Exploring the Power of Filtering in Signal Processing
Delve into the world of signal processing and filtering as a means of separating desired information from noise. Explore the role of digital filters in processing images and signals. Discover how filtering can achieve noise cancellation in headphones, clean up noisy images, and understand the importance of frequency concepts in signal processing.
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Presentation Transcript
Filtering Separating what you want from what you have
Signals are all around us Image, video, audio, radio, medical and musical signals These signals contain a lot of information
We can also filter signals signal (we want) + noise (we don t) FILTER signal (we want)
Digital Filters When an image is being processed by a computer/iPhone 1 0 0 1 0 1 0 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 1 0 0 0 0 1 0 0 1 0 1 0 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 0 1 0 1 0 1 0 1 0 0 0 0 1 1 1 1 1 0 0 0 0 1 1 0 1 1 1 1 0 0 0 0 1 0 1 0 1 1 1 1 0 0 0 0 1 1 1 0 1 0 1 0 0 1 0 1 0 1 0 1 0 1 0 1 0 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 1 1 1 0 1 0 1 0 0 we can filter it using computation (also known as digital signal processing or DSP)
What can filtering achieve? Noise-cancelling headphones reduce unwanted ambient sounds (noise) by generating an antinoise sound wave to cancel the noise, letting just the music be heard
What can filtering achieve? noisy image de-noised image
The concept of frequency Describes how quickly a signal moves low frequency high frequency Plays an important role in many types of filters
middle C 261.626 Hz middle A 440 Hz
Spectrum Hz 261 27.5 4186 440
Spectrum of a real-world signal Real-world signals can be thought of as combinations of different frequency components
Many filters act by keeping some frequencies (the ones we want) and throwing away others (the ones we don t)
