MATLAB: Adaptive filter with mask 5*5 for an image with noise

digital image processingfilter designfrequencywallis filter

how can mplement this adaptive filter with mask 5*5 for an image with noise :

f(x,y) = g(x,y) – ( (ση)^2 / (σL)^2 ) * ( g(x,y)-mL ))

where :

g(x,y) : is the value of the pixel (x,y) in the noisy image

ση : is the variance of the noise corrupting f(x,y)

σL : is the local variance for the pixels in Sxy

mL: the local mean for the pixels in Sxy

Best Answer

This looks like the Wallis Filter. See http://www.dtic.mil/dtic/tr/fulltext/u2/a248301.pdf. It does a localized contrast stretch where is sets the mean and standard deviation of every window equal to some specified values. There is no built-in MATLAB function to do the Wallis filter. You should be able to do this using stdfilt() and conv2(). Give that a try and come back if you can't figure it out.

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See this snippet

% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
bar(grayLevels, pixelCount);
grid on;
title('Histogram of image', 'FontSize', 22);
xlim([0 255]); % or 65535 if image is uint16
% Compute and display mean
meanGrayLevel = mean2(grayImage);
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MATLAB: How to display the input image, after when the threshold values exceeds certain limit

It's just 3 lines. Just mask the original image:

binaryImage = grayImage > 150;
maskedImage = zeros(size(grayImage)); % Initialize.

maskedImage(binaryImage) = grayImage(binaryImage);

See the full demo below:

% Demo by ImageAnalyst
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
fontSize = 14;
% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');
baseFileName = 'coins.png';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
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    errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName);
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  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows columns numberOfColorBands] = size(grayImage);
% Display the original gray scale image.


subplot(2, 2, 1);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Give a name to the title bar.
set(gcf,'name','Demo by ImageAnalyst','numbertitle','off') 
% Let's compute and display the histogram.
[pixelCount grayLevels] = imhist(grayImage);
subplot(2, 2, 2); 
bar(pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
yl = ylim();
line([150 150], [0 yl(2)], 'Color', 'r');
% Threshold at 150
binaryImage = grayImage > 150;
% Display the original gray scale image.
subplot(2, 2, 3);
imshow(binaryImage, []);
title('Binary Image', 'FontSize', fontSize);
% Mask the image
maskedImage = zeros(size(grayImage)); % Initialize.
% Assign values from grayImage that are > 150.
maskedImage(binaryImage) = grayImage(binaryImage);
% Display the original gray scale image.
subplot(2, 2, 4);
imshow(maskedImage, []);
title('Masked Image', 'FontSize', fontSize);

Best Answer

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MATLAB: Compare the levels of gray

MATLAB: How to display the input image, after when the threshold values exceeds certain limit

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