Dynamic Harris hawks optimization with mutation mechanism for satellite image segmentation

Heming Jia, Chunbo Lang, Diego Oliva, Wenlong Song, Xiaoxu Peng

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

In this paper, a novel satellite image segmentation technique based on dynamic Harris hawks optimization with a mutation mechanism (DHHO/M) is proposed. Compared with the original Harris hawks optimization (HHO), the dynamic control parameter strategy and mutation operator used in DHHO/M can avoid falling into the local optimum and effciently enhance the search capability. To evaluate the performance of the proposed method, a series of experiments are carried out on various satellite images. Eight advanced thresholding approaches are selected for comparison. Three criteria are adopted to determine the segmentation thresholds, namely Kapur's entropy, Tsallis entropy, and Otsu between-class variance. Furthermore, four oil pollution images are used to further assess the practicality and feasibility of the proposed method on real engineering problem. The experimental results illustrate that the DHHO/M based thresholding technique is superior to others in the following three aspects: fitness function evaluation, image segmentation effect, and statistical tests.

Original languageEnglish
Article number1421
JournalRemote Sensing
Volume11
Issue number12
DOIs
Publication statusPublished - 1 Jun 2019
Externally publishedYes

Keywords

  • Harris hawks optimization
  • Image segmentation
  • Kapur's entropy
  • Mutation mechanism
  • Satellite image
  • Thresholding

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

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