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UID:88027c8817f72808b98b6eb9e6040fdd
CATEGORIES:Applied and Computational Math Seminar
CREATED:20240314T192829
SUMMARY:Regularization Methods for Inverse Problems in Imaging
LOCATION:Hill 425
DESCRIPTION:<div style="border: 0px; font-style: normal; font-weight: 400; font-size: 1
 5px; line-height: inherit; font-family: 'Segoe UI', 'Segoe UI Web (West Eur
 opean)', 'Segoe UI', -apple-system, BlinkMacSystemFont, Roboto, 'Helvetica 
 Neue', sans-serif; margin: 0px; padding: 0px; vertical-align: baseline; col
 or: #242424; letter-spacing: normal; orphans: 2; text-align: start; text-in
 dent: 0px; text-transform: none; widows: 2; word-spacing: 0px; white-space:
  normal; background-color: #ffffff;">Discrete linear and nonlinear inverse 
 problems arise from many different imaging systems, exhibiting inherent ill
 -posedness wherein solution sensitivity to data perturbations prevails. Thi
 s sensitivity is exacerbated by errors arising from imaging system componen
 ts (e.g., cameras, sensors, etc.), necessitating the development of robust 
 regularization methods to attain meaningful solutions. This talk starts wit
 h a review of distinct imaging systems and their mathematical formalism and
  subsequently introduces regularization techniques tailored for linear inve
 rse problems. Then, we will look into the variable projection method, a pow
 erful tool to address separable nonlinear least squares problems.&nbsp;<br 
 aria-hidden="true"></div>
CONTACT:Malena Espanol (Arizona State University )
DTSTAMP:20260826T213940
DTSTART;TZID=America/New_York:20240405T130000
DTEND;TZID=America/New_York:20240405T140000
SEQUENCE:0
TRANSP:OPAQUE
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