Image and Signal Processing using Sparse Optimization, A Few Recent Results

Monday, March 7, 2011 - 11:00am - 12:00pm
Keller 3-180
Wotao Yin (Rice University)
This talk overviews a few viable sparse optimization algorithms such as variable splitting L1/TV minimization, compressive sensing edge detection, nonnegative matrix factorization, and Beta-process based Bayesian learning. They allow us to take advantages of structures in both the model and the data to produce state-of-the-art results.

Imaging examples such as edge detection, image deblurring and denoising, MRI reconstruction, background subtraction, as well as hyperspectral image processing will be given.