i need a codes for 'local enhancement using mean and standard deviation'…. urgent
MATLAB: Local enhancement using mean and standard deviation
local enhancement using mean and standard deviationurgent
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Do you mean like this:
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
clear; % Erase all existing variables. Or clearvars if you want.
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 15;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'originalimage.jpg';% Get the full filename, with path prepended.
folder = pwdfullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endend%===============================================================================% Read in demo image.
rgbImage = imread(fullFileName);% Get the dimensions of the image.
[imageRows, imageColumns, numberOfColorChannels] = size(rgbImage);% Display the original image.
subplot(3, 3, 1);imshow(rgbImage, []);axis on;caption = sprintf('Original Color Image, %s', baseFileName);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);% Get rid of tool bar and pulldown menus that are along top of figure.
set(gcf, 'Toolbar', 'none', 'Menu', 'none');% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Crop the image
rgbImage = rgbImage(29:391, 87:762, :);% Convert to HSV color space so we can segment the saturation channel.
hsvImage = rgb2hsv(rgbImage);sImage = hsvImage(:, :, 2);% Display the image.
subplot(3, 3, 2);imshow(sImage, []);axis on;caption = sprintf('Saturation Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Display the histogram
subplot(3, 3, 3);histogram(sImage);grid on;title('Histogram of Saturation Image', 'FontSize', fontSize);% Threshold the image
saturationThreshold = 0.15;mask = sImage > saturationThreshold;% Fill holes.
mask = imfill(mask, 'holes');% Extract the two largest blobs only.
mask = bwareafilt(mask, 2);% Put a red line at the threshold.
line([saturationThreshold, saturationThreshold], ylim, 'Color', 'r', 'LineWidth', 3);% Display the image.subplot(3, 3, 4);imshow(mask, []);axis on;caption = sprintf('Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Give each blob an ID number.
labeledImage = bwlabel(mask);% Get the top and bottom mask
topMask = ismember(labeledImage, 1);bottomMask = ismember(labeledImage, 2);% Display the image.subplot(3, 3, 5);imshow(topMask, []);axis on;caption = sprintf('Top Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Display the image.subplot(3, 3, 6);imshow(bottomMask, []);axis on;caption = sprintf('Bottom Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Mask the original RGB image and display.
% Mask the image using bsxfun() function
topMaskedRgbImage = bsxfun(@times, rgbImage, cast(topMask, 'like', rgbImage));bottomMaskedRgbImage = bsxfun(@times, rgbImage, cast(bottomMask, 'like', rgbImage));% Display the image.subplot(3, 3, 7);imshow(topMaskedRgbImage, []);axis on;caption = sprintf('Top Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Display the image.subplot(3, 3, 8);imshow(bottomMaskedRgbImage, []);axis on;caption = sprintf('Bottom Mask Image');title(caption, 'FontSize', fontSize, 'Interpreter', 'None');drawnow;
Again, I'm not sure what this means or if it is really what you want but I think it's what you described.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
imtool close all; % Close all imtool figures.
clear; % Erase all existing variables.
workspace; % Make sure the workspace panel is showing.
fontSize = 20;% Read in a standard MATLAB gray scale demo image.
folder = fullfile(matlabroot, '\toolbox\images\imdemos');baseFileName = 'cameraman.tif';fullFileName = fullfile(folder, baseFileName);% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);if ~exist(fullFileName, 'file') % Didn't find it there. Check the search path for it.
fullFileName = baseFileName; % No path this time.
if ~exist(fullFileName, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist.', fullFileName); uiwait(warndlg(errorMessage)); return; endendgrayImage = 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, 3, 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') % Calculate the standard deviation image.
sdImage = stdfilt(grayImage);% Display the image.
subplot(2, 3, 2);imshow(sdImage, []);title('Std. Dev. Image', 'FontSize', fontSize);% Calculate the variance image.
varianceImage = sdImage .^2;% Display the image.subplot(2, 3, 3);imshow(varianceImage, []);title('Variance Image', 'FontSize', fontSize);% Calculate the mean of the variance image in a 3x3 region.
% Basically this is a blurred version of it.
meanVarianceImage = conv2(varianceImage, ones(3)/9);% Display the image.subplot(2, 3, 4);imshow(meanVarianceImage, []);title('Mean Variance Image', 'FontSize', fontSize);for gl = 0:255 % Find pixels in the original image with this gray level.
matchingIndexes = (grayImage == gl); % Get the mean of only those pixels from the mean variance image.
W(gl+1) = mean(meanVarianceImage(matchingIndexes));end% Plot W
subplot(2, 3, 5);plot(W);grid on;title('Plot of W', 'FontSize', fontSize);xlabel('Gray Level', 'FontSize', fontSize);
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