Fundamentals of Computer Science I: Media Computing (CS151.02 2007F)

Laboratory: Transforming RGB Colors

This lab is also available in PDF.

Summary: In this laboratory, you will experiment with a variety of techniques for transforming RGB colors and images built from RGB colors.




In this laboratory, you will be creating a few images and manipulating others. We will also be working with some colors.

Create a new 4x3 image, call it canvas, show it, and zoom in to 16x resolution.

Open an existing image of your choice, call it picture, and show it. Please choose an image that is not too large (say, not much more than 250x250).

Load your list of favorite colors, /home/username/Desktop/fave-colors.sct. If you don't have that file, use /home/rebelsky/glimmer/samples/fave-colors.sct.


Exercise 1: Lighter and Darker

a. Using rgb->rgb-list or rgb->string, remind yourself of the three components of fave1.

b. Determine what happens to the components when you apply rgb.darker to fave1. You'll need to apply rgb.darker and then find out the components of the new color.

c. Determine what happens when you apply rgb.lighter to fave1.

d. Draw three pixels in sequence on canvas. The first should be the lighter version of fave1. The second should be fave1. The third should be the darker version of fave1. Do you see a difference?

e. What do you expect to happen to the red, green, and blue components if you apply rgb.lighter three times to the color 127/20/20, as in the following?

(define newcolor (rgb.lighter (rgb.lighter (rgb.lighter ( 127 20 20)))))

f. Check your answer experimentally.

g. What do you expect to happen to the red, green, and blue components if you apply rgb.darker three times to the color 127/20/20, as in the following?

(define newcolor (rgb.darker (rgb.darker (rgb.darker ( 127 20 20)))))

h. Check your answer experimentally.

Exercise 2: Other Transformations

As you may recall from the reading, there are also color transformations that make more significant changes to colors. For example, rgb.phaseshift shifts each component by 128 (adding to small components and subtracting from large components). In contrast, rgb.complement computes the complement of a color.

Suppose we've defined the following colors:

(define c0 ( 64 128 196))
(define c1 ( 32 96 255))
(define c2 ( 240 0 127))

a. What do you expect the complements of c0, c1, and c2 to be?

b. Check your answer experimentally.

c. What do you expect the phase shifts of c0, c1, and c2 to be?

d. Check your answer experimentally.

Exercise 3: Transforming Pixels

a. Set pixels (0,0) and (1,1) of canvas to fave1.

b. Make the top-left pixel darker using the more verbose instruction from the reading.

(image.set-pixel! canvas 0 0 (rgb.darker (image.get-pixel canvas 0 0)))

c. Make the pixel at (1,1) darker using the the more concise image.transform-pixel! procedure.

(image.transform-pixel! canvas 1 1 rgb.darker)

d. Do you see any advantages of using the longer instruction?

Exercise 4: Transforming and Copying Pixels

Of course, rather than computing new pixels from the pixels in one image, we can also compute them from the pixels in another image. For example, the following code should put in canvas a darker version of the top-left square of some pixels from picture

(image.set-pixel! canvas 0 0 (rgb.darker (image.get-pixel picture 100 100)))
(image.set-pixel! canvas 0 1 (rgb.darker (image.get-pixel picture 100 101)))
(image.set-pixel! canvas 1 0 (rgb.darker (image.get-pixel picture 101 100)))
(image.set-pixel! canvas 1 1 (rgb.darker (image.get-pixel picture 101 101)))

Confirm experimentally that these instructions work as we suggested.

Exercise 5: Multiple Transformations

Of course, we can get more transformations by combining the basic transformations. For example, we get a different color when we complement and darken a color than when we complement or darken the color alone.

a. Does the order in which we apply transformations matter? In particular, do you get the same or different color when you complement and then darken a color as compared to when you darken and then complement the color? In code, what is the relationship between newcolor1 and newcolor2?

(define newcolor1 (rgb.darken (rgb.complement fave1)))
(define newcolor2 (rgb.complement (rgb.darken fave1)))

b. Check your answer experimentally.

c. What do you expect to have happen if you complement a color twice, as in this example?

(define newcolor3 (rgb.complement (rgb.complement fave2)))

d. Check your answer experimentally.

e. At first glance, lightening and darkening an image seem to be complements. Are there ever times in which the sequence of lighten and then darken does not give you back the same color?

(define newcolor4 (rgb.darken (rgb.lighten fave3)))

f. Check your answer experimentally. In doing so, try colors near the extremes, such as black, white, yellow, 10/255/127, and such.

Exercise 6: Transforming Larger Sections

In the corresponding reading, there is a set of sample code that is intended to transform canvas by complementing every pixel.

(image.transform-pixel! canvas 0 0 rgb.complement)
(image.transform-pixel! canvas 0 1 rgb.complement)
(image.transform-pixel! canvas 0 2 rgb.complement)
(image.transform-pixel! canvas 0 3 rgb.complement)
(image.transform-pixel! canvas 1 0 rgb.complement)
(image.transform-pixel! canvas 1 1 rgb.complement)
(image.transform-pixel! canvas 1 2 rgb.complement)
(image.transform-pixel! canvas 1 3 rgb.complement)
(image.transform-pixel! canvas 2 0 rgb.complement)
(image.transform-pixel! canvas 2 1 rgb.complement)
(image.transform-pixel! canvas 2 2 rgb.complement)
(image.transform-pixel! canvas 2 3 rgb.complement)

a. There is a subtle error in the code. Identify the error and fix it. (If you can't figure out the error, try running the code to see what error messages you get.)

b. Update canvas so that it has a variety of colors. Here is one set of simple changes, but you can do what you want.

(image.set-pixel! canvas 0 0 ( 0 0 0))
(image.set-pixel! canvas 1 0 ( 255 0 0))
(image.set-pixel! canvas 2 0 ( 0 255 0))
(image.set-pixel! canvas 3 0 ( 0 0 255))
(image.set-pixel! canvas 0 1 ( 255 255 255))
(image.set-pixel! canvas 1 1 ( 255 0 255))
(image.set-pixel! canvas 2 1 ( 255 255 0))
(image.set-pixel! canvas 3 1 ( 0 255 255))
(image.set-pixel! canvas 0 2 ( 63 127 195))
(image.set-pixel! canvas 1 2 ( 127 195 63))
(image.set-pixel! canvas 2 2 ( 195 63 127))

c. Verify that the repaired instructions do, in fact, complement all of the pixels.

d. What do you expect to have happen if you run this code twice?

e. Check your answer to the previous question experimentally.

For Those With Extra Time

Extra 1: Phase Shifting vs. Complementing

At first glance, some find that rgb.phaseshift is a lot like rgb.complement. After all, each changes a color by shifting the components, and adding or subtracting 128 may feel like an easier way to get something that sums to 255. However, as we've suggested in the reading, the two operations are quite different.

a. Find two colors whose pseudo-complements are fairly close to their phase-shifted versions. You may find the following code useful as you visually compare the different colors.

(define color1 ( __ __ __))
(define color2 ( __ __ __))
(define ps1 (rgb.phaseshift color1))
(define ps2 (rgb.phaseshift color2))
(define comp1 (rgb.complement color1))
(define comp2 (rgb.complement color2))
(image.set-pixel! canvas 0 0 color1)
(image.set-pixel! canvas 1 0 ps1)
(image.set-pixel! canvas 2 0 comp1)
(image.set-pixel! canvas 0 2 color2)
(image.set-pixel! canvas 1 2 ps2)
(image.set-pixel! canvas 2 2 comp2)

b. Find two colors whose phase-shifted versions are much different than their pseudo-complements.

c. Do you expect there to be more colors like those in a, or more colors like those in b? (That is, is it more likely that the pseudo-complement of a color is close to the phase-shifted color, or that they are different?) Explain your answer.




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Samuel A. Rebelsky,

Copyright © 2007 Janet Davis, Matthew Kluber, and Samuel A. Rebelsky. (Selected materials copyright by John David Stone and Henry Walker and used by permission.) This material is based upon work partially supported by the National Science Foundation under Grant No. CCLI-0633090. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. This work is licensed under a Creative Commons Attribution-NonCommercial 2.5 License. To view a copy of this license, visit or send a letter to Creative Commons, 543 Howard Street, 5th Floor, San Francisco, California, 94105, USA.