期刊
REMOTE SENSING
卷 11, 期 12, 页码 -出版社
MDPI
DOI: 10.3390/rs11121421
关键词
satellite image; thresholding; image segmentation; Harris hawks optimization; mutation mechanism; Kapur's entropy
类别
资金
- Fundamental Research Funds for the Central Universities [2572019BF04]
- National Nature Science Foundation of China [31470714]
- Northeast Forestry University Horizontal Project [43217002, 43217005, 43219002]
- Research Training Project for College Students of Northeast Forestry University
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 efficiently 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.
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