Bayesian wavelet-based image deconvolution: a GEM algorithm exploiting a class of heavy-tailed priors - Bioucas-Dias, J.M. (IEEE transactions on image processing, 2006)
Keywords: Algorithms; Applied sciences; Bayes Theorem; Bayesian; Bayesian analysis; Bayesian methods; Computational complexity; Computer Simulation; Deconvolution; Density; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; expectation maximization (EM); Gaussian; Gaussian scale mixtures (GSM); generalized expectation maximization (GEM); GSM; heavy-tailed priors; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Information Storage and Retrieval - methods; Information, signal and communications theory; Iterative algorithms; Mathematical analysis; Mathematical models; Maximization; Maximum a posteriori estimation; Miscellaneous; Models, Statistical; Noise reduction; Numerical Analysis, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal Processing, Computer-Assisted; Signal representation. Spectral analysis; Signal, noise; Studies; Sufficient conditions; Telecommunications and information theory; wavelet; Wavelet coefficients; Wavelet domain; Performance evaluation; Second order; State of the art; Image processing; Necessary and sufficient condition; Threshold detection; Noise reduction; Wireless telecommunication; Iterative method; expectation maximization (EM); A posteriori estimation; Gaussian scale mixtures (GSM); Bayes estimation; Mobile radiocommunication; GSM system; Bayesian; heavy-tailed priors; Scale factor; Computational complexity; Wavelets; deconvolution; Gaussian process; Wavelet transformation; generalized expectation maximization (GEM); Signal processing; wavelet; EM algorithm; Signal analysis