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A New SAR Image Segmentation Algorithm for the Detection of Target and Shadow Regions.

Shiqi Huang1, Wenzhun Huang1, Ting Zhang1

  • 1Department of Electronic Information Engineering, Xijing University, Xi'an, 710123, China.

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|December 8, 2016
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Summary
This summary is machine-generated.

This study introduces a new wavelet decomposition and constant false alarm rate (WD-CFAR) algorithm for segmenting synthetic aperture radar (SAR) images. The WD-CFAR method effectively reduces speckle noise, enabling accurate segmentation of targets and shadows, even in low signal-to-clutter ratio conditions.

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Area of Science:

  • Remote Sensing
  • Image Processing
  • Signal Processing

Background:

  • Synthetic Aperture Radar (SAR) provides all-weather, all-time data acquisition capabilities.
  • SAR imaging mechanisms inherently introduce speckle noise, complicating image segmentation.
  • Accurate segmentation of target and shadow regions in SAR imagery is challenging due to noise.

Purpose of the Study:

  • To develop a novel SAR image segmentation method robust to speckle noise.
  • To enable simultaneous segmentation of target and shadow regions.
  • To improve segmentation performance in low signal-to-clutter ratio (SCR) environments.

Main Methods:

  • The proposed method utilizes wavelet decomposition for noise reduction.
  • A constant false alarm rate (CFAR) algorithm is integrated for enhanced segmentation.
  • The combined Wavelet Decomposition-Constant False Alarm Rate (WD-CFAR) algorithm is applied.

Main Results:

  • The WD-CFAR algorithm demonstrates insensitivity to speckle noise in SAR images.
  • Simultaneous segmentation of target and shadow regions was achieved.
  • Effective segmentation was observed even with low signal-to-clutter ratios (SCR).

Conclusions:

  • The proposed WD-CFAR method is effective and feasible for SAR image segmentation.
  • The algorithm exhibits good general applicability across various SAR images.
  • This approach offers a significant improvement for challenging SAR image analysis tasks.