• Speeding Up Non-Gaussian POLSAR Image Analysis 

      Doulgeris, Anthony Paul; Hu, Dingsheng (Journal article; Peer reviewed, 2017-12-04)
      Non-Gaussian statistical models fit SAR data better than Gaussian-based statistics, in most cases, but are complicated and time-consuming to use for unsupervised image segmentation via probabilistic clustering. The more advanced the model, the more complicated and slow the clustering. The U-distribution has been demonstrated to be one of the most flexible models, capturing the Gaussian/Wishart, the ...
    • Unsupervised Estimation of the Equivalent Number of Looks in PolSAR Image with High Heterogeneity 

      Hu, Dingsheng; Qiu, Xiaolan; Anfinsen, Stian Normann; Lei, Bin (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-03-01)
      Equivalent Number of Looks (ENL) is an important parameter in statistical modelling of multi-look Polarimetric SAR (PolSAR) data. In some automated applications of PolSAR images, it is necessary to estimate the ENL in an unsupervised way without any manual intervention. The existing unsupervised estimation of ENL can not obtain accurate estimates for the images with high heterogeneity. To address ...
    • An unsupervised method for equivalent number of looks estimation in complex SAR scenes 

      Hu, Dingsheng; Doulgeris, Anthony Paul; Qiu, Xiaolan (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-11-12)
      This paper introduces a novel unsupervised estimator of equivalent number of looks (ENL) that can be applied to an arbitrary image. It avoids the assumption that homogeneous speckle will dominate the investigated image that is followed by current unsupervised ENL estimators but not always valid, especially for the complex SAR scenes with high mixture and texture. Incorporating the statistical ...
    • Unsupervised Mixture-Eliminating Estimation of Equivalent Number of Looks for PolSAR Data 

      Hu, Dingsheng; Anfinsen, Stian Normann; Qiu, X; Doulgeris, Anthony Paul; Lei, Bin (Journal article; Tidsskriftartikkel; Peer reviewed, 2017-08-22)
      This paper addresses the impact of mixtures between classes on equivalent number of looks (ENL) estimation. We propose an unsupervised ENL estimator for polarimetric synthetic aperture radar (PolSAR) data, which is based on small sample estimates but incorporates a mixture-eliminating (ME) procedure to automatically assess the uniformity of the estimation windows. A statistical feature derived from ...