Abstract
(Dis)similarity measures play an important role in the interpretation of polarimetric synthetic aperture radar (PolSAR) images. Here, the authors introduce a kind of similarity measures for PolSAR images based on the concepts of Holder pseudo-divergence and Holder divergence. Authors’ similarity measures are more generalised as the derived formulas indicate that they contain several widely used measures, such as Bartlett or Bhattahcharyya distances and Chernoff distance. Also, their similarity measures are derived from the complex Wishart distribution, so these measures are good at quantifying the similarity between two covariance matrices and perform well while dealing with classification problems for PolSAR images. Experimental results on unsupervised and supervised classification of PolSAR images also verify the effectiveness of their measures.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
