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TA-L6: Signal/Image Reconstruction from Sparse Measurements

Session Type: Invited Lecture

Time: Tuesday, October 10, 09:40 - 12:40

Location: Marquis III

Chair: Pier Luigi Dragotti, Imperial College, UK

TA-L6.1: ROBUST KERNEL REGRESSION FOR RESTORATION AND RECONSTRUCTION OF IMAGES FROM SPARSE NOISY DATA

Hiroyuki Takeda; University of California, Santa Cruz

Sina Farsiu; University of California, Santa Cruz

Peyman Milanfar; University of California, Santa Cruz

TA-L6.2: SPARSE IMAGE RECONSTRUCTION USING SPARSE PRIORS

Michael Ting; University of Michigan

Raviv Raich; University of Michigan

Alfred Hero; University of Michigan

TA-L6.3: MULTICHANNEL SAMPLING OF PARAMETRIC SIGNALS WITH A SUCCESSIVE APPROXIMATION PROPERTY

Julius Kusuma; Massachusetts Institute of Technology

Vivek Goyal; Massachusetts Institute of Technology

TA-L6.4: COMPRESSIVE SAMPLING VS. CONVENTIONAL IMAGING

Jarvis Haupt; University of Wisconsin-Madison

Robert Nowak; University of Wisconsin-Madison

TA-L6.5: AN ARCHITECTURE FOR COMPRESSIVE IMAGING

Michael Wakin; Rice University

Jason Laska; Rice University

Marco Duarte; Rice University

Dror Baron; Rice University

Shriram Sarvotham; Rice University

Dharmpal Takhar; Rice University

Kevin Kelly; Rice University

Richard Baraniuk; Rice University

TA-L6.6: TREE-BASED ORTHOGONAL MATCHING PURSUIT ALGORITHM FOR SIGNAL RECONSTRUCTION

Chinh La; University of Illinois at Urbana-Champaign

Minh Do; University of Illinois at Urbana-Champaign

TA-L6.7: ROBUST SIGNAL RECOVERY FROM INCOMPLETE OBSERVATIONS

Emmanuel Candes; California Institute of Technology

Justin Romberg; California Institute of Technology

TA-L6.8: EXACT LOCAL RECONSTRUCTION ALGORITHMS FOR SIGNALS WITH FINITE RATE OF INNOVATION

Pier Luigi Dragotti; Imperial College London

Martin Vetterli; Swiss Federal Institute of Technology

Thierry Blu; Swiss Federal Institute of Technology