Gaussian-Hermite moments algorithm for SAR image segmentation

Li Sun, Yanning Zhang, Ying Li, Miao Ma

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

SAR image segmentation is one of the most important tasks on SAR image processing. But the multiplication nature of the speckle noise in SAR images has been a troublesome problem in SAR images. In this paper, a SAR image segmentation approach based on Gaussian-Hermite moments is proposed. Because Gaussian-Hermite moments can better separate image features and enhance the object based on different modes. Different orders of Gaussian-Hermite moments are made use of as image features to extract objects from background scene. We use the even order moments equivalent to a filter to perform the segmentation in SAR image. The proposed algorithm is compared with other four algorithms on real SAR images (Figure 4) and simulation images (Figure 3). Experimental results show that the proposed method is effective to extract objects from background scene in SAR image and to restrain the speckle noise.

Original languageEnglish
Pages (from-to)438-441
Number of pages4
JournalXibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
Volume25
Issue number3
StatePublished - Jun 2007

Keywords

  • Gaussian-Hermite moment
  • Image segmentation
  • SAR (Synthetic Aperture Radar)

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