The Unreasonable Effectiveness of JPEG: A Signal Processing Approach
Visit https://brilliant.org/Reducible/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription. Chapters: 00:00 Introducing JPEG and RGB Representation 2:15 Lossy Compression 3:41 What information can we get rid of? 4:36 Introducing YCbCr 6:10 Chroma subsampling/downsampling 8:10 Images represented as signals 9:52 Introducing the Discret
Compressed Sensing in Python
In this post I’ll be investigating compressed sensing (also known as compressive sensing, compressive sampling, and sparse sampling) in Python. Since the idea of compressed sensing can be applied in wide array of subjects, I’ll be focusing mainly on how to apply it in one and two dimensions to things like sounds and images. Specifically, I will show how to take a highly incomplete data set of sign
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