A fast GEM algorithm for Bayesian wavelet-based image restoration using a class of heavy-tailed priors

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2683, Issue , 2003, Pages 407-420

  Bioucas Dias, José M ^a  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTER VISION; DECONVOLUTION; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); IMAGE RECONSTRUCTION; ITERATIVE METHODS; MAXIMUM PRINCIPLE; PATTERN RECOGNITION; TURBO CODES; WAVELET ANALYSIS; WAVELET DECOMPOSITION; WHITE NOISE;

ADDITIVE WHITE GAUSSIAN NOISE; GAUSSIAN DENSITY; GENERALIZED EXPECTATIONMAXIMIZATION ALGORITHM (GEM); LOW COMPUTATIONAL COMPLEXITY; MAXIMUM A POSTERIORI; STATE-OF-THE-ART METHODS; WAVELET COEFFICIENTS; WAVELET-BASED IMAGES;

ALGORITHMS;

EID: 35248884304     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-45063-4_26     Document Type: Article

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