A thumbnail-based hierarchical fuzzy clustering algorithm for SAR image segmentation

Ronghua Shang, Chen Chen, Guangguang Wang, Licheng Jiao, Michael Aggrey Okoth, Rustam Stolkin

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)
253 Downloads (Pure)

Abstract

This paper proposes a novel algorithm for segmentation of synthetic aperture radar (SAR) image, our proposed algorithm (THFCM) is based on thumbnail representations and a hierarchical fuzzy C-means (FCM) approach. THFCM firstly divides the image into pixel groups to extract local feature, and the major pixels of each pixel group are selected to construct a thumbnail. FCM is then used to segment each thumbnail, and hierarchical segmentation is then performed on the overall image data, based on the results of thumbnail clustering. The thumbnail approach leverages local image information, helping to overcome speckle noise, while the hierarchical approach improves computational efficiency. Experiments on simulated and real SAR images suggest that THFCM outperforms several other state-of-the-art algorithms in terms of both segmentation accuracy and running time.
Original languageEnglish
Article number107518
Pages (from-to)1-15
Number of pages15
JournalSignal Processing
Volume171
Early online date2 Feb 2020
DOIs
Publication statusPublished - Jun 2020

Keywords

  • Fuzzy C-means
  • Neighborhood information
  • SAR image segmentation
  • Speckle phenomenon
  • Thumbnail

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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