Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis

ZHANG Han; NI Weiping; YAN Weidong; BIAN Hui; WU Junzheng; LI Sha; JIN Xiao

doi:10.13203/j.whugis20140375

Volume 41 Issue 5

May 2016

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Geomatics and Information Science of Wuhan University > 2016 > 41(5): 642-648. > DOI: 10.13203/j.whugis20140375

ZHANG Han, NI Weiping, YAN Weidong, BIAN Hui, WU Junzheng, LI Sha, JIN Xiao. Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis[J]. Geomatics and Information Science of Wuhan University, 2016, 41(5): 642-648. DOI: 10.13203/j.whugis20140375

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Mid and Low Resolution SAR Image Change Detection Based on Fractal and Multi-scale Analysis

1.
Northwest Institute of Nuclear Technology, Xi'an 710024, China;
2.
School of Electronic Engineering, Xidian University, Xi'an 710071, China;
3.
Shenyang Artillery Academy, Shenyang 110161, China

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Received Date: September 14, 2014
Published Date: May 04, 2016

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Abstract

For pixel based SAR image change detection, the discrepancy images produced by the log ratio operation or Kullback-Leibler divergence cannot achieve satisfactory results in artificial target change detection. We introduce a fractal dimension into the construction of discrepancy images and define the Fractal Dimension-Log Ratio (FD-LR) image capable of detecting changes both from the natural targets and the artificial targets. A Gaussian mixture distribution is used to model the statistical properties of FD-LR. The Bayesian principle with expectation maximization-based parameter estimation is conducted to perform unsupervised thresholding on the FD-LR. To reduce speckle interferences , multiscale analysis and data fusion in the decision step are performed. Comparative experiments confirm the effectiveness of the proposed approach.
- SAR image,
- change detection,
- fractal dimension,
- multiscale analysis

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