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Slide Show

Atlanta Conv. & Vis. Bureau
 

TA-L6: Signal/Image Reconstruction from Sparse Measurements

Session Type: Special 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
 
IEEE Signal Processing Society

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