אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

Recent advances in computational imaging have significantly expanded our ability to image through scattering layers such as biological tissues, by exploiting the auto-correlation properties of captured speckle patterns. However, most experimental demonstrations of this capability focus on the far-field imaging setting, where obscured light sources are very far from the scattering layer. By contrast, medical imaging applications such as fluorescent imaging operate in the near-field imaging setting, where sources are inside the scattering layer. We provide a theoretical and experimental study of the similarities and differences between the two settings, highlighting the increased challenges posed by the near-field setting. We then draw insights from this analysis to develop a new algorithm for imaging through scattering that is tailored to the near-field setting, by taking advantage of unique properties of speckle patterns formed under this setting, such as their local support. We present a theoretical analysis of the advantages of our algorithm, and perform real experiments in both far-field and near-field configurations, showing an order-of magnitude expansion in both the range and the density of the obscured patterns that can be recovered. Short bio: Marina Alterman received the B.Sc. M.Sc. and Ph.D. degrees in electrical engineering from the Technion under the supervision of Prof. Yoav Schechner. She was a Postdoctoral Fellow in the Department of Electrical Engineering and Computer Science, Northwestern university, Evanston, IL, USA, during 2015–2017. She is currently a researcher in the Computational Imaging lab (prof. Anat Levin) in the Electrical Engineering at the Technion.