image modeling and optimization

The morning began with a talk by Oguz Semerci (Schlumberger-Doll) about optimization and inverse problems in imaging where the data are non trivially related to the image of interest and the problem is under-determined (requiring regularization). He showed examples from medical imaging, airport security, and oil exploration. Unlike many talks I see in these areas, he wasn't restricting to convex problems but still had very good performance. My only complaint would be that he was custom-building optimizers for each problem; I would be surprised if he beats the best industrial optimizers out there. Of course Lang and I are guilty of the same thing in The Tractor! One beautiful idea in his talk is the use of level sets to define the shapes of complex, opaque objects (or image segments).

Mid-day, Maria Kapala (Cape Town), Dustin Lang, and I had a chat about how to proceed on modeling Herschel imaging. Lang agreed to help Kapala get our old code from 2012 working again, and consult on optimization. I promised to start writing the paper (my favorite) and Kapala agreed to gather the relevant data for paper 1. (Somehow the two paragraphs of this research-blog post are more similar than I expected.)

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