Variance map of an image is calculated by taking a square window of a set size around a center pixel, and calculating the variance of the values of the pixels.
The variance within the window can be calculated from the following equation:
Example
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MATLAB Code
% *************************************************************************
% Title: Function-Compute Variance map of the image
% Author: Siddhant Ahuja
% Created: May 2008
% Copyright Siddhant Ahuja, 2008
% Inputs: Input Image (var: inputImage), Window Size (var: windowSize),
% Threshold (var: thresh) Typical value is 140
% Outputs: Variance Map (var: varianceImg) , Time taken (var: timeTaken)
% Example Usage of Function: [varianceImg, timeTaken]=funcVarianceMap('MonopolyLeftColor.png', 5, 9);
% *************************************************************************
function [varianceImg, timeTaken]=funcVarianceMap(inputImage, windowSize, thresh)
try
% Grab the image information (metadata) of input image using the function imfinfo
inputImageInfo=imfinfo(inputImage);
if(getfield(inputImageInfo,'ColorType')=='truecolor')
% Read an image using imread function, convert from RGB color space to
% grayscale using rgb2gray function and assign it to variable inputImage
inputImage=rgb2gray(imread(inputImage));
% Convert the image from uint8 to double
inputImage=double(inputImage);
else if(getfield(inputImageInfo,'ColorType')=='grayscale')
% If the image is already in grayscale, then just read it.
inputImage=imread(inputImage);
% Convert the image from uint8 to double
inputImage=double(inputImage);
else
error('The Color Type of Left Image is not acceptable. Acceptable color types are truecolor or grayscale.');
end
end
catch
% if it is not an image but a variable
inputImage=inputImage;
end
% Find the size (columns and rows) of the input image and assign the rows to
% variable nr, and columns to variable nc
[nr,nc] = size(inputImage);
% Check the size of window to see if it is an odd number.
if (mod(windowSize,2)==0)
error('The window size must be an odd number.');
end
% Create an image of size nr and nc, fill it with zeros and assign
% it to variable meanImg
meanImg=zeros(nr, nc);
% Create an image of size nr and nc, fill it with zeros and assign
% it to variable varianceImg
varianceImg=zeros(nr, nc);
% Find out how many rows and columns are to the left/right/up/down of the
% central pixel based on the window size
win=(windowSize-1)/2;
tic; % Initialize the timer to calculate the time consumed.
% Compute a map of mean values
for(i=1+win:1:nr-win)
for(j=1+win:1:nc-win)
sum=0.0;
for(a=-win:1:win)
for(b=-win:1:win)
sum=sum+inputImage(i+a,j+b);
end
end
meanImg(i,j)=sum/(windowSize*windowSize);
end
end
% Compute a map of variance values
for(i=1+win:1:nr-win)
for(j=1+win:1:nc-win)
sum=0.0;
for(a=-win:1:win)
for(b=-win:1:win)
sum=sum+((inputImage(i+a,j+b)-meanImg(i,j))^2);
end
end
var=sum/((windowSize*windowSize)-1);
% Apply threshold to produce a binarized variance map
if (var > thresh)
varianceImg(i,j) = 255;
else
varianceImg(i,j) = 0;
end
end
end
% Stop the timer to calculate the time consumed.
timeTaken=toc;
