Difference-of-Gaussians on Aayush Bajaj's Augmenting Infrastructure

Seeing in Frequency

Wed, 11 Nov 2026 21:00:00 +1100

Spatial filtering slides a small kernel over the pixels. This page looks at the same image through a different lens: as a sum of waves. In that view blurring keeps the slow waves and throws away the fast ones, a periodic artefact is a handful of bright dots that can be deleted one by one, and an edge detector is a filter that keeps a ring of middle frequencies. The Fourier transform is the change of lens; the convolution theorem is what makes it worth the trouble, because it turns convolution into multiplication. 𐃏

SIFT, Matching and Stitching

Wed, 11 Nov 2026 21:00:00 +1100

Take two photographs of the same building from slightly different spots. To glue them into one panorama you need three things: points that can be found again in both pictures, a way of deciding which point in one picture is which point in the other, and the single geometric map that carries one picture onto the other even though some of those decisions are wrong. The scale-invariant feature transform (SIFT) of Lowe (2004) supplies the first two; a homography fitted by random sample consensus (RANSAC) supplies the third. 𐃏