alt Hacker NewsVery neat. I have a love-hate relationship with a unique type of digital sensor called the Foveon X3, which needs a particular (very sluggish and limited capability) software made by Sigma to convert the RAWs. Recently I have been using AI to create a converter that processes the RAWs in a similar fashion with some improvements.
This is one of those cases where its a means-to-an-end (I just want to take more photos without being bogged down) and less of a project for me to learn how to reverse-engineer and design signal processing pipelines. I am very grateful for what recent models are enabling me to do.
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Remind us what the Foveon sensor's quirk was? Something in the subpixel layout as I recall. A non-bayer pattern since abandoned and largely unsupported, yet effective somehow. But maybe I'm imagining this.
What improvements have you made? Processing RAW sluggishness was always an issue from de-Bayering. Before RAW, my hell was DPX image sequences. This was pre-SSD, so I/O was painful opening/closing individual frames in realtime. The best improvement of processing RAW I've experienced was NVMe SSDs.
Everyone has a love/hate relationship with Foveon, that's the beauty of the sensor isn't it ? Would you mind sharing your project ? That's awesome. Have you been able to compare crispness of files ? Dng compatibility from latest cameras, although it results in huge files, was pretty useful but files were not as sharp as native X3F developed in Sigma Photo Pro.