The goal of this paper is to estimate a denoised phase image from the observed noisy SAR interferogram. We proposed a linear model to obtain a sparse representation of the interferomteric phase image. The main idea is based on the smoothness property of the phases inside interferometric fringes which leads to get a sparse image when applying the gradient operator twice, along <i>x</i> or <i>y</i> direction, on the interferogram. The new sparse representation of the interferometric phase image allows to transform the denoising problem to an optimization one. So the estimated interferogram is achieved using the approximate message passing algorithm. The proposed approach is validated on different cases of simulated and real interferograms
Interferometric phase filtering is one of the key steps in interferometric synthetic aperture radar ...
This paper addresses interferometric phase image estimation – that is, the estimation of phase modul...
A novel sparse Bayesian learning approach with a joint sparsity model is proposed for Interferometri...
The goal of this paper is to estimate a denoised phase image from the observed noisy SAR interferogr...
This paper addresses the noise filtering problem for SAR interfero- gram phase images. The phase no...
This paper presents a new filtering technique for SAR interferometric phase images. Due to the prese...
International audienceInterferometric SAR images suffer from a strong noise and their regularization...
The quality of an interferogram, which is limited by various phase noise, will greatly affect the fu...
A high-contrast inpainting scheme based on the Complex Ginzburg-Landau equation recently applied suc...
An interferometric synthetic aperture radar (InSAR) phase denoising algorithm using the local sparsi...
Phase noise reduction is one of the key steps for synthetic aperture radar interferometry data proce...
This paper presents a new filtering approach for Synthetic Aperture Radar (SAR) interferometric phas...
This paper addresses the problem of interferometric phase noise reduction in synthetic aperture rad...
The block-matching 3-D (BM3D) algorithm, based on the nonlocal approach, is one of the most effecti...
SAR interferograms are generally affected by different types of errors. Phase noise in interferometr...
Interferometric phase filtering is one of the key steps in interferometric synthetic aperture radar ...
This paper addresses interferometric phase image estimation – that is, the estimation of phase modul...
A novel sparse Bayesian learning approach with a joint sparsity model is proposed for Interferometri...
The goal of this paper is to estimate a denoised phase image from the observed noisy SAR interferogr...
This paper addresses the noise filtering problem for SAR interfero- gram phase images. The phase no...
This paper presents a new filtering technique for SAR interferometric phase images. Due to the prese...
International audienceInterferometric SAR images suffer from a strong noise and their regularization...
The quality of an interferogram, which is limited by various phase noise, will greatly affect the fu...
A high-contrast inpainting scheme based on the Complex Ginzburg-Landau equation recently applied suc...
An interferometric synthetic aperture radar (InSAR) phase denoising algorithm using the local sparsi...
Phase noise reduction is one of the key steps for synthetic aperture radar interferometry data proce...
This paper presents a new filtering approach for Synthetic Aperture Radar (SAR) interferometric phas...
This paper addresses the problem of interferometric phase noise reduction in synthetic aperture rad...
The block-matching 3-D (BM3D) algorithm, based on the nonlocal approach, is one of the most effecti...
SAR interferograms are generally affected by different types of errors. Phase noise in interferometr...
Interferometric phase filtering is one of the key steps in interferometric synthetic aperture radar ...
This paper addresses interferometric phase image estimation – that is, the estimation of phase modul...
A novel sparse Bayesian learning approach with a joint sparsity model is proposed for Interferometri...