# 0.16 Lab 10b - image processing (part 2)  (Page 2/5)

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In $Y{C}_{b}{C}_{r}$ , the luminance parameter is related to an overall intensity of the image.The chrominance components are a measure of the relative intensities of the blue and red components. The inverse of the transformation in [link] can easily be shown to be the following.

$\begin{array}{ccc}R\hfill & =\hfill & Y+1.4025\left({C}_{r}-128\right)\hfill \\ G\hfill & =\hfill & Y-0.3443\left({C}_{b}-128\right)-0.7144*\left({C}_{r}-128\right)\hfill \\ B\hfill & =\hfill & Y+1.7730\left({C}_{b}-128\right)\hfill \end{array}$

## Color exercise

You will be displaying both color and monochrome images in the following exercises.Matlab's image command can be used for both image types, but care must be taken for the command to work properly.Please see the help on the image command for details.

Download the $RGB$ color image file girl.tif , and load it into Matlab using the imread command. Check the size of the Matlab array for this image by typing whos . Notice that this is a three dimensional array of type uint8 . It contains three gray scale image planes corresponding to the red, green, andblue components for each pixel. Since each color pixel is represented bythree bytes, this is commonly known as a 24-bit image. Display the color image using

image(A);

axis('image');

where $A$ is the 3-D $RGB$ array.

You can extract each of the color components using the following commands.

RGB = imread('girl.tif'); % color image is loaded into matrix RGB

R = RGB(:,:,1); % extract red component from RGB

G = RGB(:,:,2); % extract green component from RGB

B = RGB(:,:,3); % extract blue component from RGB

Use the subplot and image commands to plot the original image, along with each of the three color components.Note that while the original is a color image, each color component separately is a monochrome image.Use the syntax subplot(2,2,n) , where $n=1,2,3,4$ , to place the four images in the same figure.Place a title on each of the images, and print the figure(use a color printer).

We will now examine the $Y{C}_{b}{C}_{r}$ color space representation. Download the file ycbcr.mat , and load it intoMatlab using load ycbcr . This file contains a Matlab array for a color image in $Y{C}_{b}{C}_{r}$ format. The array containsthree gray scale image planes that correspond to the luminance ( $Y$ ) and two chrominance ( ${C}_{b}{C}_{r}$ ) components. Use subplot(3,1,n) and image to display each of the components in the same figure.Place a title on each of the three monochrome images, and print the figure.

In order to properly display this color image, we need to convert it to $RGB$ format. Write a Matlab function that will perform the transformation of [link] . It should accept a 3-D $Y{C}_{b}{C}_{r}$ image array as input, and return a 3-D $RGB$ image array.

Now, convert the ycbcr array to an $RGB$ representation and display the color image.Remember to convert the result to type uint8 before using the image command.

An interesting property of the human visual system, with respect to the $Y{C}_{b}{C}_{r}$ color space, is that we are much more sensitive to distortion in the luminance component than in the chrominancecomponents. To illustrate this, we will smooth each of these components with a Gaussian filter and view the results.

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