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mit.edu
Demonstration 2: Sampling, Aliasing, and Frequency Response, Part 2 | Digital Signal Processing | Electrical Engineering and Computer Science | MIT OpenCourseWare
MIT OpenCourseWare is a web based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity
Apr 7, 2022
Downsampling Examples
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peter Magaga on Instagram: "Downsampling Explained — Why Small Images Still Make Sense: Downsampling shrinks an image by selecting fewer pixels from the original, which keeps the main shapes visible because large patterns survive while tiny details disappear. As fewer samples represent the scene, fine textures fade, edges soften, and small features vanish—but the overall structure remains clear enough for the brain to understand what’s happening. This is why cameras, editing software, and AI mod
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PEEPER on Instagram: "Physically slicing an image into smaller pieces is one of the simplest ways to understand downsampling, because each fragment retains the large shapes while losing the fine details that disappear at lower resolution. Digital downsampling works the same way by averaging and compressing pixels so the overall structure stays clear, yet the tiny patterns the eye would barely notice at smaller sizes are removed to save space and processing power. Seeing the process physically ma
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