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Halftoned images, esp old images, can be "descreened" to produce clearer versions than just blurring the halftone.
Some use neural networks and some use FFT math. Here's a nice image of descreening from this excellent page and paper (click for higher res comparison):
Closeup:
Research:
- https://dercuano.github.io/notes/processing-halftoning.html
- https://www.cse.cuhk.edu.hk/~leojia/projects/rollguidance/results_dehalftone.html
- https://github.com/ccc870206/InverseHalftoneColorization
- https://github.com/MenghanXia/InverseHalftoning \
- GIMP descreen plugin:
- Opencv: https://github.com/6o6o/fft-descreen
Maybe the FFT-descreen OpenCV library looks simplest and most promising?
Could we refactor that and model on our other OpenCV modules, like our Blob Analysis module?
https://github.com/publiclab/image-sequencer/blob/main/src/modules/BlobAnalysis/BlobAnalysis.js

