A major theme of yesterday's lecture, and a major theme of our class, was how poor sampling and reconstruction can lead to aliasing.

Recall that aliasing means, roughly speaking, when something appears to be what it is not. (In English, an "alias" essentially just means a false name or identity.) In computer graphics and signal processing, aliasing occurs because of a mismatch between sampling and reconstruction: the rate or manner in which a signal is sampled is insufficient to provide a faithful reconstruction of the original signal.

We discussed several examples in class, such as:

• Losing peaks/valleys in a 1D function when sampled at regular intervals and reconstructed via piecewise linear interpolation.
• The "wagon wheel effect" where a car wheel appears to spin backwards under artificial illumination.
• "Shimmering" artifacts that come from sampling a checkerboard at 1 sample per pixel.
• Moire patterns that show up in a wire trash basket, or the artificial "zone plate" image.
• Bright vertical and horizontal lines in the 2D Fourier transform of a pixel image.

Your quiz is to identify one interesting place where aliasing shows up that is different from the ones we saw in class. (E.g., it should not just be a minor riff on one of the examples above, but should really be a different example.) The two criteria for when something is aliased should be:

1. the thing appears different from what it really is, and
2. this illusion is a result of poor sampling/aliasing.

For instance, there are plenty of optical illusions (e.g., that have to do with psychological or perceptual phenomena), but not all of them are examples of aliasing, since they do not all have to do with sampling and reconstruction.

Finally, remember that aliasing is not something that just happens on a computer, but can also happen "in real life," e.g., when you look at a wire trash basket or a spinning wheel, your eyes and brain pick up on features that are not really there.

As usual, the quiz should be handed in on a piece of paper at the beginning of the next lecture (Wednesday, 2/5).