Acta Optica Sinica, Volume. 36, Issue 5, 511002(2016)

Sea Sky Line Detection Method of Unmanned Surface Vehicle Based on Gradient Saliency

Wang Bo*, Su Yumin, Wan Lei, Zhuang Jiayuan, and Zhang Lei
Author Affiliations
  • [in Chinese]
  • show less

    Unmanned surface vehicle (USV) plays a more and more important role in various areas such as meteorological monitoring, maritime search and rescue, enemy reconnaissance, and precision strike. However, special features in real marine environment such as cloud clutter, sea glint, and weather conditions result in various kinds of interference in optical images, which makes it very difficult to detect the sea sky line accurately. To solve this problem, a sea sky line detection method is proposed based on gradient saliency. The line features of sea sky line are enhanced effectively through the computation of gradient saliency; other interference factors are suppressed; sea sky line detection and identification are achieved by region growing method. In the end, the proposed method is tested on optical images from “XL” USV in real marine environment and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of detection rate and real-time performance.

    Tools

    Get Citation

    Copy Citation Text

    Wang Bo, Su Yumin, Wan Lei, Zhuang Jiayuan, Zhang Lei. Sea Sky Line Detection Method of Unmanned Surface Vehicle Based on Gradient Saliency[J]. Acta Optica Sinica, 2016, 36(5): 511002

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Imaging Systems

    Received: Dec. 1, 2015

    Accepted: --

    Published Online: May. 3, 2016

    The Author Email: Bo Wang (wb@hrbeu.edu.cn)

    DOI:10.3788/aos201636.0511002

    Topics