From the article

> In the days of generative image models, it's still fun to see what can be achieved using traditional image transformation techniques.

> But the really fun part of the project was in combining a number of techniques, such as Perlin noise, wavelets, and edge detection, that I played around with previously in isolation. All these different tricks came together for this project, making it possible to build something greater than the sum of its parts. I find these are the most rewarding types of experiments where you can build on things you've previously learned and combine them in novel ways to make something new and unexpected. I hope you enjoyed the journey as much as I did working on the project.

You can already use genAI to do similar things. The whole point, however, was to see what I could do using traditional techniques. The other benefit is that it's something you can run locally without needing a lot of resources, and have full control over the shape of the output. You can also combine this with generative models, and have a model generate a picture, then have this repaint it. Ultimately the point was to have some fun and play around with combining these techniques.