Unsupervised classification for hybrid polarimetric SAR data based on scattering mechanisms and Wishart classifier. Issue 19 (2nd September 2015)

• Record Type: Journal Article
• Authors: Chen, Shiqiang; Guo, Shenglong; Li, Yang; Hong, Wen
• Is Part Of: Electronics letters. Volume 51:Issue 19(2015)
• Page Start: 1530
• Page End: 1532
• Publication Date: 2015-09-02
• Subjects: synthetic aperture radar; hybrid polarimetric SAR data -- Wishart classifier -- unsupervised classification algorithm -- polarimetric scattering mechanisms -- PSM -- hybrid polarity data -- initial scattering categories -- roll‐invariant m‐χ classification algorithm -- San Francisco; Electronics -- Periodicals; 621.381
• DOI: 10.1049/el.2015.1627
• Languages: English
• ISSNs: 0013-5194

Abstract

Abstract : An unsupervised classification algorithm utilising both polarimetric scattering mechanisms (PSMs) of hybrid‐polarity data and the Wishart classifier is proposed. The initial scattering categories of the proposed algorithm are derived from the roll‐invariant m – χ classification algorithm. Pixels with no clearly defined dominant PSM are excluded, and the resulting categories are expanded into a specified number of classes. These derived classes are taken as training samples of the Wishart classifier. The effectiveness of the proposed algorithm is validated with the dataset over San Francisco.