Reconstruction of Binary function from Incomplete Frequency Information

Applied and Computational Mathematics Seminar
Monday, January 30, 2012 - 2:00pm
1 hour (actually 50 minutes)
Skiles 006
Institute for Mathematics and Its Applications (IMA) at University of Minnesota
Binary function is a class of important function that appears in  many applications e.g. image segmentation, bar code recognition, shape  detection and so on. Most studies on reconstruction of binary function are based on the nonconvex double-well potential or total variation. In this research we proved that under certain conditions the binary function can be reconstructed from incomplete frequency information by using only simple linear programming, which is far more efficient.