The method is a modification of Euclid’s blind deconvolution where the multichannel impulse response is estimated by solving an homogeneous system of equations. SMBD can tolerate moderate levels of noise and does not require knowing the source duration. SMBD solves the homogeneous system of equations arising in Euclid deconvolution by imposing sparsity on the multichannel impulse response. To avoid the trivial solution, the sparse reflectivity is constrained to have unit norm. The latter results in non- convex optimization that is solved via a constrained steepest descent technique
International audienceThe ℓ 1 /ℓ 2 ratio regularization function has shown good performance for retr...
A new and different approach to the solution of the normal equations of minimum entropy deconvolutio...
We develop a multilevel approach to solving a blind deconvolution problem, with the ultimate intent ...
We describe a method that allows for blind surface consistent estimation of the source and receiver ...
In this technical report, we show that sparse power factorization (SPF) is an effective solution to ...
We consider linear inverse problems in a nonparametric statistical framework. Both the signal and th...
The paper proposes a method of deconvolution in a periodic setting which combines two important idea...
The paper proposes a method of deconvolution in a periodic setting which combines two important idea...
International audienceIn seismic deconvolution, blind approaches must be considered in situations wh...
We consider the problem of estimating the unknown response function in the multichannel deconvolutio...
We propose an effective method for sparse blind deconvolution (SBD) of ground penetrating radar data...
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvime...
We consider the problem of estimating the unknown response function in the multichannel deconvolutio...
Statistical dependencies among wavelet coefficients are commonly represented by graphical models suc...
This Master Thesis deals with image restoration using deconvolution. The terms introducing into deco...
International audienceThe ℓ 1 /ℓ 2 ratio regularization function has shown good performance for retr...
A new and different approach to the solution of the normal equations of minimum entropy deconvolutio...
We develop a multilevel approach to solving a blind deconvolution problem, with the ultimate intent ...
We describe a method that allows for blind surface consistent estimation of the source and receiver ...
In this technical report, we show that sparse power factorization (SPF) is an effective solution to ...
We consider linear inverse problems in a nonparametric statistical framework. Both the signal and th...
The paper proposes a method of deconvolution in a periodic setting which combines two important idea...
The paper proposes a method of deconvolution in a periodic setting which combines two important idea...
International audienceIn seismic deconvolution, blind approaches must be considered in situations wh...
We consider the problem of estimating the unknown response function in the multichannel deconvolutio...
We propose an effective method for sparse blind deconvolution (SBD) of ground penetrating radar data...
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvime...
We consider the problem of estimating the unknown response function in the multichannel deconvolutio...
Statistical dependencies among wavelet coefficients are commonly represented by graphical models suc...
This Master Thesis deals with image restoration using deconvolution. The terms introducing into deco...
International audienceThe ℓ 1 /ℓ 2 ratio regularization function has shown good performance for retr...
A new and different approach to the solution of the normal equations of minimum entropy deconvolutio...
We develop a multilevel approach to solving a blind deconvolution problem, with the ultimate intent ...