function [] = iterativeRegistering(vidname, NCparamStruct, regname)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Consecutive registrations with increasing grid number (2x2 -> 3x3 -> 6x6)
% Inputs:
%     - vidname: The name of the video. Assumes that the videos are h5
%     files
%     - NCparamStruct: A struct of the desired parameters for NormCorre
%     - regname: The desired name for the registered video
% Output: (none)
%     - 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%% load in the data
video = h5read(vidname, '/video');

[d1 d2 d3] = size(video);
templateim = mean(video(:, :, 1:50), 3);
M2 = video;

%% Calculate initial metrics
[cM2f(:, 1),mM2f,vM2f(1)] = motion_metrics(M2, 0);
% Check to see if the h5 file exists. If it doesn't create it. 
clear video
iteration = 0; 
vidcheck = dir(regname)
if isempty(vidcheck)
    h5create(regname, '/iteration', size(iteration));
    h5write(regname, '/iteration', iteration);
    h5create(regname, '/originalname', size(string(vidname)), 'Datatype', 'string');
    h5write(regname, '/originalname', string(vidname));
end

%% Go through the different stages of registration
maxmove = [0 0 0 0]; 
for fn = 1:size(NCparamStruct.gridsize, 1)
    if fn == 1
    else
        templateim = mean(M2(:, :, 1:50), 3);
    end
    completed = h5read(regname, '/iteration');
    if completed < fn
        % Check to see if the registration completed successfully because
        % sometimes it can fail in the upsampling factor is too high

        count = 0;
        display(num2str(count))
        err_count = 0;
        M2 = M2(maxmove(fn, 3)+1:end-maxmove(fn, 4), maxmove(fn, 1)+1:end-maxmove(fn, 2), :);
        templateim = templateim(maxmove(fn, 3)+1:end-maxmove(fn, 4), maxmove(fn, 1)+1:end-maxmove(fn, 2), :);
        [d1(fn+1) d2(fn+1) d3(fn+1)] = size(M2);

        options_nr = NoRMCorreSetParms('d1',d1(fn+1),'d2',d2(fn+1),'bin_width',50, ...
            'grid_size',NCparamStruct.gridsize(fn, :),'mot_uf',NCparamStruct.motuf(fn),'correct_bidir',false, ...
            'overlap_pre',NCparamStruct.overlap(fn),'overlap_post', NCparamStruct.overlap(fn),'max_shift',....
            NCparamStruct.maxshift(fn), 'upd_template', false, 'shifts_method', NCparamStruct.interp,...
            'max_dev', NCparamStruct.max_dev(fn));
        
        tic; [M2,shifts2{fn+1},template2] = normcorre_batch(M2,options_nr,templateim); toc
        itname = strcat('/video', num2str(fn));
        cshift = convertShifts(shifts2{fn+1});
        
        maxmove(fn+1, :) = ceil([abs(max([0 max(cshift.x(:))])) abs(min([0 min(cshift.x(:))])) abs(max([0 max(cshift.y(:))])) abs(min([0 min(cshift.y(:))]))]);

        infcheck = h5info(regname);
        if ~contains(strcat([infcheck.Datasets.Name]), itname(2:end))                
            h5create(regname, itname, size(M2), 'Datatype', 'uint8');
        end
        h5write(regname, itname, M2);
        iteration = fn;
        h5write(regname, '/iteration', iteration);

    end
   
end

%% Save the associated data into a .mat file for easier use
assocdat = strcat(regname(1:end-3), '_associated.mat');
h5create(regname, '/datname', size(string(assocdat)), 'Datatype', 'string');
h5write(regname, '/datname', string(assocdat));
save(assocdat, 'maxmove', 'd1', 'd2', 'shifts2', 'NCparamStruct');

end