Add to ORKGThe results of texture estimation in SAR images depend on image scale and model order being employed in Gauss Markov Random Field modeling
The despeckling of SAR images can be done by non-quadratic regularization and a Gauss Markov random ...
Abstract- Tools are required to assist the identification of pertinent classes in SAR sea ice imager...
A method for the analysis of spatial statistics in multifrequency polarimetric Synthetic Aperture Ra...
The structure and texture contained in SAR images can be modeled by complex-valued Gauss-Markov ran...
High resolution SAR images show specific characteristics that can be exploited for texture modeling ...
Synthetic Aperture Radar (SAR) is a powerful signal processing system that finds its application in ...
Speckle hinders information in synthetic aperture radar (SAR) images and makes automatic information...
The despeckling of SAR images can be performed based on models. Gibbs random field models lend thems...
The underlying aim of this research is to investigate the mathematical descriptions of homogeneous t...
We describe a technique for using the joint occurrence of local features at multiple resolutions to ...
Tools are required to assist the identification of pertinent classes in SAR sea ice imagery. Texture...
Abstract—The paper presents two algorithms for texture primitive feature extraction on Single Look C...
The performance of despeckling algorithms for SAR images can be assessed by Cramer-Rao bound calcula...
In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aper...
A novel Markov-random-field model for speckled synthetic aperture radar (SAR) imagery is derived acc...
The despeckling of SAR images can be done by non-quadratic regularization and a Gauss Markov random ...
Abstract- Tools are required to assist the identification of pertinent classes in SAR sea ice imager...
A method for the analysis of spatial statistics in multifrequency polarimetric Synthetic Aperture Ra...
The structure and texture contained in SAR images can be modeled by complex-valued Gauss-Markov ran...
High resolution SAR images show specific characteristics that can be exploited for texture modeling ...
Synthetic Aperture Radar (SAR) is a powerful signal processing system that finds its application in ...
Speckle hinders information in synthetic aperture radar (SAR) images and makes automatic information...
The despeckling of SAR images can be performed based on models. Gibbs random field models lend thems...
The underlying aim of this research is to investigate the mathematical descriptions of homogeneous t...
We describe a technique for using the joint occurrence of local features at multiple resolutions to ...
Tools are required to assist the identification of pertinent classes in SAR sea ice imagery. Texture...
Abstract—The paper presents two algorithms for texture primitive feature extraction on Single Look C...
The performance of despeckling algorithms for SAR images can be assessed by Cramer-Rao bound calcula...
In this work the G(A)(0) distribution is assumed as the universal model for amplitude Synthetic Aper...
A novel Markov-random-field model for speckled synthetic aperture radar (SAR) imagery is derived acc...
The despeckling of SAR images can be done by non-quadratic regularization and a Gauss Markov random ...
Abstract- Tools are required to assist the identification of pertinent classes in SAR sea ice imager...
A method for the analysis of spatial statistics in multifrequency polarimetric Synthetic Aperture Ra...