Learning sparse representations to restore, classify, and sense images and videos Guillermo Sapiro University of Minnesota Supported by NSF, NGA, NIH,
The K–SVD Design of Dictionaries for Redundant and Sparse Representation of Signals Michael Elad The Computer Science Department The Technion – Israel.
Sparse and Overcomplete Data Representation Michael Elad The CS Department The Technion – Israel Institute of technology Haifa 32000, Israel Israel Statistical.
Sparse & Redundant Signal Representation and its Role in Image Processing Michael Elad The Computer Science Department The Technion – Israel Institute.
Recent Trends in Signal Representations and Their Role in Image Processing Michael Elad The CS Department The Technion – Israel Institute of technology.
A Weighted Average of Sparse Several Representations is Better than the Sparsest One Alone Michael Elad The Computer Science Department The Technion –
Sparse and Redundant Representation Modeling for Image Processing Michael Elad The Computer Science Department The Technion – Israel Institute of technology.
