MATLAB: Creation of a mask on RGB image

image processingmaskrgb image

Hello,

I have applied a mask with irregular contours to a RGB image and then changed the saturation only in the area of the mask.

Imm = imread('lena .bmp');
imshow(Imm);
title('Original Image');
message = sprintf('After you see the cross hairs, \nleft-click and hold to begin drawing.\nSimply lift the mouse button to finish');
uiwait(msgbox(message));
hFH = drawfreehand();
% Create a binary image ("mask") from the ROI object.
binaryImage = hFH.createMask();
% Display the freehand mask
figure
imshow(binaryImage)
title('Binary mask of the region');
%Get HSV image from the RGB image
hsvImage = rgb2hsv(Imm);
hueImage = hsvImage(:, :, 1);
saturationImage = hsvImage(:, :, 2);
valueImage = hsvImage(:, :, 3);
% Increase saturation only within the mask area.
satFactor = 1.6; 
saturationImage(binaryImage) = saturationImage(binaryImage) * satFactor;
% Recombine
hsvImage = cat(3, hueImage, saturationImage, valueImage);
% Convert back to RGB 
rgbImage2 = hsv2rgb(hsvImage);
figure
imshow(rgbImage2);
impixelinfo;
title('Altered RGB Image');

Here the result I got:

Do you know how to obtain a less sharper transition between the mask and the rest of the image in order to get a less artificial effect?

Thank you in advance for your help, I'm not very skilled on Image Processing yet.

Best Answer

Instead of multiplying pixels in the mask by a constant value, you can mulitply all pixels by an "image" of the saturation multiplier.

So rather than the scalar "1.6", which could as well have been a element-by-element multiplication, your original strategy could have been executed as

[M,N] = size(Imm)
satFactorMat = 1.6*ones(M,N);
satFactorMat(binaryImage) = 1.6;
saturationImage = saturationImage .* satFactorMat;

So now hopefully it is clear you don't really need the mask concept for the operation of altering the image itself, you just might use it to define the satFactorMat "topography", which looks like a mesa.Now you can just smooth it out using something like a smoothing function; you can use imgaussfilt

satFactorMat = imgaussfilt(satFactorMat,6);

You may need to convert everything to doubles first before doing the imgaussfilt and elementwise multiplication, and then convert back to uint8.

Also, note that multiplying is dangerous because you may end up with values outside valid range (>255). So it would be safe to exponentiate (but then you have to normalize your pixel values onto (0,1) first.

hsvImage = double(hsvImage)/255;
% ... everythign in between
% except instead of multiply by satFactorMat, you can do something like
satPowerMat = ones(M,N);
satPowerMat(binaryImage) = 0.3;
satPowerMat = imgaussfilt(satPowerMat,6);
saturationImage = saturationImage .* satPowerMat;
% Recombine
hsvImage = cat(3, hueImage, saturationImage, valueImage);
hsvImage = uint8(hsvImage*255);

Related Solutions

MATLAB: Increase hue of image

Take the hue image, and multiply it by something.

hsvImage = rgb2hav(rgbImage);
hsvImage(:,:,1) = hsvImage(:,:,1) * someFactor;
rgbImage = hsv2rgb(hsvImage);

I think you really mean increase the saturation, but whatever... The saturation channel is 2, so switch to that if you really want that.

MATLAB: How to make the applied color look more natural/blend into the skin

Try this. I drew the nose up higher so you can see the difference. Adjust the blur window size to soften the rosy disk.

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 = 25;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'capture.png';
% Get the full filename, with path prepended.
folder = pwd
fullFileName = 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;
  end
end
%===============================================================================
% Read in demo image.
rgbImage = imread(fullFileName);
% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage);
% Display the original image.
% subplot(2, 2, 1);
imshow(rgbImage, []);
axis on;
caption = sprintf('Original Color Image, %s', baseFileName);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hp = impixelinfo();
% Set up figure properties:

% Enlarge figure to full screen.


set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% 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.
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
% greenChannel = rgbImage(:, :, 2);
% blueChannel = rgbImage(:, :, 3);
% Let user draw a box around the nose.
uiwait(helpdlg('Locate the nose.  Double-click inside it to accept it'));
hRect = imrect();
noseBox = wait(hRect);
% Draw the image again.
subplot(2, 2, 1);
imshow(rgbImage);
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
hold on;
rectangle('Position', noseBox, 'EdgeColor', 'b');
axis on;
% Convert from RGB color space to HSV color space.
hsvImage = rgb2hsv(rgbImage);
hueImage = hsvImage(:,:,1);
satImage = hsvImage(:,:,2);
valueImage = hsvImage(:,:,3);
subplot(2, 2, 2);
imshow(hsvImage);
title('HSV Image, displayed in RGB', 'FontSize', fontSize, 'Interpreter', 'None');
hold on
hold on;
rectangle('Position', noseBox, 'EdgeColor', 'r');
axis on;
impixelinfo(); % Display status line when user mouses around over image.
%=========================================================
% Create a mask of two circles.
% Define center of circle to the right of the nose.
nx = noseBox(1) + noseBox(3)/2;     
ny = noseBox(2) + noseBox(4)/2;     
final_x = nx - 145;
final_y = ny - 25;
% Make a circular mask on the left side of the image (right side of her face).
theta = 0 : 0.01 : 2*pi;
radius = 45;
X = radius * cos(theta) + final_x;
Y = radius * sin(theta) + final_y;
plot(X, Y, 'b-', 'LineWidth', 1);
leftMask = poly2mask(X, Y, rows, columns);
% Make a circular mask on the right side of the image (left side of her face).
final_x = nx + 145;
theta = 0 : 0.01 : 2*pi;
X2 = radius * cos(theta) + final_x;
plot(X2, Y, 'b-', 'LineWidth', 1);
rightMask = poly2mask(X2, Y, rows, columns);
% Make a mask with both of the circles.
mask = leftMask | rightMask;
% Blur the mask to soften the edges.
blurWindowWidth = 21;
se = strel('disk', blurWindowWidth, 0); % Big circle.
kernel = se.Neighborhood;
kernel = kernel / sum(kernel(:)); % Normalize.
blurredMask = conv2(double(mask), ones(blurWindowWidth)/blurWindowWidth^2, 'same');
% Find the non-zero areas of the blurred mask.
mask = blurredMask > 0;
subplot(2, 2, 3);
imshow(blurredMask);
title('Mask', 'FontSize', fontSize, 'Interpreter', 'None');
hold on
axis on;
% Alter the hue, saturation, and value.
% Desired hue = 0.25.
hueImage(mask) = hueImage(mask) .* (1 - blurredMask(mask));
satImage = satImage + 0.01 * blurredMask;
valueImage = valueImage + 0.01 * 5 * blurredMask;
% Clip to valid range of 0-1.
hueImage(hueImage>1)=1; hueImage(hueImage<0)=0;
satImage(satImage>1)=1; satImage(satImage<0)=0;
valueImage(valueImage>1)=1; valueImage(valueImage<0)=0;
% Put back altered images into hsvImage so we can convert back to RGB.
hsvImage = cat(3, hueImage, satImage, valueImage);
% Convert back to RGB color space.
newRGBImage = hsv2rgb(hsvImage);
subplot(2, 2, 4);
imshow(newRGBImage);
title('New Image', 'FontSize', fontSize, 'Interpreter', 'None');
hold on;
rectangle('Position', noseBox, 'EdgeColor', 'b');
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);
% 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')
% Bring up the new image full screen alone.
figure;
imshow(newRGBImage);
title('New Image', 'FontSize', fontSize, 'Interpreter', 'None');
hold on;
rectangle('Position', noseBox, 'EdgeColor', 'b');
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);

Best Answer

Related Solutions

MATLAB: Increase hue of image

MATLAB: How to make the applied color look more natural/blend into the skin

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