more-fundamentals.slides.printing.6 - Sampling Revisited CS...

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CS 450: Introduction to Digital Signal and Image Processing A Few More Fundamentals… Sampling Revisited How much sampling is enough? Shannon Sampling Theorem : Twice the highest frequency in the signal (in theory) Nyquist rate What happens if you sample above this? Avoids dangers of theoretical limits Better for intermediate processing What happens if you don’t sample enough? Aliasing (false low-frequencies components appear) Moiré patterns Insufficient sampling during acquisition introduces flaws that cannot be corrected through later processing Moiré Patterns Interpolation Sometimes we want to turn a digital signal into an analog one Need to “undo” the sampling by interpolating the values between the samples Reasons: Physical playback or display “Resampling” (resizing, changing bitrate, etc.) Geometric transformation (rotation, warping, etc.) Interpolation Interpolation is the process of guessing values of a
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more-fundamentals.slides.printing.6 - Sampling Revisited CS...

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