Image Processing Reference
In-Depth Information
Fig. 3.13 A color image
captured by a Bayer pattern
3.5
Exercises
Exercise 1: Explain the following concepts: rods, cones, achromatic, chromaticity
plane, additive colors, subtractive colors, color spaces.
Exercise 2: How many different 512
×
512 color (24-bit) images can be con-
structed?
Exercise 3: The image in Fig. 3.13 was captured by a Bayer pattern sensor. Use
demosaicing to convert the image into an RGB image.
Exercise 4: An RGB image is converted into a gray-scale image so that the cyan
color is enhanced. What are the weight factors for R, G, and B, respectively?
Exercise 5: Is the RGB pixel (R,G,B)
( 42 , 42 , 42 ) located on the gray-vector?
Exercise 6: An RGB image is converted into a gray-scale image. During the con-
version W B =
=
0 and the two remaining colors are weighted equally. A pixel in the
gray-scale image has the value 100. How much green was present in the corre-
sponding RGB pixel when we know that R
=
20?
Exercise 7: Convert the RGB pixel (R,G,B)
( 20 , 40 , 60 ) into (r,g,b) , (r,g,I) ,
(H,S,I) , (H,S,V) , (Y,U,V) , and (Y, C b ,C r ) , respectively.
Exercise 8: Show that r + g + b =
=
1.
Additional exercise 1: How is color represented in HTML?
Additional exercise 2: What is the “red-eye effect” in pictures and what can be
done about it?
Additional exercise 3: What is white balance?
Additional exercise 4: What is color blindness?
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