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Optimal Sparse Representation for Blind Deconvolution of Images
Optimal Sparse Representation Blind Deconvolution Images
2010/1/7
The relative Newton algorithm, previously proposed for quasi maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of ima...
Optimal Sparse Representation for Blind Deconvolution of Images
Optimal Sparse Representation Blind Deconvolution Images
2010/1/7
The relative Newton algorithm, previously proposed for quasi maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind deconvolution of ima...
Variational Blind Deconvolution of Multi-Channel Images
image restoration color images kernel estimation variational methods Non-linear PDEs
2010/1/7
The fundamental problem of denoising and deblurring images is addressed in this study. The great difficulty in this task is due to the ill-posedness of the problem. We analyze multi-channel images to ...
Variational Blind Deconvolution of Multi-Channel Images
image restoration color images kernel estimation variational methods Non-linear PDEs
2010/1/7
The fundamental problem of denoising and deblurring images is addressed in this study. The great difficulty in this task is due to the ill-posedness of the problem. We analyze multi-channel images to ...
Blind Deconvolution of Images Using Optimal Sparse Representations
Blind deconvolution quasi-maximum likelihood relative Newton optimization sparse representations
2010/1/7
The relative Newton algorithm, previously proposed for quasi-maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind
deconvolution of im...
Blind Deconvolution of Images Using Optimal Sparse Representations
Blind deconvolution quasi-maximum likelihood relative Newton optimization sparse representations
2010/1/7
The relative Newton algorithm, previously proposed for quasi-maximum likelihood blind source separation and blind deconvolution of one-dimensional signals is generalized for blind
deconvolution of im...
Blind deconvolution is considered as a problem of quasi maximum likelihood (QML) estimation of the restoration kernel. Simple closed-form expressions for the asymptotic estimation error are derived. T...
Blind deconvolution is considered as a problem of quasi maximum likelihood (QML) estimation of the restoration kernel. Simple closed-form expressions for the asymptotic estimation error are derived. T...
Phase Unwrapping for 2-D Blind Deconvolution of Ultrasound Images
Phase unwrapping Poisson equation multiresolution
2010/1/6
In most approaches to the problem of two-dimensional
homomorphic deconvolution of ultrasound images, the estimation
of a corresponding point-spread function (PSF) is necessarily
the first stage in ...
Blind Deconvolution of Ultrasound Sequences Using Nonparametric Local Polynomial Estimates of the Pulse
Blind deconvolution pulse estimation ultrasound
2010/1/6
The problem of reconstructing the reflectivity of a
biological tissue is examined by means of blind deconvolution of
the echo ultrasound signals. It is shown that the quality of the
reconstruction ...
Modeling circadian rhythms of food intake by means of parametric deconvolution: results from studies of the night eating syndrome
Modeling circadian rhythms food intake
2016/12/30
Disordered temporal eating patterns are a feature of a number of eating disorders. There is currently no standard mathematical model to quantify temporal eating patterns.