Bayesian inference for inverse problems in signal and image processing and applications

International Journal of Imaging Systems and Technology

Volumn 16, Issue 5, 2006, Pages 209-214

  Mohammad Djafari, Ali ^a  

^a CNRS   (France)

Author keywords

Bayesian estimation; Blind source separation; Computed tomography; Data and image fusion; Deconvolution; Image restoration; Inverse problems

Indexed keywords

BLIND SOURCE SEPARATION; COMPUTERIZED TOMOGRAPHY; IMAGE FUSION; IMAGE RECONSTRUCTION; INVERSE PROBLEMS; PROBABILITY;

BAYESIAN ESTIMATION; BAYESIAN INFERENCE; SIGNAL DECONVOLUTION;

DIGITAL SIGNAL PROCESSING;

EID: 34247146738     PISSN: 08999457     EISSN: 10981098     Source Type: Journal    
DOI: 10.1002/ima.20081     Document Type: Conference Paper

References (5)

1. P. Brault and A. Mohammad-Djafari, Bayesian segmentation and motion estimation in video sequences using a Markov-Potts model, presented at WSEAS04, 2004.
2. O. Féron and A. Mohammad-Djafari, Image fusion and joint segmentation using an MCMC algorithm, Journal of Electronic Imaging 2004.
3. A. Mohammad-Djafari, "Bayesian approach for inverse problems in optics". Presented at SPIE, Optical Information Systems, August 2003, San Diego, CA.
4. H. Snoussi and A. Mohammad-Djafari, Fast joint separation and segmentation of mixed images, Journal of Electronic Imaging 13(2004), 349-361.
5. H. Snoussi and A. Mohammad-Djafari, Information geometry and prior selection, In Bayesian Inference and Maximum Entropy Methods, Proc of MaxEnt Workshops, American Institute of Physics, 569 (2002), 307-327.