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The basics of convolutions in the context of image processing.
Course website: https://computationalthinking.mit.edu/Fall20/

Contents:
0:00 - Introduction
1:12 - Box blur as an average
3:00 - Dealing with the edges
4:31 - Gaussian blur
5:30 - Visualizing gaussian blur
6:04 - Convolution
6:40 - Kernels and the gaussian kernel
7:26 - Looking at the convolution in Julia
8:45 - Julia: `ImageFiltering` package and Kernels
9:08 - Julia: `OffsetArray` with different indices
10:15 - Visualizing a kernel
11:25 - Computational complexity
12:00 - Julia: `prod` function for a product
13:00 - Example of a non-blurring kernel
16:00 - Sharpening edges in an image
17:13 - Edge detection with Sobel filters
21:25 - Relation to polynomial multiplication
25:00 - Convolution in polynomial multiplication
26:08 - Relation to Fourier transforms
28:50 - Fourier transform of an image
31:50 - Convolution via Fourier transform is faster
34:00 - Final thoughts

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