Interpolation in 5 minutes
2024 ж. 20 Мам.
12 259 Рет қаралды
Equivalent to a 50 minute university lecture on convolution-based interpolation methods.
0:00 - intro
0:31 - 1D convolution
1:02 - linear interpolation with a hat filter
2:12 - deriving the sinc function
3:33 - ringing
4:19 - cubic and lanczos filters
4:51 - 2D interpolation filters
Graphics in 5 minutes is a series of cartoon-style videos that teach computer graphics in 10x less time. You can take the equivalent of a University level computer graphics course in just over two hours. The playlist is here:
• Graphics in 5 minutes ...
See here for more information: g5m.cs.washington.edu/
I really think the video is underestimated... it is clear, easy to understand, and comprehensive
Please for the love of all that is holy keep making these videos. Why is it that almost all the best foundational math content used in Computer Vision applications I can find online comes from someone at The University of Washington? Y'all are awesome!
What a beautifully simplified way to visualize the working of kernels and its relation to interpolation. WAW!
This was a good one. Cheers!
I arrived at your video from the audio world, where there is a fellow who has made interpolation filters for reconstructing analog audio waveforms from digital samples. While an infinite-length sinc function can perfectly reconstruct a bandlimited signal from its samples, what is the interpolation error for finite-length sinc functions? This fellow (Rob Watts / Chord Electronics) uses upwards of a million (!!) taps of a sinc function to reconstruct the signal. With fewer taps (say, 100) would the estimation of inter sample peaks (like those encountered with drums) be shifted in time upon reconstruction?
hear me out. it'll be "Interpolation in 2.5 minutes" if you put the playback speed on 2x