RASL: Robust alignment by sparse and low-rank decomposition for linearly correlated images

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 34, Issue 11, 2012, Pages 2233-2246

  Peng, Yigang ^a   Ganesh, Arvind ^b   Wright, John ^c   Xu, Wenli ^a   Ma, Yi ^b  

^a TSINGHUA UNIVERSITY   (China)

^b UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

^c Columbia University ^*  (United States)

Author keywords

Batch image alignment; low rank matrix; occlusion and corruption; robust principal component analysis; sparse errors

Indexed keywords

ALIGNED IMAGES; ALIGNMENT ALGORITHMS; CONVEX OPTIMIZATION TECHNIQUES; CONVEX PROGRAMS; IMAGE ALIGNMENT; IMAGE DOMAIN; LOW-RANK DECOMPOSITION; LOW-RANK MATRICES; OCCLUSION AND CORRUPTION; OPTIMAL SETS; OPTIMIZATION PROBLEMS; ROBUST PRINCIPAL COMPONENT ANALYSIS; SPARSE MATRICES; TWO-COMPONENT;

ALIGNMENT; CRIME; ERRORS; OPTIMIZATION; PRINCIPAL COMPONENT ANALYSIS;

LINEAR TRANSFORMATIONS;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; STATISTICS; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFACTS; ARTIFICIAL INTELLIGENCE; IMAGE ENHANCEMENT; IMAGING, THREE-DIMENSIONAL; LINEAR MODELS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; STATISTICS AS TOPIC; SUBTRACTION TECHNIQUE;

MLCS; MLOWN;

EID: 84866665730     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2011.282     Document Type: Article

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