Research Papers

Multifeature fusion for polarimetric synthetic aperture radar image classification of sea ice

[+] Author Affiliations
Hao Guo

Dalian Maritime University, Information Science and Technology College, No. 1 Linghai Street, Dalian 116026, China

Qing Fan

Dalian Maritime University, Information Science and Technology College, No. 1 Linghai Street, Dalian 116026, China

Xi Zhang

State Oceanic Administration of China, The First Institute of Oceanography, No. 6 Xianxialing Street, Qingdao 266061, China

Jubai An

Dalian Maritime University, Information Science and Technology College, No. 1 Linghai Street, Dalian 116026, China

J. Appl. Remote Sens. 8(1), 083534 (Nov 03, 2014). doi:10.1117/1.JRS.8.083534
History: Received July 25, 2014; Revised September 15, 2014; Accepted September 29, 2014
Text Size: A A A

Abstract.  Sea ice conditions are so heterogeneous, and the differences between the different ice types are less varied than that of land targets, so only using polarimetric or textural features would lead to misclassification of polarimetric synthetic aperture radar (PolSAR) data of sea ice. To support the identification of different ice types, the fusion of textural and polarimetric features would be a good solution. Simple discrimination analysis is used to rationalize a preferred features subset. Some features are analyzed, which include entropy H/alphaα/anisotropyA and three kinds of texture statistics (entropy, contrast, and correlation), in the C- and L-band polarimetric mode. After that, a multiobjective fuzzy decision model is proposed for supervised PolSAR data classification of sea ice, and the targets are categorized according to the principle of maximum membership grade. In consideration of the interference of the correlation among features, the model is based on Mahalanobis distance in which the covariances between the selected heterogeneous features could restrain the interference among redundant features. In the end, the effectiveness of the algorithm for PolSAR image classification of sea ice is demonstrated through the analysis of some experimental results.

© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Hao Guo ; Qing Fan ; Xi Zhang and Jubai An
"Multifeature fusion for polarimetric synthetic aperture radar image classification of sea ice", J. Appl. Remote Sens. 8(1), 083534 (Nov 03, 2014). ; http://dx.doi.org/10.1117/1.JRS.8.083534


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Proceedings Articles

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.