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SAR Image Change Detection Method Based on Pulse-Coupled Neural Network

  • Rui Liu
  • Zhenhong Jia
  • Xizhong Qin
  • Jie Yang
  • Nikola Kasabov
Short Note

Abstract

The study proposes a new algorithm for change detection of SAR images based on segmentation to improve the accuracy of the SAR image change detection. The ratio method is used to acquire the difference image (DI). Then, the global dictionary is applied to address the image denoising problem. Finally, change mask is obtained by pulse-coupled neural network (PCNN). The results of the experiment show that the proposed method improves accuracy.

Keywords

Change detection Remote sensing image Global dictionary Pulse-coupled neural network (PCNN) 

Notes

Acknowledgments

This work was supported in part by International Cooperative Research and Personnel Training Projects of the Ministry of the Ministry of Education of the People’s Republic of China [Grant number DICE2014-2029].

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Copyright information

© Indian Society of Remote Sensing 2016

Authors and Affiliations

  • Rui Liu
    • 1
  • Zhenhong Jia
    • 1
  • Xizhong Qin
    • 1
  • Jie Yang
    • 2
  • Nikola Kasabov
    • 3
  1. 1.College of Information Science and EngineeringXinjiang UniversityUrumqiChina
  2. 2.Institute of Image Processing and Pattern RecognitionShanghai Jiao Tong UniversityShanghaiChina
  3. 3.Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyAucklandNew Zealand

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