Description
INTRODUCTION
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Have you ever wondered how Instagram color filters work? A color image can be represented by a matrix
with the dimensions corresponding to the dimensions of the image. Each of the elements of this matrix
contains the number (or numbers) representing the color of the corresponding pixel. If the image is a color
image, then the color of the pixel is represented by three numbers {R,G,B} (Red, Green and Blue) with
each number ranging from 0 to 255 (RGB system). In this project we will learn to manipulate these colors
in order to obtain different color effects.
TASKS
1. Start by loading the image into Matlab and displaying it on the screen by using the commands imshow
and imread (type help imshow and help imread to learn about these commands.) Save the resulting
array as ImJPG. You should see the image in the Figure 1.
Variables: ImJPG
Figure 1: The original image
2. Check the dimensions of the array ImJPG using the command [m,n,l]=size(ImJPG). Observe, that
Matlab will return three numbers. Since the image is colored, the resulting array is three-dimensional.
Among other things, Matlab allows operations on multidimensional arrays. The first two dimensions of
the array ImJPG correspond to the horizontal and vertical dimensions (number of pixels) of the image,
and the third dimension stores three numbers corresponding to the values of Red, Green, and Blue for
each pixel. These three colors mixed together produce all other colors in the image. The values for
Red, Green and Blue can range from 0 to 255, allowing us to create 2563 = 16, 777, 216 colors. That
is more than an ordinary human eye can distinguish. In this project, we will be manipulating these
three numbers to achieve various visual effects (similar color filters in Instagram).
Variables: m,n,l
3. First of all, let us look into amount of each of Red, Green, and Blue color in the image. To do this, let
us extract individual layers or color channels from the image array. To obtain the red channel of color
in the image, use the following command:
redChannel = ImJPG(:,:,1);
Similarly, extract green and blue color channels and save them in the arrays greenChannel and
blueChannel. Display each array in a separate figure using figure and imshow commands. Observe that individual color channels will be shown by Matlab as grayscale images. That is due to the
fact that we have taken “layers” off of the matrix ImJPG and each of these layers individually looks like
a two-dimensional array with numbers ranging from 0 to 255 aka like a grayscale image. If you did
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everything correctly, you should see three images like in Figure 2. The whiter the pixel appears on a
particular color channel, the larger amount of that color is contained in that pixel. Other way around,
the darker the area is, the less corresponding color is in that part of the image.
Variables: redChannel, greenChannel, blueChannel
Figure 2: Different color channels
4. Let us convert the original image to a grayscale image by using the following matrix:
GrayMatrix =
1/3 1/3 1/3
1/3 1/3 1/3
1/3 1/3 1/3
This matrix produces an average of red, green, and blue for each pixel. Use the following code:
1 GrayMatrix=[1/3 1/3 1/3; 1/3 1/3 1/3; 1/3 1/3 1/3];
2 for i = 1:m
3 for j = 1:n
4 PixelColor = reshape(double(ImJPG(i,j,:)),3,1);
5 ImJPG Gray(i,j,:) = uint8(GrayMatrix*PixelColor);
6 end;
7 end;
8 figure;
9 imshow(ImJPG Gray)
This code produces an array ImJPG Gray. Observe the use of the commands reshape, uint8, double.
For every pixel of the image, first, the color attributes (RGB) are extracted from the matrix ImJPG,
then these color attributes are treated as a vector with three components [R,G,B], and finally, the color
attributes are changed by multiplying the vector [R, G, B] by the filter matrix GrayMatrix on the left.
The result is saved then as color attributes of the corresponding pixel in the array ImJPG Gray. All
the pixels of the array ImJPG Gray have equal number of Red, Green, and Blue; this produces different
shades of gray color. Observe that there are different ways to create a grayscale conversion, and this
is just one of them.
Variables: ImJPG Gray
Q1: What do the uint8 and double commands do in the code above?
5. Modify the code above to produce a sepia conversion of the image. Instead of GrayMatrix use the
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following filter matrix, and reproduce the code above with this matrix:
SepiaMatrix =
0.393 0.769 0.189
0.349 0.686 0.168
0.272 0.534 0.131
Save the result in the ImJPG Sepia array and display this array using imshow command.
Variables: ImJPG Sepia
6. Next, consider the filter matrix
RedMatrix =
1 0 0
0 0 0
0 0 0
Modify the code again, using the matrix above as a filter matrix. The result should look like the left
image in Figure 3. Save the result as ImJPG Red. Display the image.
Variables: ImJPG Red
Q2: What does the transformation (i.e. multiplying by the matrix RedMatrix) do to the image?
7. Now let us delete one of the colors in the image, say red. First, produce the matrix which deletes red
color in the image and keeps the values of Green and Blue the same. Use it to filter the image. The
result should look like the right image in Figure 3. Save the result as ImJPG DeleteRed.
Variables: ImJPG DeleteRed
Figure 3: Left: Multiplying by RedMatrix. Right: Red color deleted
8. Let us permute the colors in the image. To do this repeat the steps above with the matrix:
PermuteMatrix =
0 0 1
0 1 0
1 0 0
Save the result as ImJPG Permute. If you did correctly, you should see the image in Figure 4.
Variables: ImJPG Permute
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Figure 4: Colors permuted
The matrix PermuteMatrix is an example of hue rotation filter. You can produce other hue rotation
effects with this more general transformation:
HueRotationMatrix =
0.213 0.715 0.072
0.213 0.715 0.072
0.213 0.715 0.072
+ cos(θ)
0.787 −0.715 −0.072
−0.213 0.285 −0.072
−0.213 −0.715 0.928
+ sin(θ)
0.213 −0.715 0.928
0.143 0.140 −0.283
−0.787 0.715 0.072
.
Here θ is the angle of rotation. You can try experimenting with various values of the angle θ to get
different color effects.
9. It is also possible to amplify/deamplify individual colors in the image. For instance, consider the color
transformation with the matrix:
SaturateMatrix =
0.5 0 0
0 2 0
0 0 1
Modify the code with matrix SaturateMatrix. Save the result as ImJPG Saturate.
Variables: ImJPG Saturate
Q3: What does the transformation above do to the image?
10. It is possible to invert the colors of the image by using the following code:
1 ImJPG Invert=255-ImJPG;
2 figure;
3 imshow(ImJPG Invert);
Observe that here again Matlab automatically substitutes matrix of appropriate dimension (in this
case m × n × l) with all the elements equal to 255 instead of the constant 255.
Variables: ImJPG Invert
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