1. Color Perception of color Color spaces
Three cones sensitive to “red”, “green”, and “blue”
Overlapping response curves
Color spaces
, ,  space vs. R, G, B space vs. X, Y, Z space, 3x3 matrices to convert between them
Gamut, chromaticity diagrams

2. Color Combining colors Intuitive colorspaces
Additive vs. subtractive mixing
Primaries
Intuitive colorspaces
Single and double cones, hexcones
HSL, HSV
When are these useful? When is RGB preferable?

3. Color Sample questions:
What are ideal spectra for primaries used in additive mixing? Why?
The point (255, 127, 127) in RGB space is nearest to what point in single-hexcone HSV space?
The gamut of a typical CRT, when drawn on a chromaticity diagram, does not intersect the locus of spectral colors. Why not?

4. Sampling and Antialiasing
The sampling and reconstruction pipeline:
Prefiltering
Sampling
Resampling
Reconstruction
Fourier transform, aliasing in the frequency domain
Filtering and convolution

5. Sampling and Antialiasing
Prefiltering vs. postfiltering
Desirable filters for antialiasing
Supersampling
Regular vs. stochastic
Unweighted/weighted area sampling
Why is this an approximation?

6. Sampling and Antialiasing
Sample questions:
Which of the following would affect your choice of a reconstruction filter?
Pixel shape
Choice of prefilter
Actual size of the display
What is the result of convolving a 1-D box filter with itself?