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- Aliasing can arise when you sample a continuous signal or image
- occurs when your sampling rate is not high enough to capture the amount
of detail in your image
- Can give you the wrong signal/image—an alias
- formally, the image contains structure at different scales
- called “frequencies” in the Fourier domain
- the sampling rate must be high enough to capture the highest frequency
in the image
- To avoid aliasing:
- sampling rate ≥ 2 * max frequency in the image
- said another way: ≥ two samples per cycle
- This minimum sampling rate is called the Nyquist rate
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- So far, we considered only power-of-two subsampling
- What about arbitrary scale reduction?
- How can we increase the size of the image?
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- So far, we considered only power-of-two subsampling
- What about arbitrary scale reduction?
- How can we increase the size of the image?
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- So what to do if we don’t know
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- What does the 2D version of this hat function look like?
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- A simple method for resampling images
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