You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: doRiskEstimation.m
    path of file: ./repos/Image-Harmonization-Dataset-iHarmony4/Lalonde and Efros/colorStatistics/mycode
    
    the code of the file until where you have to start completion: function doRiskEstimationglobal cumulativeHistogram;
 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Copyright 2006-2007 Jean-Francois Lalonde
% Carnegie Mellon University
% Do not distribute
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    
function dbFnRisk(imgPath, imagesBasePath, outputBasePath, annotation, varargin)
global cumulativeHistogram;

% check if the user specified the option to recompute
defaultArgs = struct('Recompute', 0, 'nbBins', 10);
args = parseargs(defaultArgs, varargin{:});

% get the bins from the argument
nbBins = args.nbBins;

% read the image
img = imread(imgPath);

% make sure all the images have the same size
img = imresize(img, [256,256], 'bilinear');

% convert the image to the L*a*b* color space
labImg = rgb2lab(img);

% add small amount of random noise to the data
% what stdev should we use in each dimensions?
stdevL = 5;
stdevAB = 10;
noise = randn(size(labImg)) .* repmat(shiftdim([stdevL stdevAB stdevAB], -1), [size(labImg,1) size(labImg,2) 1]);
labImg = labImg + noise;
% imshow(reshape(lab2rgb(reshape(labImg, 256*256,3)), 256, 256, 3));

% minRange = [0 -100 -100];
% maxRange = [100 100 100];

% compute the histogram
% histogram = imageHisto3D(labImg, ones(size(labImg(:,:,1))), nbBins, minRange, maxRange);
% histogram = histc(reshape(labImg(:,:,1), 256*256, 1), 0:(100/nbBins):100);
% histogram(end