海洋学研究 ›› 2018, Vol. 36 ›› Issue (2): 44-49.DOI: 10.3969/j.issn.1001-909X.2018.02.006

• 研究论文 • 上一篇    下一篇

基于纹理特征的围填海SAR图像分水岭分割方法

王衍, 许小贝, 洪海凌   

  1. 海南省海洋监测预报中心,海南 海口 570206
  • 收稿日期:2016-10-09 修回日期:2018-01-20 出版日期:2018-06-15 发布日期:2022-11-21
  • 作者简介:王衍(1983-),男,安徽太和县人,高级工程师,主要从事海洋工程、海域管理等方面的研究。E-mail:13519800900@139.com
  • 基金资助:
    国家海洋公益性行业科研专项项目资助(201405028)

Watershed segmentation method for SAR image of reclamation based on texture feature

WANG Yan, XU Xiao-bei, HONG Hai-ling   

  1. Ocean Monitoring and Forecasting Center of Hainan Province,Haikou 570206, China
  • Received:2016-10-09 Revised:2018-01-20 Online:2018-06-15 Published:2022-11-21

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摘要： 本文提出了一种基于纹理特征的围填海SAR图像分水岭分割方法,首先对机载MiniSAR图像进行灰度共生矩阵纹理滤波,获得纹理特征图像,再对纹理特征图像进行分水岭算法分割,将获得的形态学重建图像进行门限阈值分割,得到最后的二值化分割结果。该方法一方面通过调整灰度共生矩阵纹理滤波的窗口大小,抑制了斑点噪声的影响;另一方面,利用分水岭算法对边缘模糊杂乱图像的优势,提高了围填海信息提取的准确性。实验结果表明,本方法对高分辨率SAR图像围填海监测图像的分割效果良好。

关键词: 机载MiniSAR, 围填海, 灰度共生矩阵, 分水岭, 图像分割

Abstract: The speckle noise of high resolution airborne MiniSAR image is serious, and in image the edge of the reclamation is fuzzy and messy. For more efficient extraction of reclamation information, a method of watershed segmentation was presented based on texture feature for SAR image of reclamation. First, the airborne MiniSAR image was filtered by the gray level co-occurrence matrix, and the texture feature image was obtained. Then the watershed algorithm was used to segment the texture feature image and to get the morphological reconstruction image, and finally, the threshold method was used to segment the morphological image, and to get the final results of the two values. On the one hand, this method suppresses the influence of speckle noise by adjusting the gray co-occurrence matrix texture filtering window size . On the other hand, it uses watershed algorithm of fuzzy edge clutter images to improve the accuracy of information extraction of sea reclamation. Test results show that this method is effective for the image segmentation of high resolution SAR image.

Key words: airborne MiniSAR, reclamation, gray level co-occurrence matrix, watershed, image segmentation

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