71 / 2016-03-18 13:54:48
Underwater Image Segmentation Methods Based on MCA and Adaptive Level Set Evolution
5286,9589,9590,9591
全文录用
继嵩 白 / 哈尔滨工程大学
Noise and uneven gray levels in underwater image cause the low segment precision, this paper presents a segmentation method based on morphological component analysis (MCA) and adaptive level set evolution. MCA method is used to sparse decompose the image into texture and cartoon parts. The cartoon part contains the mainly information with less noise, which is good for segmentation. In order to obtain the image’s weaken edges, we combine the threshold piecewise function with the adaptive level set evolution’s variable right coefficient and halting speed function, and use the new method to segment the image’s cartoon part as the final result. At last, we use this paper method compare with the other adaptive level set evolution method to segment the different underwater images, the result can prove the paper’s method is more effective for the underwater image processing.
重要日期
  • 会议日期

    07月08日

    2016

    07月10日

    2016

  • 04月25日 2016

    终稿截稿日期

  • 05月20日 2016

    初稿截稿日期

  • 07月10日 2016

    注册截止日期

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