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SUMMARY:Computational Imaging and Sensing: Theory and Applications - Prof.
  Pier Luigi Dragotti\, Imperial College London
DTSTART:20220512T140000Z
DTEND:20220512T150000Z
UID:TALK172475@talks.cam.ac.uk
CONTACT:Prof. Ramji Venkataramanan
DESCRIPTION:The revolution in sensing\, with the emergence of many new ima
 ging techniques\, offers the possibility of gaining unprecedented access t
 o the physical world\, but this revolution can only bear fruit through the
  skilful interplay between the physical and computational realms. This is 
 the domain of computational imaging which advocates that\, to develop effe
 ctive imaging systems\, it will be necessary to go beyond the traditional 
 decoupled imaging pipeline where  device physics\, image processing and th
 e end-user application are considered separately. Instead\, we need to ret
 hink imaging as an integrated sensing and inference model.\n \nIn the firs
 t part of the talk we highlight the centrality of sampling theory in compu
 tational imaging and  investigate new sampling modalities which are  inspi
 red by the emergence of new sensing mechanisms. We discuss time-based samp
 ling which is connected to event-based cameras where pixels behave like ne
 urons and fire when an event happens. We derive sufficient conditions and 
 propose novel algorithms for the perfect reconstruction of classes of non-
 bandlimited functions from time-based samples. We then discuss sampling at
  unknown location in particular we address the problem of reconstructing 2
 -D shapes from tomographic projections at unknown angles. This problem is 
 linked to Cryogenic Electron Microscopy which produces a large number of t
 omographic projections of molecules dispersed in a frozen solution\, howev
 er\,  orientation of these projections is unknown.\n \nIn the second part 
 of the talk\, we develop the interplay between learning and computational 
 imaging. We discuss the problem of monitoring the activity of neurons with
  two-photon microscopes and present a model-based neural network for the l
 ocalization of neurons. The architecture of the network is model-based and
  is designed using the unfolding technique. Finally\, we focus on the heri
 tage sector which is experiencing a digital revolution driven in part by t
 he increasing use of non-invasive\, non-destructive imaging techniques. Th
 ese new imaging methods provide a way to capture information about an enti
 re painting and can give us information about features at or below the sur
 face of the painting. We focus on Macro X-Ray Fluorescence (XRF) scanning 
 which is a technique for the mapping of chemical elements in paintings and
  introduce a method that can process XRF scanning data from paintings. The
  results presented show the ability of our method to detect and separate w
 eak signals related to hidden chemical elements in the paintings. We analy
 se the results on Leonardo’s “The Virgin of the Rocks” and show that
  our algorithm is able to reveal\, more clearly than ever before\, the hid
 den drawings of a previous composition that Leonardo then abandoned for th
 e painting that we can now see.\n \nThis is joint work with  A. Foust\, R.
  Alexandru\, R. Wang\, P. Song\, C. Howe\, H. Verinaz\, J. Huang and Y.Su 
 from Imperial College London\, and C. Higgitt and N. Daly from The Nationa
 l Gallery in London.\n\n*Bio*: Pier Luigi Dragotti is Professor of Signal 
 Processing in the Electrical and Electronic Engineering Department at Impe
 rial College London and Fellow of the IEEE. He received the Laurea Degree 
 (summa cum laude) in Electronic Engineering from the University Federico I
 I\, Naples\, Italy\, in 1997\; the Master degree in Communications Systems
  from the Swiss Federal Institute of Technology of Lausanne (EPFL)\, Switz
 erland in 1998\; and PhD degree from EPFL\, Switzerland\, in 2002. He has 
 held several visiting positions. In particular\, he was a visiting student
  at Stanford University\, Stanford\, CA in 1996\, a summer researcher in t
 he Mathematics of Communications Department at Bell Labs\, Lucent Technolo
 gies\, Murray Hill\, NJ in 2000\, a visiting scientist at Massachusetts In
 stitute of Technology (MIT) in 2011 and a visiting scholar at Trinity Coll
 ege Cambridge in 2020.\n\nDragotti was Editor-in-Chief of the IEEE Transac
 tions on Signal Processing (2018-2020)\, Technical Co-Chair  for the Europ
 ean Signal Processing Conference in 2012\, Associate Editor  of the IEEE T
 ransactions on Image Processing from 2006 to 2009. He was also  Elected Me
 mber  of the IEEE Computational Imaging Technical Committee and the recipi
 ent of an ERC starting investigator award for the project RecoSamp. Curren
 tly\, he is IEEE SPS Distinguished Lecturer.\n\nHis research interests inc
 lude sampling theory\, wavelet theory and its applications\, computational
  imaging and sparsity-driven signal processing.  \n 
LOCATION:JDB Seminar Room\, CUED
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