Mathematical Challenges in Astronomical Imaging

January 26 - 30, 2004


This workshop on Mathematical Challenges in Astronomical Imaging will focus on novel mathematical techniques in image reconstruction and image analysis. New approaches to deconvolution will be explored, with emphases on developments in multiscale, Bayesian, and wavelet methods, on the varieties of point spread functions that characterize modern astronomical instrumentation and on the constraints presented by astronomical images (non-negativity, continuity [nebulae] or discontinuity [stars] on sub-resolution scales). Other topics of interest include: image formation from sparse interferometer data, mosaicking and resampling techniques, and source location algorithms in the presence of noise. Imaging challenges specific to low-count-rate techniques such as X-ray, gamma-ray, neutrino and cosmic ray astronomy will also be discussed, including event reconstruction algorithms, and adaptive smoothing techniques. Finally, imaging challenges specific to the cosmic microwave background will be addressed. The goal of this workshop is to bring scientists from the astronomical community together with mathematicians to explore these issues.


  1. Opening session: New Types of Astronomical Data (1/2 day)
  2. Direct Imaging Techniques/ Aperture Masking/ Imaging and Modelling with Sparse Interferometer Data (1 day)
  3. Point Spread Function Extraction for Crowded Fields (1/2 day)
  4. Time-Domain Imaging (1/2 day)
  5. Deconvolution (1- 1 1/2 days)
  6. Imaging With Photon-Limited Data (1/2 day)
  7. Cosmic Microwave Background Imaging (1/2 day)

Organizing Committee

Alanna Connors (Eureka Scientific)
Tim Cornwell (National Radio Astronomical Observatory)
Brent Ellerbroek (National Optical Astronomical Observatory)
Don Gavel (Lawrence Livermore National Laboratory)
Robert Hanisch (Space Telescope Science Institute)
Margarita Karovska (Harvard University, Smithsonian Astrophysical Observatory, HEAD)
Mark Morris, Chair (UCLA, Physics & Astronomy)
Stanley Osher (IPAM, Mathematics)
David van Dyk (University of California at Irvine, Information and Computer Science)