The better alternatives are all like 50-page papers with worse titles and a lot of math. If you know a nice 5–10-page “modern” summary of how to treat filters f

The better alternatives are all like 50-page papers with worse titles and a lot of math. If you know a nice 5–10-page “modern” summary of how to treat filters for image resampling aimed at a non-specialist audience, please link away. I’ll agree that treating pixels as Gaussians is not especially great. In practice most images go through multiple layers of processing, physical sensor and display pixels come in all kinds of wacky shapes (and as you point out have channels offset by different amounts, etc.). It’s usually better to treat pixels as point samples for generic intermediate processing because you have no idea what kind of source an image comes from, and you have no idea what someone down the line is going to do with your image before sending a final signal to the display hardware. Creating synthetic images by integrating over little rectangles produces markedly inferior results to applying some real resampling filter to the samples, but gets done by computer games etc. because it’s computationally cheap, with the hope that there are enough pixels moving fast enough that someone won’t notice the artifacts.