Bayesian wavelet-based image deconvolution: A GEM algorithm exploiting a class of heavy-tailed priors

IEEE Transactions on Image Processing

Volumn 15, Issue 4, 2006, Pages 937-951

  Bioucas Dias, José M ^a  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

Bayesian; Deconvolution; Expectation maximization (EM); Gaussian scale mixtures (GSM); Generalized expectation maximization (GEM); Heavy tailed priors; Wavelet

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; ITERATIVE METHODS; PROBABILITY DISTRIBUTIONS; STATISTICAL METHODS; WAVELET TRANSFORMS;

EXPECTATION MAXIMIZATION (EM); GAUSSIAN SCALE MIXTURES (GSM); GENERALIZED EXPECTATION MAXIMIZATION (GEM); HEAVY-TAILED PRIORS; IMAGE DECONVOLUTION;

IMAGE PROCESSING;

ALGORITHM; ARTICLE; BAYES THEOREM; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; MATHEMATICAL COMPUTING; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; STATISTICAL MODEL;

ALGORITHMS; BAYES THEOREM; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFORMATION STORAGE AND RETRIEVAL; MODELS, STATISTICAL; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 33645136947     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2005.863972     Document Type: Article

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