message

functions/image cross correlation/GIVcore.m

@@ -95,6 +95,11 @@
 inputs.realresolution = ceil(inputs.idealresolution/mean_resolution)*8;
 %
 
+%Check if cell size is at least 32 (needs to be at least 8*4)
+if inputs.realresolution < 32
+    inputs.realresolution = 32;
+end
+
 %Initialize some parameters
 newcol1 = {}; %import to external (new) array in order to be parralelized
 newcol2 = {};

functions/image cross correlation/GIVtrackmultifinal.m

@@ -106,7 +106,7 @@
                 % or parabolic fit
                 [x0, y0]=GIVtrackmultipeak(max_x1,max_y1,R(max_y1,max_x1),...
                     R(max_y1,max_x1-1),R(max_y1,max_x1+1),...
-                    R(max_y1-1,max_x1),R(max_y1+1,max_x1),3,[M,winsize]);
+                    R(max_y1-1,max_x1),R(max_y1+1,max_x1),2,[M,winsize]);
 
 
                 % Find the signal to Noise ratio

functions/image cross correlation/GIVtrackmultifirst.m

@@ -87,6 +87,7 @@
             else
               [max_y1,max_x1]=find(R==max(max(R(0.5*winsize+2:1.5*winsize-3,0.5*M+2:1.5*M-3))));
             end
+
 
             if length(max_x1)>1
               max_x1=round(sum(max_x1.*(1:length(max_x1))')./sum(max_x1));

functions/image processing and filters/cropmask.m

@@ -93,12 +93,12 @@
     rightsizex = min(size_matrix(:,2));
 
     if size(mask_0_1,1) ~= rightsizey || size(mask_0_1,2) ~=rightsizex
-       mask_0_1 = interp2(mask_0_1, linspace(1, size(mask_0_1,2), rightsizex).', linspace(1, size(mask_0_1,1), rightsizey));
+       mask_0_1 = interp2(double(mask_0_1), linspace(1, size(mask_0_1,2), rightsizex).', linspace(1, size(mask_0_1,1), rightsizey));
     end
 
     for i = 2:size(images,1)
         if size(images{i,3},1) ~= rightsizey || size(images{i,3},2) ~=rightsizex 
-            images{i,3} = interp2(images{i,3}, (linspace(1, size(images{i,3},2), rightsizex).'), linspace(1, size(images{i,3},1), rightsizey));
+            images{i,3} = interp2(double(images{i,3}), (linspace(1, size(images{i,3},2), rightsizex).'), linspace(1, size(images{i,3},1), rightsizey));
         end
     end
 end

functions/post-processing/fd_outlier_filter.m

@@ -0,0 +1,48 @@
+function [out_limits_fd] = fd_outlier_filter(full_fd,mean_fd,std_fd,num_stand_dev)
+%Input = multi-array of flow directions
+%        mean flow direction
+%        stv of flow direction
+%Output = binary array with location of outliers
+%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%                    %% GLACIER IMAGE VELOCIMETRY (GIV) %%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% %Code written by Max Van Wyk de Vries @ University of Minnesota
+% %Credit to Ben Popken and Andrew Wickert for portions of the toolbox.
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% %Portions of this toolbox are based on a number of codes written by
+% %previous authors, including matPIV, IMGRAFT, PIVLAB, M_Map and more.
+% %Credit and thanks are due to the authors of these toolboxes, and for
+% %sharing their codes online. See the user manual for a full list of third
+% %party codes used here. Accordingly, you are free to share, edit and
+% %add to this GIV code. Please give us credit if you do, and share your code
+% %with the same conditions as this.
+%
+% % Read the associated paper here:
+% % doi.org/10.5194/tc-15-2115-2021
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%                         %Version 1.0, Spring-Summer 2021%
+% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%                   %Feel free to contact me at [email protected]%
+
+
+
+%Calculate the radial distance between each measurement and the mean flow
+%direction
+
+fd_dist = min(abs(full_fd-mean_fd),360-abs(full_fd-mean_fd));
+
+% Create stv outlier detection matrix
+
+fd_detection = (repmat(std_fd,size(full_fd,1),1)*num_stand_dev);
+
+
+%Identify regions where the radial distance is larger than XX times the stv
+
+out_limits_fd = double(fd_dist>fd_detection);
+
+%Remove any pixels with a stv*num_stand_dev larger than 180 (in this case,
+%there are no outliers
+
+out_limits_fd = out_limits_fd-double(fd_detection>=180);
+