Recent Results on the Co-Sparse Analysis Model
December 7th, 2012
NIPS, Lake Tahoe

In this talk we describe the co-sparse analysis model, with emphasis on pursuit algorithms and dictionary learning for it. We present two of our recent activities on this subject: (i) A theoretical study of the Analysis-Thresholding algorithm, exposing measures of goodness for the dictionary that govern the pursuit performance; and (ii) The development of an analysis K-SVD algorithm that trains a dictionary from signal examples and its use for image denoising.

This is a joint work with Tomer Peleg and Ron Rubinstein. This talk was given as an invited talk in the workshop "Analysis Operator Learning vs. Dictionary Learning: Fraternal Twins in Sparse Modeling"