Majorization-Minimization Algorithms for Wavelet-Based Image Restoration

Standard formulations of image/signal deconvolution under wavelet-based priors/regularizers lead to very high-dimensional optimization problems involving the following difficulties: the non-Gaussian (heavy-tailed) wavelet priors lead to objective functions which are nonquadratic, usually nondifferen...

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Bibliographic Details
Published in:	IEEE transactions on image processing Vol. 16; no. 12; pp. 2980 - 2991
Main Authors:	Figueiredo, M.A.T., Bioucas-Dias, J.M., Nowak, R.D.
Format:	Journal Article
Language:	English
Published:	New York, NY IEEE 01.12.2007 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Applied sciences Computational efficiency Convergence of numerical methods Convolution Deconvolution Detection, estimation, filtering, equalization, prediction Exact sciences and technology Image deconvolution Image denoising Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image processing Image restoration Information Storage and Retrieval - methods Information, signal and communications theory Iterative algorithms majorization-minimization (MM) algorithms Materials handling Mathematical models Miscellaneous Noise reduction Numerical Analysis, Computer-Assisted Optimization Optimization methods Pattern Recognition, Automated - methods regularization Reproducibility of Results Sensitivity and Specificity Signal and communications theory Signal processing Signal Processing, Computer-Assisted Signal, noise Studies Telecommunications Telecommunications and information theory wavelets Image deconvolution image restoration optimization majorization-minimization (MM) algorithms regularization wavelets Performance evaluation Singularity Separability Image processing Noise reduction Iterative method Image restoration Algorithm Optimization Convolution Wavelet transformation Least squares method Signal processing Objective function Numerical convergence
ISSN:	1057-7149, 1941-0042
Online Access:	Get full text
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