Buildings Extraction from Polarimetric SAR Image Using Improved Three-component Decomposition and Wishart Classification

  • LIU Xiuguo ,
  • JIANG Ping ,
  • CHEN Qihao ,
  • CHEN Qi
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  • College of Information Engineering, China University of Geosciences, Wuhan 430074, China

Received date: 2013-12-09

  Revised date: 2014-06-18

  Online published: 2015-02-14

Supported by

The National Natural Science Foundation of China (Nos. 41301477;41471355);China Postdoctoral Science Foundation(No. 2012M521497);Wuhan Academic Leaders Plan Funded Projects (No. 201271130443)

Abstract

To address the misclassification issue on buildings extraction based on Freeman decomposition method, a novel improved three-component decomposition model is proposed in this paper. By combining the selective de-orientation derived from the circular polarization correlation coefficient method with the generalized volume scattering model, it can accurately characterize the scattering characteristics of surface features. On this basis, the complex Wishart iterative classification is introduced to develop a new method of buildings extraction. An E-SAR L band polarimetric SAR image was used to verify the effectiveness of this modified algorithm. The experiment result shows it could perform better in distinguishing between oblique buildings and forest, and consequently improve the accuracy of buildings extraction.

Cite this article

LIU Xiuguo , JIANG Ping , CHEN Qihao , CHEN Qi . Buildings Extraction from Polarimetric SAR Image Using Improved Three-component Decomposition and Wishart Classification[J]. Acta Geodaetica et Cartographica Sinica, 2015 , 44(2) : 206 -213 . DOI: 10.11947/j.AGCS.2015.20130535

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