Image denoising employing local mixture models in sparse domains

IET Image Processing

Volumn 4, Issue 5, 2010, Pages 413-428

  Rabbani, H ^a   Gazor, S ^b  

^a ISFAHAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^b QUEEN S UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COSTS; CONTOURLET TRANSFORM; CURVELET TRANSFORMS; DE-NOISING; DISCRETE COMPLEXES; HEAVY-TAILED; IMAGE COEFFICIENT; IMAGE DE-NOISING; MAP ESTIMATOR; MAXIMUM A POSTERIORI; MINIMUM MEAN SQUARED ERROR; MIXTURE DISTRIBUTIONS; MIXTURE MODEL; MIXTURE PRIORS; NOISE LEVELS; PEAK SIGNAL-TO-NOISE RATIO; SHRINKAGE FUNCTIONS; STATISTICAL DEPENDENCIES; UNIVARIATE; WINDOW SIZE;

DISCRETE WAVELET TRANSFORMS; IMAGE SEGMENTATION; MEAN SQUARE ERROR; MIXTURES; NOISE POLLUTION CONTROL; SIGNAL TO NOISE RATIO;

ESTIMATION;

EID: 77957567729     PISSN: 17519659     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-ipr.2009.0048     Document Type: Article

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