function [filtIm] = bandpass2D(Image, largerPixel, smallerPixel)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%A basic implementation of a 2-D bandpass filter as a first pass for
%processing gi ca videos. Made from 2 butterworth filters
% Inputs:
%     - Image: The image to be filtered
%     - largerPixel: The upper limit of features to be filtered in pixels
%     - smallerPixel: the lower limit of the features to be filtered in
%     pixels
% Output:
%     - filtIm: the filtered image

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
norder = 2;
%% Find the next power of 2 from the dimensions of the original image. 
[nx ny] = size(Image);
np2nx = nextpow2(nx);
np2ny = nextpow2(ny);
sqdim = max([np2nx np2ny]);
% Set up the padding for the image so that the total dimensions of the
% figure are the next closest power of two to the original image
padx = floor((2^sqdim - nx)/2);
pady = floor((2^sqdim - ny)/2);


padImage = padarray(Image, [padx pady], 'symmetric');
[px py] = size(padImage);
%% Check that the dimensions are even:
% if not add an extra row/column of zeros and save for the conversion back
if iseven(px)
else
    padImage = cat(1, zeros(1, py), padImage);
    padx = padx +1;
end
[px py] = size(padImage);
if iseven(py)
else
    padImage = cat(2, zeros(px, 1), padImage);
    pady = pady+1;
end

% Perform the fft on the padded image
fftI = fft2(padImage);
fftI = fftshift(fftI); 

%% Generate bandpass filter parameters
% Calculate the frequency value for the pixels of the fft image
[f1,f2] = freqspace(size(fftI), 'meshgrid');
dist = sqrt(f1.^2 + f2.^2);

wU = (1/smallerPixel)*2;
wL = (1/largerPixel)*2;

% Generate the low pass and high pass Butterworth filters
filterLP = 1./(1 + (dist./wL).^(2*norder));
filterLP = 1-filterLP;
filterHP = 1./(1 + (dist./wU).^(2*norder));

%% Generate the bandpass filter and apply it
filterBP = filterLP.*filterHP;

% Filter and calculate the inverse fourier transform
filtIm = fftI.*filterBP;
filtIm = ifftshift(filtIm);
filtIm = ifft2(filtIm);
filtIm = real(filtIm)+mean(Image(:));

% undo the padding
filtIm = filtIm(padx+1:padx+nx, pady+1:pady+ny);

end