A fast majorize-minimize algorithm for the recovery of sparse and low-rank matrices

IEEE Transactions on Image Processing

Volumn 21, Issue 2, 2012, Pages 742-753

  Hu, Yue ^a   Lingala, Sajan Goud ^b   Jacob, Mathews ^b  

^a University of Rochester   (United States)

^b IA United States   (United States)

Author keywords

Dynamic magnetic resonance imaging (MRI); low rank; majorize minimize; matrix recovery; sparse

Indexed keywords

DYNAMIC MAGNETIC RESONANCE IMAGING (MRI); LOW RANK; MAJORIZE MINIMIZE; MATRIX RECOVERY; SPARSE;

ALGORITHMS; IMAGE QUALITY; MATRIX ALGEBRA; RECOVERY; SIGNAL TO NOISE RATIO;

MAGNETIC RESONANCE IMAGING;

ALGORITHM; ARTICLE; BRAIN; FOURIER ANALYSIS; HISTOLOGY; HUMAN; IMAGE PROCESSING; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; SIGNAL NOISE RATIO;

ALGORITHMS; BRAIN; FOURIER ANALYSIS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; SIGNAL-TO-NOISE RATIO;

EID: 84856263456     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2011.2165552     Document Type: Article

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