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SUMMARY:Joint imaging and calibration using non-convex optimization - Audr
 ey Repetti (Heriot-Watt University)
DTSTART:20170907T135000Z
DTEND:20170907T144000Z
UID:TALK78261@talks.cam.ac.uk
CONTACT:INI IT
DESCRIPTION:<span>Co-authors: Jasleen Birdi		(Heriot Watt University)\, Yv
 es Wiaux		(Heriot Watt University)        <br></span><br>New generations o
 f imaging devices aim to produce high resolution and high dynamic range im
 ages. In this context\, the high dimensionality associated inverse problem
 s can become extremely challenging from an algorithmic view point. In addi
 tion\, the quality and accuracy of the reconstructed images often depend o
 n the precision with which the imaging device has previously been calibrat
 ed. Unfortunately\, calibration does not depend only on the device but may
  also rely on the time and on the direction of the acquisitions. This lead
 s to the need of performing joint image reconstruction and calibration\, a
 nd thus of solving non-convex blind deconvolution problems.  <br><span><br
 >We focus on the joint calibration and imaging problem in the context of r
 adio-interferometric imaging in astronomy. In this case\, the sparse image
 s of interest can reach gigapixel or terapixel size\, while the calibratio
 n variables consist of a large number of low resolution images related to 
 each antenna of the telescope. To solve this problem\, we leverage a block
 -coordinate forward-backward algorithm\, specifically designed to minimize
  non-smooth non-convex and high dimensional objective functions. We demons
 trate by simulation the performance of this first joint imaging and calibr
 ation method in radio-astronomy.</span>
LOCATION:Seminar Room 1\, Newton Institute
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