gaussianFilter.m

function filtered = gaussianFilter(img, sigma, varargin)
% GAUSSIANFILTER Simplified open-source version of IMGAUSSFILT
%   The IMGAUSSFILT function is part of the Image Processing Toolbox,
%   but if you don't want to install that, then use this
%   instead. I haven't actually tested this to ensure it gives the same result.
%   Inspired by https://stackoverflow.com/questions/13193248/how-to-make-a-gaussian-filter-in-matlab
%
%   Hardcodes in the default arguments of IMGAUSSFILT
%   (per https://www.mathworks.com/help/images/ref/imgaussfilt.html)

  sigma = .5;
  % In our case this is 3
  filterSize = 2*ceil(2*sigma)+1;
  % In our case this is 1
  radius = (filterSize-1) / 2;
  
  % Pad the image so the edges are filtered properly
  padded = padarray(args.img, [radius radius], args.Padding, 'both')
  kernel = gaussianKernel(radius, args.sigma);
  filtered = conv2(padded, kernel, 'full')
  % Extract the center region to undo our padding
  [H, W] = size(img)
  filtered = filtered(radius+1:H-radius, radius+1:W-radius)
end

function kernel = gaussianKernel(radius, sigma)
  [x y] = meshgrid(-radius:radius, -radius:radius);
  kernel = exp(-x.^2/(2*sigma^2)-y.^2/(2*sigma^2));
  % Finally, normalize the kernel so that sum of weights is 1
  kernel = kernel./sum(kernel(:));
end