Xiaorui Ma
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Wishart distance-based joint collaborative representation for polarimetric SAR image classification
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Indexed by:期刊论文

Date of Publication:2017-11-01

Journal:IET RADAR SONAR AND NAVIGATION

Included Journals:SCIE、EI、Scopus

Volume:11

Issue:11

Page Number:1620-1628

ISSN No.:1751-8784

Key Words:synthetic aperture radar; radar imaging; image classification; radar polarimetry; statistical analysis; polarimetric synthetic aperture radar; PolSAR; collaborative representation classifier; polarimetric SAR image classification; Wishart distance-based joint collaborative representation

Abstract:Inspired by collaborative representation classifier (CRC), a Wishart distance-based joint CRC (W-JCRC) is proposed for polarimetric synthetic aperture radar (PolSAR) image classification. Since that neighbouring pixels usually belong to the same category with high probability, they can be simultaneously represented via a joint representation model of linear combinations of labelled samples. The joint collaborative representation of neighbouring pixels can overcome the influence of speckle noise at the same time. Considering the statistical property of PolSAR data, a weighted regularisation term with revised Wishart distance is designed to contain the correlations between unlabelled and labelled samples. The coefficients of representation are estimated by an l(2)-norm minimisation derived closed-form solution. In the experiments, three real PolSAR images are applied to evaluate the performance, and the experimental results demonstrate that the proposed method is able to improve classification accuracies compared with other state-of-the-art methods.

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Associate Professor
Supervisor of Master's Candidates

Gender:Female

Alma Mater:Dalian University of Technology

Degree:Doctoral Degree

School/Department:School of Information and Communication Engineering

Discipline:Signal and Information Processing

Business Address:海山楼B513

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