Results 171 to 180 of about 25,862 (211)

MRF-Based Blind Image Deconvolution

2013
This paper proposes an optimization-based blind image deconvolution method. The proposed method relies on imposing a discrete MRF prior on the deconvolved image. The use of such a prior leads to a very efficient and powerful deconvolution algorithm that carefully combines advanced optimization techniques. We demonstrate the extreme effectiveness of our
Komodakis, Nikos, Paragios, Nikos
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Sparse multichannel blind deconvolution

GEOPHYSICS, 2014
We developed a sparse multichannel blind deconvolution (SMBD) method. The method is a modification of the multichannel blind deconvolution technique often called Euclid deconvolution, in which the multichannel impulse response of the earth is estimated by solving an homogeneous system of equations.
Nasser Kazemi, Mauricio D. Sacchi
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Multichannel blind image deconvolution

Proceedings of 2012 9th International Bhurban Conference on Applied Sciences & Technology (IBCAST), 2012
A new method has been proposed for performing multichannel blind image deconvolution. We consider the image deconvolution problem when limited information about the Point Spread Function (PSF) is available and the original image is of sparse nature. It is assumed that the original image is corrupted by a degradation function (i.e.
Umer Javed, Muhammad Mohsin Riaz, null Tanveer Ahmad Cheema   +2 more
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Blind Image Deconvolution

2017
BLIND IMAGE DECONVOLUTION: PROBLEM FORMULATION AND EXISTING APPROACHES Tom E. Bishop, S. Derin Babacan, Bruno Amizic, Aggelos K. Katsaggelos, Tony Chan, and Rafael Molina Introduction Mathematical Problem Formulation Classification of Blind Image Deconvolution Methodologies Bayesian Framework for Blind Image Deconvolution Bayesian Modeling of Blind ...
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Blind deconvolution using temporal predictability

Neurocomputing, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Projection-based blind deconvolution

Journal of the Optical Society of America A, 1994
We present a new projection-based algorithm for solving the classical blind-deconvolution problem. In our approach all known a priori information about both the unknown source and the blurring functions is expressed through constraint sets. In computer simulations the algorithm performed well even when the prior information was not accurate. To see how
Yongyi Yang, Nikolas P. Galatsanos, Henry Stark   +2 more
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Blind deconvolution under band limitation

Optics Letters, 2003
A blind deconvolution problem is newly stated with the following conditions: the point-spread function is band limited, both the object and the point-spread function are nonnegative, and the solution is to be a diffraction-limited object. A blind deconvolution method was developed that can easily be applied to problems in optics because of the ...
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Blind Deconvolution

Digital Signal Processing, 1995
J.A. Cadzow, X.K. Li
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Sparsity-Based Blind Deconvolution

2014
In the previous chapters our focus was on overcoming the tendency of joint MAP estimator to give trivial solutions by choosing an appropriate PSF regularizer and the regularization factor, and the convergence analysis of the resulting optimization problem.
Subhasis Chaudhuri, Rajbabu Velmurugan, Renu Rameshan   +2 more
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Iteratively reweighted blind deconvolution

2013 IEEE International Conference on Image Processing, 2013
Traditional blind deconvolution techniques rely on a statistical model that relates the measured data to the pristine scene whose reconstruction is sought. If the data is not consistent with this forward model, then the reconstruction is badly degraded.
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