global intensity threshold mask
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intensity_thresh = 0.8;
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intensity_thresh = 0.20;
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intensity_mask = I_masked > intensity_thresh;
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I_masked = I_masked .* intensity_mask;
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% Adaptive binarization
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IMGBIN = imbinarize(I_masked, 'adaptive', 'Sensitivity', 0.0);
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% Adaptive binarization and cleanup
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IMGBIN = imbinarize(I_masked, 'adaptive', 'Sensitivity', 0.0);
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IMGBIN = imdilate(IMGBIN, strel('disk', 2));
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IMGBIN = imerode(IMGBIN, strel('disk', 1));
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IMGBIN = imfill(IMGBIN, 'holes');
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% Compute 2D Fourier Transform
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F = fft2(double(I));
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IMGFFT = abs(fftshift(F))'; % Shift zero frequency to center
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F = fft2(double(I));
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IMGFFT = abs(fftshift(F))'; % Shift zero frequency to center
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% Define the radius for the circular region to exclude
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region_radius = 4; % Adjust the radius as needed
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% Create a circular mask
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[~, center_idx] = max(IMGFFT(:));
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[~, center_idx] = max(IMGFFT(:));
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[cx, cy] = ind2sub(size(IMGFFT), center_idx);
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% Equation for a circle (centered at cx, cy)
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center_region = (X - cx).^2 + (Y - cy).^2 <= region_radius^2;
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% Define a scaling factor for the central region (e.g., reduce amplitude by 90%)
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scaling_factor = 0.1; % Scale center region by 10%
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scaling_factor = 0.1; % Scale center region by 10%
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% Apply the scaling factor to the center region
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IMGFFT(center_region) = IMGFFT(center_region) * scaling_factor;
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IMGFFT(center_region) = IMGFFT(center_region) * scaling_factor;
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end
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function [theta_vals, S_theta] = computeAngularStructureFactor(IMGFFT, r_min, r_max, num_bins, threshold, sigma)
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% Apply threshold to isolate strong peaks
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IMGFFT(IMGFFT < threshold) = 0;
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% Prepare polar coordinates
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[ny, nx] = size(IMGFFT);
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[X, Y] = meshgrid(1:nx, 1:ny);
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cx = ceil(nx/2);
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cy = ceil(ny/2);
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R = sqrt((X - cx).^2 + (Y - cy).^2);
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Theta = atan2(Y - cy, X - cx); % range [-pi, pi]
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% Choose radial band
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radial_mask = (R >= r_min) & (R <= r_max);
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% Initialize the angular structure factor array
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S_theta = zeros(1, num_bins); % Pre-allocate for 180 angle bins
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% Define the angle values for the x-axis
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theta_vals = linspace(0, pi, num_bins);
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% Loop through each angle bin
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for i = 1:180
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angle_start = (i-1) * pi / num_bins;
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angle_end = i * pi / num_bins;
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% Define a mask for the given angle range
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angle_mask = (Theta >= angle_start & Theta < angle_end);
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bin_mask = radial_mask & angle_mask;
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% Extract the Fourier components for the given angle
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fft_angle = IMGFFT .* bin_mask;
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% Integrate the Fourier components over the radius at the angle
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S_theta(i) = sum(sum(abs(fft_angle).^2)); % Compute structure factor (sum of squared magnitudes)
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end
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% Create a 1D Gaussian kernel
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half_width = ceil(3 * sigma);
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x = -half_width:half_width;
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gauss_kernel = exp(-x.^2 / (2 * sigma^2));
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gauss_kernel = gauss_kernel / sum(gauss_kernel); % normalize
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% Apply convolution (circular padding to preserve periodicity)
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S_theta = conv([S_theta(end-half_width+1:end), S_theta, S_theta(1:half_width)], gauss_kernel, 'same');
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S_theta = S_theta(half_width+1:end-half_width); % crop back to original size
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% Normalize to maximum value of 1
|
||||
S_theta = S_theta / max(S_theta);
|
||||
|
||||
end
|
||||
|
||||
@ -475,3 +486,147 @@ function [optrefimages] = removefringesInImage(absimages, refimages, bgmask)
|
||||
optrefimages(:,:,j)=reshape(R*c,[ydim xdim]);
|
||||
end
|
||||
end
|
||||
|
||||
% Deprecated
|
||||
%% Display Images
|
||||
%{
|
||||
figure(1)
|
||||
clf
|
||||
set(gcf,'Position',[50 50 950 750])
|
||||
|
||||
% Calculate the x and y limits for the cropped image
|
||||
y_min = center(1) - span(2) / 2;
|
||||
y_max = center(1) + span(2) / 2;
|
||||
x_min = center(2) - span(1) / 2;
|
||||
x_max = center(2) + span(1) / 2;
|
||||
|
||||
% Generate x and y arrays representing the original coordinates for each pixel
|
||||
x_range = linspace(x_min, x_max, span(1));
|
||||
y_range = linspace(y_min, y_max, span(2));
|
||||
|
||||
% Display the cropped image
|
||||
for k = 1 : length(od_imgs)
|
||||
imagesc(x_range, y_range, od_imgs{k})
|
||||
axis equal tight;
|
||||
hcb = colorbar;
|
||||
hL = ylabel(hcb, 'Optical Density');
|
||||
set(hL,'Rotation',-90);
|
||||
colormap jet;
|
||||
set(gca,'CLim',[0 3.0]);
|
||||
set(gca,'YDir','normal')
|
||||
set(gca, 'YTick', linspace(y_min, y_max, 5)); % Define y ticks
|
||||
set(gca, 'YTickLabel', flip(linspace(y_min, y_max, 5))); % Flip only the labels
|
||||
xlabel('X', 'Interpreter', 'tex');
|
||||
ylabel('Y', 'Interpreter', 'tex');
|
||||
|
||||
drawnow
|
||||
pause(0.5)
|
||||
end
|
||||
|
||||
%}
|
||||
%% Averaged FFT
|
||||
%{
|
||||
|
||||
% Assuming od_imgs is a cell array of size 4*n
|
||||
n = length(fft_imgs) / 4; % Calculate n
|
||||
fft_imgs_avg = cell(1, n); % Initialize the new cell array to hold the averaged images
|
||||
|
||||
for i = 1:n
|
||||
% Take the 4 corresponding images from od_imgs
|
||||
img1 = fft_imgs{4*i-3}; % 1st image in the group
|
||||
img2 = fft_imgs{4*i-2}; % 2nd image in the group
|
||||
img3 = fft_imgs{4*i-1}; % 3rd image in the group
|
||||
img4 = fft_imgs{4*i}; % 4th image in the group
|
||||
|
||||
% Compute the average of these 4 images
|
||||
avg_img = (img1 + img2 + img3 + img4) / 4;
|
||||
|
||||
% Store the averaged image in the new cell array
|
||||
fft_imgs_avg{i} = avg_img;
|
||||
end
|
||||
|
||||
% Create VideoWriter object for movie
|
||||
videoFile = VideoWriter('Averaged_FFT.mp4', 'MPEG-4');
|
||||
videoFile.Quality = 100; % Set quality to maximum (0–100)
|
||||
videoFile.FrameRate = 2; % Set the frame rate (frames per second)
|
||||
open(videoFile); % Open the video file to write
|
||||
|
||||
% Display the cropped image
|
||||
for k = 1 : length(fft_imgs_avg)
|
||||
figure(3)
|
||||
clf
|
||||
set(gcf,'Position',[50 50 1500 550])
|
||||
set(gca,'FontSize',16,'Box','On','Linewidth',2);
|
||||
t = tiledlayout(1, 2, 'TileSpacing', 'compact', 'Padding', 'compact'); % 1x2 grid
|
||||
|
||||
nexttile
|
||||
imagesc(log(1 + fft_imgs_avg{k}));
|
||||
% Define normalized positions (relative to axis limits)
|
||||
x_offset = 0.025; % 5% offset from the edges
|
||||
y_offset = 0.025; % 5% offset from the edges
|
||||
% Top-right corner (normalized axis coordinates)
|
||||
text(1 - x_offset, 1 - y_offset, ['Angle: ', num2str(theta_values(k), '%.1f')], ...
|
||||
'Color', 'white', 'FontWeight', 'bold', 'Interpreter', 'tex', 'FontSize', 20, 'Units', 'normalized', 'HorizontalAlignment', 'right', 'VerticalAlignment', 'top');
|
||||
axis equal tight;
|
||||
hcb = colorbar;
|
||||
set(gca,'YDir','normal')
|
||||
xlabel('X', 'Interpreter', 'tex','FontSize',16);
|
||||
ylabel('Y', 'Interpreter', 'tex','FontSize',16);
|
||||
title('Averaged Fourier Power Spectrum','FontSize',16);
|
||||
|
||||
|
||||
% Plot the angular structure factor
|
||||
nexttile
|
||||
[theta_vals, angular_intensity] = computeAngularDistribution(fft_imgs_avg{k}, 10, 20, 100, 75);
|
||||
polarhistogram('BinEdges', theta_vals, 'BinCounts', angular_intensity, ...
|
||||
'FaceColor', [0.2 0.6 0.9], 'EdgeColor', 'k');
|
||||
title('Angular Distribution');
|
||||
|
||||
drawnow
|
||||
pause(0.5)
|
||||
|
||||
% Capture the current frame and write it to the video
|
||||
frame = getframe(gcf); % Capture the current figure as a frame
|
||||
writeVideo(videoFile, frame); % Write the frame to the video
|
||||
end
|
||||
|
||||
% Close the video file
|
||||
close(videoFile);
|
||||
|
||||
%}
|
||||
%% Angular Distribution
|
||||
%{
|
||||
|
||||
function [theta_vals, angular_intensity] = computeAngularDistribution(IMGFFT, r_min, r_max, num_bins, threshold)
|
||||
|
||||
% Apply threshold to isolate strong peaks
|
||||
IMGFFT(IMGFFT < threshold) = 0;
|
||||
|
||||
% Prepare polar coordinates
|
||||
[ny, nx] = size(IMGFFT);
|
||||
[X, Y] = meshgrid(1:nx, 1:ny);
|
||||
cx = ceil(nx/2);
|
||||
cy = ceil(ny/2);
|
||||
R = sqrt((X - cx).^2 + (Y - cy).^2);
|
||||
Theta = atan2(Y - cy, X - cx); % range [-pi, pi]
|
||||
|
||||
% Choose radial band
|
||||
mask = (R >= r_min) & (R <= r_max);
|
||||
|
||||
% Bin intensities by angle
|
||||
theta_vals = linspace(-pi, pi, num_bins+1);
|
||||
angular_intensity = zeros(1, num_bins);
|
||||
|
||||
for i = 1:num_bins
|
||||
t0 = theta_vals(i);
|
||||
t1 = theta_vals(i+1);
|
||||
bin_mask = mask & (Theta >= t0) & (Theta < t1);
|
||||
tmp = mean(IMGFFT(bin_mask), 'all');
|
||||
if tmp > 50
|
||||
angular_intensity(i) = tmp;
|
||||
else
|
||||
angular_intensity(i) = 0;
|
||||
end
|
||||
end
|
||||
end
|
||||
%}
|
||||
@ -2,24 +2,26 @@
|
||||
|
||||
groupList = ["/images/MOT_3D_Camera/in_situ_absorption", "/images/ODT_1_Axis_Camera/in_situ_absorption", "/images/ODT_2_Axis_Camera/in_situ_absorption", "/images/Horizontal_Axis_Camera/in_situ_absorption", "/images/Vertical_Axis_Camera/in_situ_absorption"];
|
||||
|
||||
%{
|
||||
|
||||
|
||||
folderPath = "C:/Users/Karthik/Documents/GitRepositories/Calculations/Data-Analyzer/";
|
||||
|
||||
run = '0140';
|
||||
run = '0013';
|
||||
|
||||
cam = 4;
|
||||
folderPath = strcat(folderPath, run);
|
||||
|
||||
cam = 5;
|
||||
|
||||
angle = 0;
|
||||
center = [95, 1042];
|
||||
span = [50, 50];
|
||||
center = [1285, 2105];
|
||||
span = [200, 200];
|
||||
fraction = [0.1, 0.1];
|
||||
|
||||
pixel_size = 5.86e-6;
|
||||
removeFringes = false;
|
||||
|
||||
%}
|
||||
|
||||
%{
|
||||
folderPath = "C:/Users/Karthik/Documents/GitRepositories/Calculations/Imaging-Response-Function-Extractor/";
|
||||
|
||||
run = '0096';
|
||||
@ -35,14 +37,15 @@ fraction = [0.1, 0.1];
|
||||
|
||||
pixel_size = 5.86e-6;
|
||||
removeFringes = false;
|
||||
%}
|
||||
|
||||
% Compute OD image, rotate and extract ROI for analysis
|
||||
%% Compute OD image, rotate and extract ROI for analysis
|
||||
% Get a list of all files in the folder with the desired file name pattern.
|
||||
|
||||
filePattern = fullfile(folderPath, '*.h5');
|
||||
files = dir(filePattern);
|
||||
refimages = zeros(span(1) + 1, span(2) + 1, length(files));
|
||||
absimages = zeros(span(1) + 1, span(2) + 1, length(files));
|
||||
|
||||
refimages = zeros(span(1) + 1, span(2) + 1, length(files));
|
||||
absimages = zeros(span(1) + 1, span(2) + 1, length(files));
|
||||
|
||||
for k = 1 : length(files)
|
||||
baseFileName = files(k).name;
|
||||
@ -60,24 +63,24 @@ for k = 1 : length(files)
|
||||
end
|
||||
|
||||
% Fringe removal
|
||||
|
||||
if removeFringes
|
||||
optrefimages = removefringesInImage(absimages, refimages);
|
||||
absimages_fringe_removed = absimages(:, :, :) - optrefimages(:, :, :);
|
||||
|
||||
nimgs = size(absimages_fringe_removed,3);
|
||||
od_imgs = cell(1, nimgs);
|
||||
nimgs = size(absimages_fringe_removed,3);
|
||||
od_imgs = cell(1, nimgs);
|
||||
for i = 1:nimgs
|
||||
od_imgs{i} = absimages_fringe_removed(:, :, i);
|
||||
od_imgs{i} = absimages_fringe_removed(:, :, i);
|
||||
end
|
||||
else
|
||||
nimgs = size(absimages,3);
|
||||
od_imgs = cell(1, nimgs);
|
||||
nimgs = size(absimages(:, :, :),3);
|
||||
od_imgs = cell(1, nimgs);
|
||||
for i = 1:nimgs
|
||||
od_imgs{i} = absimages(:, :, i);
|
||||
od_imgs{i} = absimages(:, :, i);
|
||||
end
|
||||
end
|
||||
|
||||
%%
|
||||
%% Display Images
|
||||
|
||||
figure(1)
|
||||
clf
|
||||
@ -98,10 +101,10 @@ for k = 1 : length(od_imgs)
|
||||
imagesc(x_range, y_range, od_imgs{k})
|
||||
axis equal tight;
|
||||
hcb = colorbar;
|
||||
hL = ylabel(hcb, 'Normalised Optical Density', 'FontSize', 16);
|
||||
hL = ylabel(hcb, 'Optical Density', 'FontSize', 16);
|
||||
set(hL,'Rotation',-90);
|
||||
colormap jet;
|
||||
set(gca,'CLim',[0 1.0]);
|
||||
set(gca,'CLim',[0 3.0]);
|
||||
set(gca,'YDir','normal')
|
||||
set(gca, 'YTick', linspace(y_min, y_max, 5)); % Define y ticks
|
||||
set(gca, 'YTickLabel', flip(linspace(y_min, y_max, 5))); % Flip only the labels
|
||||
@ -112,6 +115,7 @@ for k = 1 : length(od_imgs)
|
||||
pause(0.5)
|
||||
end
|
||||
|
||||
|
||||
%% Overlay images
|
||||
|
||||
% image_below = ;
|
||||
|
||||
Loading…
Reference in New Issue
Block a user